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European vs. American Investors: Two Worlds, Two Mindsets
Over the past weeks, I had the opportunity to attend two major events shaping my entrepreneurial perspective: the Venture Days in Luxembourg and the Web Summit in Lisbon. Both were intense, inspiring and at times overwhelming, especially because I was wearing all the hats at once.
Building a solid business plan, compelling a pitch deck, developing the software, managing stakeholders and potential customers, while simultaneously running a fast-growing open-source project is challenging. But these events gave me invaluable insights into how differently European and American investors think and why this has such a deep impact on how we must communicate.
European Investors
Pragmatic. Detail-driven. Break-even focused.
In Luxembourg and other European settings, conversations consistently revolved around questions such as:
- How fast can you reach break-even?
- Show me the exact numbers, prices and sources.
- How precisely is the market researched?
- What is the unit economics structure?
European investors tend to value stability, caution and predictability. They expect detailed business plans where every calculation is documented in depth. Market research, pricing models, competitive matrices and break-even analyses carry significant weight.
What is often missing is ambition.
The desire to change the world is frequently overshadowed by a culture centered around minimizing risk. Radical innovation becomes rare. Founders are encouraged to think small, stay safe and avoid big leaps. As a result, Europe produces far fewer breakthrough technologies.American Investors
Vision first. Details later.
The conversations I had with American investors, both in Luxembourg and Lisbon, felt dramatically different.
Their core interests centered around questions such as:
- How do you dominate the global market?
- What is the story and the movement you are building?
- How big can this become?
- What is the monopoly you are aiming for?
American-style investors think in terms of global market power, narrative, category creation and world-changing potential. They want to invest in huge visions and massive outcomes, even if the roadmap is not fully defined yet.
For them, communication must be bold, visionary and transformative.
This Creates a Communication Challenge
Switching between these mindsets is not easy. You cannot pitch the same story in Germany as you would in Silicon Valley.
That’s why I created a communication matrix that highlights the differences between the “German/European Approach” and the “American Approach”. It helps me stay conscious about how to communicate depending on the audience and their cultural expectations.
Pitching is not just about the product — it is about the mindset of the listener.
Why We Are Building Infinito.Nexus
Infinito.Nexus aims to become the universal platform for rapidly building sovereign IT infrastructure. Organizations should be able to operate an essentially unlimited number of SaaS applications behind a single SSO layer, fully sovereign, on any servers or providers they choose, without being exposed to monopoly pressure or external control.
Our vision extends to hardware. Laptops, servers and even smartphones will be delivered preconfigured, ready to use the very next day, and immediately integrated into a sovereign infrastructure. The platform becomes the foundation for sovereign IT by combining automated deployment, full application integration and ready-to-use hardware into one seamless ecosystem.
Different Expectations in the US and Europe
US investors respond strongly to the transformative scale of this vision. For them, we explicitly highlight that Infinito.Nexus aims to become the dominant platform for sovereign IT deployments worldwide. This may sound paradoxical in the context of sovereignty, yet it is entirely compatible. Everything remains open source and users remain free to host wherever they want, but they naturally stay with us because of convenience, automation and usability. The logic is identical to how people today choose Netflix instead of downloading movies or Spotify instead of pirating music. Convenience creates loyalty.
For US investors, we emphasize that this convenience-driven retention enables us to secure long-term platform dominance. In addition, we guarantee enterprise-level SLAs and large-scale managed deployment services when the infrastructure is provisioned through our platform, which further strengthens trust at the enterprise level and reinforces our strategic position.
European investors think differently. They place higher value on predictable steps, measurable risk management and immediate practical value. While they understand the long-term vision, they expect a grounded and incremental approach that fits the realities of the European market.
Adapting the European Narrative
For the European context we present a slower and more conservative scaling strategy. Instead of focusing immediately on global automation, we begin with B2B delivery teams that manually roll out sovereign environments for startups and technologically open young companies. This lowers perceived risk but increases operational cost and reduces speed, and it creates exposure to competitors who scale more aggressively. Nevertheless, this approach aligns with the European preference for reliability, trust-building and controlled expansion.
In addition, the European narrative places a much stronger emphasis on consulting. Unlike in the US narrative, where consulting is downplayed due to poor scalability, in Europe consulting is both expected and necessary. It gives us the ability to tailor environments more deeply to customer needs, particularly for complex ERP and CRM integrations that require significant customization. Consulting also reinforces the perception of reliability and competence, which is essential for conservative investors.
A Unified Perspective
Both narratives describe the same product and the same mission. The US approach highlights global market leadership, platform dominance supported by convenience retention and enterprise-level services. The European approach emphasizes concrete value, trust-building, customization and predictable growth. The difference is not in the substance of the platform, but in how the story is framed so each audience sees exactly why Infinito.Nexus fits their worldview and investment culture.
#americanInvestors #breakEvenAnalysis #businessPlan #cloudDeployment #digitalSovereignty #entrepreneurship #europeanInvestors #founderInsights #fundingStrategy #globalScaling #infinitoNexus #innovationMindset #investmentCulture #investorCommunication #itInfrastructureMarketplace #openSource #pitchStrategy #saasAutomation #sovereignCloud #startupEurope #startupFinancing #startupUsa #techEcosystem #unitEconomics #ventureCapital #ventureDaysLuxembourg #webSummitLisbon
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European vs. American Investors: Two Worlds, Two Mindsets
Over the past weeks, I had the opportunity to attend two major events shaping my entrepreneurial perspective: the Venture Days in Luxembourg and the Web Summit in Lisbon. Both were intense, inspiring and at times overwhelming, especially because I was wearing all the hats at once.
Building a solid business plan, compelling a pitch deck, developing the software, managing stakeholders and potential customers, while simultaneously running a fast-growing open-source project is challenging. But these events gave me invaluable insights into how differently European and American investors think and why this has such a deep impact on how we must communicate.
European Investors
Pragmatic. Detail-driven. Break-even focused.
In Luxembourg and other European settings, conversations consistently revolved around questions such as:
- How fast can you reach break-even?
- Show me the exact numbers, prices and sources.
- How precisely is the market researched?
- What is the unit economics structure?
European investors tend to value stability, caution and predictability. They expect detailed business plans where every calculation is documented in depth. Market research, pricing models, competitive matrices and break-even analyses carry significant weight.
What is often missing is ambition.
The desire to change the world is frequently overshadowed by a culture centered around minimizing risk. Radical innovation becomes rare. Founders are encouraged to think small, stay safe and avoid big leaps. As a result, Europe produces far fewer breakthrough technologies.American Investors
Vision first. Details later.
The conversations I had with American investors, both in Luxembourg and Lisbon, felt dramatically different.
Their core interests centered around questions such as:
- How do you dominate the global market?
- What is the story and the movement you are building?
- How big can this become?
- What is the monopoly you are aiming for?
American-style investors think in terms of global market power, narrative, category creation and world-changing potential. They want to invest in huge visions and massive outcomes, even if the roadmap is not fully defined yet.
For them, communication must be bold, visionary and transformative.
This Creates a Communication Challenge
Switching between these mindsets is not easy. You cannot pitch the same story in Germany as you would in Silicon Valley.
That’s why I created a communication matrix that highlights the differences between the “German/European Approach” and the “American Approach”. It helps me stay conscious about how to communicate depending on the audience and their cultural expectations.
Pitching is not just about the product — it is about the mindset of the listener.
Why We Are Building Infinito.Nexus
Infinito.Nexus aims to become the universal platform for rapidly building sovereign IT infrastructure. Organizations should be able to operate an essentially unlimited number of SaaS applications behind a single SSO layer, fully sovereign, on any servers or providers they choose, without being exposed to monopoly pressure or external control.
Our vision extends to hardware. Laptops, servers and even smartphones will be delivered preconfigured, ready to use the very next day, and immediately integrated into a sovereign infrastructure. The platform becomes the foundation for sovereign IT by combining automated deployment, full application integration and ready-to-use hardware into one seamless ecosystem.
Different Expectations in the US and Europe
US investors respond strongly to the transformative scale of this vision. For them, we explicitly highlight that Infinito.Nexus aims to become the dominant platform for sovereign IT deployments worldwide. This may sound paradoxical in the context of sovereignty, yet it is entirely compatible. Everything remains open source and users remain free to host wherever they want, but they naturally stay with us because of convenience, automation and usability. The logic is identical to how people today choose Netflix instead of downloading movies or Spotify instead of pirating music. Convenience creates loyalty.
For US investors, we emphasize that this convenience-driven retention enables us to secure long-term platform dominance. In addition, we guarantee enterprise-level SLAs and large-scale managed deployment services when the infrastructure is provisioned through our platform, which further strengthens trust at the enterprise level and reinforces our strategic position.
European investors think differently. They place higher value on predictable steps, measurable risk management and immediate practical value. While they understand the long-term vision, they expect a grounded and incremental approach that fits the realities of the European market.
Adapting the European Narrative
For the European context we present a slower and more conservative scaling strategy. Instead of focusing immediately on global automation, we begin with B2B delivery teams that manually roll out sovereign environments for startups and technologically open young companies. This lowers perceived risk but increases operational cost and reduces speed, and it creates exposure to competitors who scale more aggressively. Nevertheless, this approach aligns with the European preference for reliability, trust-building and controlled expansion.
In addition, the European narrative places a much stronger emphasis on consulting. Unlike in the US narrative, where consulting is downplayed due to poor scalability, in Europe consulting is both expected and necessary. It gives us the ability to tailor environments more deeply to customer needs, particularly for complex ERP and CRM integrations that require significant customization. Consulting also reinforces the perception of reliability and competence, which is essential for conservative investors.
A Unified Perspective
Both narratives describe the same product and the same mission. The US approach highlights global market leadership, platform dominance supported by convenience retention and enterprise-level services. The European approach emphasizes concrete value, trust-building, customization and predictable growth. The difference is not in the substance of the platform, but in how the story is framed so each audience sees exactly why Infinito.Nexus fits their worldview and investment culture.
#americanInvestors #breakEvenAnalysis #businessPlan #cloudDeployment #digitalSovereignty #entrepreneurship #europeanInvestors #founderInsights #fundingStrategy #globalScaling #infinitoNexus #innovationMindset #investmentCulture #investorCommunication #itInfrastructureMarketplace #openSource #pitchStrategy #saasAutomation #sovereignCloud #startupEurope #startupFinancing #startupUsa #techEcosystem #unitEconomics #ventureCapital #ventureDaysLuxembourg #webSummitLisbon
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European vs. American Investors: Two Worlds, Two Mindsets
Over the past weeks, I had the opportunity to attend two major events shaping my entrepreneurial perspective: the Venture Days in Luxembourg and the Web Summit in Lisbon. Both were intense, inspiring and at times overwhelming, especially because I was wearing all the hats at once.
Building a solid business plan, compelling a pitch deck, developing the software, managing stakeholders and potential customers, while simultaneously running a fast-growing open-source project is challenging. But these events gave me invaluable insights into how differently European and American investors think and why this has such a deep impact on how we must communicate.
European Investors
Pragmatic. Detail-driven. Break-even focused.
In Luxembourg and other European settings, conversations consistently revolved around questions such as:
- How fast can you reach break-even?
- Show me the exact numbers, prices and sources.
- How precisely is the market researched?
- What is the unit economics structure?
European investors tend to value stability, caution and predictability. They expect detailed business plans where every calculation is documented in depth. Market research, pricing models, competitive matrices and break-even analyses carry significant weight.
What is often missing is ambition.
The desire to change the world is frequently overshadowed by a culture centered around minimizing risk. Radical innovation becomes rare. Founders are encouraged to think small, stay safe and avoid big leaps. As a result, Europe produces far fewer breakthrough technologies.American Investors
Vision first. Details later.
The conversations I had with American investors, both in Luxembourg and Lisbon, felt dramatically different.
Their core interests centered around questions such as:
- How do you dominate the global market?
- What is the story and the movement you are building?
- How big can this become?
- What is the monopoly you are aiming for?
American-style investors think in terms of global market power, narrative, category creation and world-changing potential. They want to invest in huge visions and massive outcomes, even if the roadmap is not fully defined yet.
For them, communication must be bold, visionary and transformative.
This Creates a Communication Challenge
Switching between these mindsets is not easy. You cannot pitch the same story in Germany as you would in Silicon Valley.
That’s why I created a communication matrix that highlights the differences between the “German/European Approach” and the “American Approach”. It helps me stay conscious about how to communicate depending on the audience and their cultural expectations.
Pitching is not just about the product — it is about the mindset of the listener.
Why We Are Building Infinito.Nexus
Infinito.Nexus aims to become the universal platform for rapidly building sovereign IT infrastructure. Organizations should be able to operate an essentially unlimited number of SaaS applications behind a single SSO layer, fully sovereign, on any servers or providers they choose, without being exposed to monopoly pressure or external control.
Our vision extends to hardware. Laptops, servers and even smartphones will be delivered preconfigured, ready to use the very next day, and immediately integrated into a sovereign infrastructure. The platform becomes the foundation for sovereign IT by combining automated deployment, full application integration and ready-to-use hardware into one seamless ecosystem.
Different Expectations in the US and Europe
US investors respond strongly to the transformative scale of this vision. For them, we explicitly highlight that Infinito.Nexus aims to become the dominant platform for sovereign IT deployments worldwide. This may sound paradoxical in the context of sovereignty, yet it is entirely compatible. Everything remains open source and users remain free to host wherever they want, but they naturally stay with us because of convenience, automation and usability. The logic is identical to how people today choose Netflix instead of downloading movies or Spotify instead of pirating music. Convenience creates loyalty.
For US investors, we emphasize that this convenience-driven retention enables us to secure long-term platform dominance. In addition, we guarantee enterprise-level SLAs and large-scale managed deployment services when the infrastructure is provisioned through our platform, which further strengthens trust at the enterprise level and reinforces our strategic position.
European investors think differently. They place higher value on predictable steps, measurable risk management and immediate practical value. While they understand the long-term vision, they expect a grounded and incremental approach that fits the realities of the European market.
Adapting the European Narrative
For the European context we present a slower and more conservative scaling strategy. Instead of focusing immediately on global automation, we begin with B2B delivery teams that manually roll out sovereign environments for startups and technologically open young companies. This lowers perceived risk but increases operational cost and reduces speed, and it creates exposure to competitors who scale more aggressively. Nevertheless, this approach aligns with the European preference for reliability, trust-building and controlled expansion.
In addition, the European narrative places a much stronger emphasis on consulting. Unlike in the US narrative, where consulting is downplayed due to poor scalability, in Europe consulting is both expected and necessary. It gives us the ability to tailor environments more deeply to customer needs, particularly for complex ERP and CRM integrations that require significant customization. Consulting also reinforces the perception of reliability and competence, which is essential for conservative investors.
A Unified Perspective
Both narratives describe the same product and the same mission. The US approach highlights global market leadership, platform dominance supported by convenience retention and enterprise-level services. The European approach emphasizes concrete value, trust-building, customization and predictable growth. The difference is not in the substance of the platform, but in how the story is framed so each audience sees exactly why Infinito.Nexus fits their worldview and investment culture.
#AmericanInvestors #breakEvenAnalysis #businessPlan #cloudDeployment #DigitalSovereignty #entrepreneurship #EuropeanInvestors #founderInsights #fundingStrategy #globalScaling #InfinitoNexus #innovationMindset #investmentCulture #investorCommunication #ITInfrastructureMarketplace #OpenSource #pitchStrategy #SaaSAutomation #sovereignCloud #startupEurope #startupFinancing #startupUSA #techEcosystem #unitEconomics #ventureCapital #VentureDaysLuxembourg #WebSummitLisbon -
European vs. American Investors: Two Worlds, Two Mindsets
Over the past weeks, I had the opportunity to attend two major events shaping my entrepreneurial perspective: the Venture Days in Luxembourg and the Web Summit in Lisbon. Both were intense, inspiring and at times overwhelming, especially because I was wearing all the hats at once.
Building a solid business plan, compelling a pitch deck, developing the software, managing stakeholders and potential customers, while simultaneously running a fast-growing open-source project is challenging. But these events gave me invaluable insights into how differently European and American investors think and why this has such a deep impact on how we must communicate.
European Investors
Pragmatic. Detail-driven. Break-even focused.
In Luxembourg and other European settings, conversations consistently revolved around questions such as:
- How fast can you reach break-even?
- Show me the exact numbers, prices and sources.
- How precisely is the market researched?
- What is the unit economics structure?
European investors tend to value stability, caution and predictability. They expect detailed business plans where every calculation is documented in depth. Market research, pricing models, competitive matrices and break-even analyses carry significant weight.
What is often missing is ambition.
The desire to change the world is frequently overshadowed by a culture centered around minimizing risk. Radical innovation becomes rare. Founders are encouraged to think small, stay safe and avoid big leaps. As a result, Europe produces far fewer breakthrough technologies.American Investors
Vision first. Details later.
The conversations I had with American investors, both in Luxembourg and Lisbon, felt dramatically different.
Their core interests centered around questions such as:
- How do you dominate the global market?
- What is the story and the movement you are building?
- How big can this become?
- What is the monopoly you are aiming for?
American-style investors think in terms of global market power, narrative, category creation and world-changing potential. They want to invest in huge visions and massive outcomes, even if the roadmap is not fully defined yet.
For them, communication must be bold, visionary and transformative.
This Creates a Communication Challenge
Switching between these mindsets is not easy. You cannot pitch the same story in Germany as you would in Silicon Valley.
That’s why I created a communication matrix that highlights the differences between the “German/European Approach” and the “American Approach”. It helps me stay conscious about how to communicate depending on the audience and their cultural expectations.
Pitching is not just about the product — it is about the mindset of the listener.
Why We Are Building Infinito.Nexus
Infinito.Nexus aims to become the universal platform for rapidly building sovereign IT infrastructure. Organizations should be able to operate an essentially unlimited number of SaaS applications behind a single SSO layer, fully sovereign, on any servers or providers they choose, without being exposed to monopoly pressure or external control.
Our vision extends to hardware. Laptops, servers and even smartphones will be delivered preconfigured, ready to use the very next day, and immediately integrated into a sovereign infrastructure. The platform becomes the foundation for sovereign IT by combining automated deployment, full application integration and ready-to-use hardware into one seamless ecosystem.
Different Expectations in the US and Europe
US investors respond strongly to the transformative scale of this vision. For them, we explicitly highlight that Infinito.Nexus aims to become the dominant platform for sovereign IT deployments worldwide. This may sound paradoxical in the context of sovereignty, yet it is entirely compatible. Everything remains open source and users remain free to host wherever they want, but they naturally stay with us because of convenience, automation and usability. The logic is identical to how people today choose Netflix instead of downloading movies or Spotify instead of pirating music. Convenience creates loyalty.
For US investors, we emphasize that this convenience-driven retention enables us to secure long-term platform dominance. In addition, we guarantee enterprise-level SLAs and large-scale managed deployment services when the infrastructure is provisioned through our platform, which further strengthens trust at the enterprise level and reinforces our strategic position.
European investors think differently. They place higher value on predictable steps, measurable risk management and immediate practical value. While they understand the long-term vision, they expect a grounded and incremental approach that fits the realities of the European market.
Adapting the European Narrative
For the European context we present a slower and more conservative scaling strategy. Instead of focusing immediately on global automation, we begin with B2B delivery teams that manually roll out sovereign environments for startups and technologically open young companies. This lowers perceived risk but increases operational cost and reduces speed, and it creates exposure to competitors who scale more aggressively. Nevertheless, this approach aligns with the European preference for reliability, trust-building and controlled expansion.
In addition, the European narrative places a much stronger emphasis on consulting. Unlike in the US narrative, where consulting is downplayed due to poor scalability, in Europe consulting is both expected and necessary. It gives us the ability to tailor environments more deeply to customer needs, particularly for complex ERP and CRM integrations that require significant customization. Consulting also reinforces the perception of reliability and competence, which is essential for conservative investors.
A Unified Perspective
Both narratives describe the same product and the same mission. The US approach highlights global market leadership, platform dominance supported by convenience retention and enterprise-level services. The European approach emphasizes concrete value, trust-building, customization and predictable growth. The difference is not in the substance of the platform, but in how the story is framed so each audience sees exactly why Infinito.Nexus fits their worldview and investment culture.
#AmericanInvestors #breakEvenAnalysis #businessPlan #cloudDeployment #DigitalSovereignty #entrepreneurship #EuropeanInvestors #founderInsights #fundingStrategy #globalScaling #InfinitoNexus #innovationMindset #investmentCulture #investorCommunication #ITInfrastructureMarketplace #OpenSource #pitchStrategy #SaaSAutomation #sovereignCloud #startupEurope #startupFinancing #startupUSA #techEcosystem #unitEconomics #ventureCapital #VentureDaysLuxembourg #WebSummitLisbon -
Why India Will Not Overtake China
There is a thought I have been sitting with for a while, and I want to put it out without dressing it up.
India is not going to overtake China. People hate hearing this. They will quote our GDP growth, our young population, our rising number of unicorns, the size of our talent pool. None of that is the real story. The real story is harder to fix because it does not sit inside policy or money. It sits inside the way Indians treat each other.India is a low trust society trying to behave like a high trust one. Until that gap closes, real scale will keep slipping out of our hands.
I know this sounds like opinion, so let me show you the research, because the work on this question is actually quite settled.
In 1997, two economists named Stephen Knack and Philip Keefer published a paper in the Quarterly Journal of Economics. They studied 29 countries and found a clear link between how much people in a country trust strangers and how well that country performs economically. More trust meant stronger growth, better institutions and lower corruption. They never claimed trust was the only thing that mattered. But they showed it mattered a lot. That paper is now one of the most cited works in development economics.
Around the same time, the political thinker Francis Fukuyama wrote a full book called Trust. His argument was simple. Countries that build large, well run institutions almost always sit on top of high social trust. When trust is missing, what you usually see is small family run businesses that struggle to grow past one or two generations.
When you actually look at the numbers, the gap between countries is huge. The Integrated Values Surveys, which collect this data through 2022, show that around seventy four percent of people in Denmark say most people can be trusted. Norway is at about seventy two. Finland at sixty eight. China comes in fourth in the world at around sixty three percent. It is the only country outside the West in the top group. India does not appear anywhere near these numbers. Researchers from IZA and other peer reviewed journals openly call India a low trust country, often using exactly that phrase in the very first line of their paper.
Corruption follows the same pattern, because trust and corruption are basically two sides of the same coin. In Transparency International’s 2024 Corruption Perceptions Index, India is ranked 96 out of 180 countries, with a score of 38 out of 100. China sits at 76. Denmark, Finland and Singapore are at the very top. These rankings are not random. The same countries that score high on trust also score low on corruption. Both numbers come from the same habit, the habit of strangers behaving honestly even when no one is watching them.
The Indian version of this problem actually has a name in academic literature. We have just not started using it.
In 1958, an American political scientist called Edward Banfield went to live for nine months in a poor village in southern Italy called Chiaromonte. He was trying to understand why the village stayed poor for generations even though the people there were perfectly capable. The book he wrote afterwards, The Moral Basis of a Backward Society, gave us a concept called amoral familism. Banfield described it as a community where everyone tries to maximize benefits for their own immediate family, and assumes everyone else is doing the same. The result was a village that could not act together for any common goal. Nobody trusted their neighbours or the institutions around them. Anything outside the household was treated as either a threat or something to quietly take from. Years later, the political scientist Robert Putnam expanded this work across all of Italy and showed that the more trusting north of Italy consistently performed better than the south on almost every measure of governance and prosperity.
Read Banfield’s description today, replace the word village with India, and the fit is uncomfortably close.
We trust our family fully. We trust our caste, region and community a little. Beyond that small circle, we are always on guard. We feel that someone is trying to use us, replace us, take credit for our work, or take our seat the moment we stand up. And the painful part is that this fear is not really paranoia. It is mostly an honest reading of how things work around us. So people protect themselves first, and stop sharing what they know. When a billion people behave this way every day, the loss to the country is huge, even if no one can see it directly.
You can feel this in daily Indian life. The senior who refuses to truly invest in juniors, because a junior who grows is a junior who might one day take their place. The manager who hides information from the team, because letting them learn feels like a personal risk. The bureaucrat who refuses to move a file unless something is in it for him. The politician who treats public money like personal property. The friend quietly happy when you slow down, because your stagnation makes their position look stronger. The cousin who quietly damages the family business from inside, because grabbing a small piece feels safer than working together to grow the whole.
This is what failure to coordinate looks like at the level of a country.
China is not a clean society. Anyone who follows even basic Chinese politics knows the place has heavy corruption. The Xi government has been running an anti corruption campaign for over ten years and has prosecuted more than a million officials. The political system itself is closed, full of internal rivalry and favouritism. Yet despite all of that, China still manages to execute at a scale we cannot match. They built one of the largest fast rail networks in the world in around two decades. They built industries that made them the world leader in solar panels, electric vehicles, lithium batteries and now AI hardware. Their Belt and Road projects now reach more than a hundred countries. You can disagree with their political system, but the execution is real and visible.
India has stronger democratic freedoms and arguably better human capital. Yet we keep failing to turn these advantages into coordinated national outcomes. The bottleneck is not intelligence. It is the ability to coordinate. And the ability to coordinate, when you really break it down, is just trust wearing institutional clothes.
The Nordic countries make this point even more clearly.
Denmark, Sweden, Norway, Finland and Iceland together have a population smaller than greater Mumbai. Apart from Norway’s oil, they have almost no natural resources. They are cold, sparsely populated and were historically poor. And yet today they sit at the top of almost every global ranking that matters in the modern world. Innovation. Healthcare. Governance. Ease of doing business. Life expectancy. Happiness.
The OECD and the World Happiness Report keep pointing to one main reason. Their generalized trust is extremely high. Citizens trust each other and trust their institutions. So contracts work. Taxes actually reach the people they were meant for. Rules get followed even without surveillance. Society does not get jammed by its own friction. Their citizens are not smarter than ours. Their cooperation between strangers is just much denser.
Researchers describe two kinds of trust. Particularized trust is what you give to people you already know. Generalized trust is what you extend to strangers. India is rich in the first and very poor in the second. This one gap explains the strange paradox we live in every day. We send world class individuals to top companies and boardrooms abroad, while our own institutions back home keep struggling. The individual rises because the family invested in that one person. The system stays broken because almost nobody truly invests in the system.
I want to be careful here, because this argument is easy to misread.
I am not saying Indians are bad people. That framing is lazy and wrong. The argument is about the cultural operating system we have inherited. That operating system was shaped over centuries of foreign rule, scarcity and a long history where trusting outsiders often ended badly for the trusting side. Once upon a time, this software helped us survive. The price we pay for it today is that we cannot bring our brilliance together the way countries with stronger social capital can. A billion careful, guarded individuals do not add up to a coordinated nation. They cancel each other out at the edges, and the noise becomes louder than the progress.
If India ever truly wants to challenge China, the real work has to go much deeper than infrastructure spending or new policies. The real work is internal. It is about widening the trust circle outward from family to strangers. It is about senior people mentoring others without fearing being overtaken. It is about backing talent that does not share our caste, our region or our background. It is about believing that the collective will eventually protect us, and then actually showing up for someone else when their moment comes.
Until that quiet inner shift happens, India will keep producing brilliant individuals who win alone, while the operating system underneath us keeps failing as a whole. And that, more than any economic chart anyone can show me, is the real reason the China gap is going to stay wider than we are willing to admit.Type your email…
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#Citizens #Colonialism #Corruption #Economy #Fear #Freedom #Government #India #Policy #Politics #Society #Trust -
Turning Saffron into Slop – Treylya Safran yn Skomblans
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
Note: Artificial Intelligence (AI) has come to be synonymous with Generative AI (GenAI) and with Large Language Models (LLMs), such as ChatGPT, in common parlance. Unless explicitly stated, I use the terms interchangeably.
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow*, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
LOW-RESOURCES AND LINGUISTIC TYPOLOGY
Simply adding a language to an AI model leads to a spike in poor-quality articles, drowning out quality writing by humans. AI has “industrialized the acts of destruction—which affect vulnerable languages most, since AI translations are typically far less reliable for them.”1 Wikipedia editors from varied languages evidence that machine translation tools have made it easier than ever before to create shoddy articles in minoritised languages, causing massive damage in minutes. AI leads to non-speakers producing much longer, truthier rubbish, Sámi computational linguistics expert Trond Trosterud notes: “the problem [is] that they are armed with Google Translate. Earlier they were armed only with dictionaries.”1
Kernewek, like all but 60 of the world’s roughly 7,000 languages, is designated “low-resource”, meaning it lacks sufficient data to train a machine.2 It is tempting, therefore, to assume that the solution is to provide more data. However, training an LLM requires petabytes of text, audio and video—manually categorised and in a machine-readable format—a vast trove that Kernewek simply does not have.3 Professor Will Lamb, Chair of Gaelic Ethnology and Linguistics at Edinburgh University, speaks of “millions of work hours devoted to just one aspect” of a working AI.4
Even if ChatGPT is trained on another language than English, the time and labour required may make it largely unviable. Current assessments of the performance of ChatGPT for different languages have shown that it performs worse in all tasks.5
Prof. Lina Dencik, Data Justice Lab
Furthermore, the amount of data and work is not the only barrier; at issue is the nature of the language itself. Microsoft has found that languages such as Breton—and thus Kernewek—cause a high rate of errors distinct from the size of their dataset, due to grammatical features, such as mutation, not present in well-sourced languages. As such, they remain poor without significant additional work.6 Essentially, simply adding more Kernewek may not help. Thus, engaging with AI is, for Kernewek, to tie ourselves to slop.
Noten: Skians Kreftus (SK) re dheuth ha bos kesstyr gans SK Dinythus (SKDin) ha gans Patronyow Yeth Bras (PYB), kepar ha ChatGPT, yn lavar kemmyn. Marnas bos menegys yn kler, my a us an termys yn keschanjyadow.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow*, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
ASNODHOW ISL HA TIPOLOGIETH YETHEL
Keworra yeth yn sempel orth patron SK a led orth spik yn erthyglow drog aga kwalita, ow peudhi skrif a gwalita gans tus. SK re wrug “diwysyansegi an aktys diswrians—hag a nas yethow goliadow an moyha, drefen bos treylyansow SK lieskweyth le lel yn tipek ragdha.”1 Golegydhyon Wikipedia a yethow divers a re dustuni re wrug medhelweyth-treylya y wul bos esya dell veu bythkweth kyns gwruthyl erthyglow pilyek yn yethow lyharivhes, ow kawsya damach kowrek yn mynysennow. SK a led orth digowsoryon owth askorra atal lieskweyth hirra ha gwirekka, konnyk yethonieth reknansek Sámi Trond Trosterud a not: “an kudyn [yw] aga bos ervys gans Google Translate. A-varra nyns ens ervys marnas gans gerlyvrow.”1
Kernewek, kepar hag oll marnas 60 a ogas lowr 7,000 yeth a’n bys, yw klassys avel “isel y asnodhow”, ow styrya nag eus dhodho kedhlow lowr dhe drenya jynn.2 Rakhenna, dynyek yw desevos bos an assoylyans profya moy a gedhlow. Byttegyns, res yw petavaytys a dekst, son ha gwydhyow—klassys dre leuv hag yn furvas redyadow gans jynn— dhe drenya PYB, tresorva efan nag eus dhe Gernewek yn sempel.3 Y kews Professor Will Lamb, Kaderyer Ethnologieth ha Yethonieth Wodhalek orth Pennskol Karedin, a “vilvilyow a ourys ober sakrys orth unn wedh hepken” a SK owth oberi.4
Hogen mars yw ChatGPT trenys war yeth a-der Sowsnek, an termyn hag ober yw res a styr y vos martesen anhewul dre vras. Arvreusyansow a-lemmyn a berformyans a ChatGPT rag yethow dyffrans re dhiskwedhas y perform gweth yn oberennow oll.5
Prof. Lina Dencik, Data Justice Lab
Pella, nyns yw an myns a gedhlow hag ober an unsel lett; a vern yw natur an yeth y honan. Microsoft re drovyas y kaws yethow kepar ha Bretonek—hag ytho Kernewek—kevradh ughel a wallow diblans a vraster aga sett kedhlow, drefen nasyow gramasek, kepar ha treylyansow, nag usi kevys yn yethow ughel aga asnodhow. Yndella, i a bes orth bos drog heb meur a ober keworransel.6 Yn essensek, possybyl yw ny wra keworra moy a Gernewek yn sempel gweres. Yndelma, oberi gans SK yw, rag Kernewek, omgelmi orth skomblans.
CORNISH UNDER CAPITALISM
But surely we can improve things over time? It will take a lot of help from AI companies, but it will be worth it. Sadly, Gabriel Nicholas, a research fellow at the Center for Democracy and Technology, has found that once a tech company has established basic capabilities for a language, they pat themselves on the back and move on.7
Big tech companies are just that: companies. They exist to make a profit. Unfortunately, a market dominated by big languages gives them no incentive to invest in improvements for small ones.
All of the speech technology, smart homes and voice interaction systems used today are the products of commercial research. To put it bluntly, they exist to either make money from your data, to sell you more goods and services, or to influence your thinking. None of this AI exists for the public good. […] Unless there is a strong enough economic argument, don’t expect big companies to rush into producing Welsh, Gaelic or Cornish speech systems.8
Prof. Ian McLoughlin, University of Kent
Should they decide that a Kernewek AI is a viable profit-making enterprise, our situation may even be worse than abandonment. As Dr. Fintan Mallory remarks, the dominant means of profit for privately-funded AI enterprises is to convert their tools into surveillance devices.9 As Kernewek is currently one of the UK’s only languages which is not currently easily surveillable, this poses a huge risk to Kernewek activism and the fight for self-determination in a state that seeks to criminalise dissent.
While we’re on the subject of Kernewek and its position under capitalism, let’s consider the human cost. I lost my 13-year career in language to AI as soon as English output became viable enough to excuse not paying a human. In the unlikely instance that we achieve an AI that can produce quality Kernewek, why would anyone bother paying speakers? The idea of AI sucking all the life out of my heritage language when we are struggling to survive as-is is appalling.
Simply put, profit is antithetical to people. While AI is the new favourite toy of profit, it will be antithetical to people. And a language is its people.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Combinations of characters on a screen mean nothing without agency and intention.10
Ross Perlin, Endangered Language Alliance
While language is not unique to humans, it is one of the chief parts of being human. It cannot be reduced to mere data, but is a highly social process.11 We all know how synthetic customer support via robot sounds or how AI fails to pick up nuance. As Dr. Mallory comments, “Language [is] something more like the soul of a community. You can’t store this in a machine. You can’t solve a human problem like linguicide with a view of language that removes the human component.”12
AI cannot comprehend Kernewek or any other language. It is a stochastic parrot: predicting what word is likely to follow the previous one.13 It cannot understand us. It cannot intend anything. If it tells you it feels delighted to help you, it is lying. I want our community to grow, but one hundred ‘Cornish-speaking’ computers do not add to it. One human does—bringing ideas and hopes and fears and foibles—and I do not think the Kernewek ‘speaking’ computers will add even one human to our community.
Worse, if it does, there is evidence from Microsoft to suggest that the use of GenAI on language tasks, even once a week, impairs cognitive ability to learn, leading to decreased engagement with the topic, overreliance on the technology and hobbled skills in independent problem-solving.14 By using AI tools to ‘teach’ a learner Kernewek, we may in fact be impairing their ability to learn the language at all without this crutch. We will make regurgitators in place of speakers.
Perlin also emphasises the human element, saying that when we hold community central to our languages, as we do, the stochastic parrot can feel like a violation.15 At the moment, I can tell when someone is using AI ‘Kernewek’ to me. The idea that one day I will not know when an outsider—someone I would welcome if they took up a book or a class—is puppeting my ancestors’ jaws and speaking through them is ghoulish. It has the instant sting of colonialism, of appropriation when one could appreciate, of parroting when one could join our chorus.
Hawai’ian scholar Ha‘alilio Solomon agrees: “It is painful, because it reminds us of all the times that our culture and language has been appropriated. We have been fighting tooth and nail in an uphill climb for language revitalization.[…] People are going to think that this is an accurate representation of the Hawaiian language.”16
TRUST AND COMMUNITY FEELING
The anti-machine backlash has long been simmering but is now seemingly breaking to the surface.17
NBC NEWS
The explosion of insults for AI itself (clanker, tinskin, toaster), its output (slop, dross, brainrot) and its users (slopper, groksucker, botlicker, second-hand thinker)—as well as others more clearly based on real-world slurs than I am comfortable to include—tells a tale of the general attitude of distrust and disgust towards the technology and its use on anglophone and other majority language internet.18 While the attitude among tech bros and corporates remains bombastic, for the general public AI is “becoming interchangeable with things that sort of suck.”19
Further, it’s not just majority languages with this negative view of AI as taint. A quick sampling of social media comments and likes regarding AI and Scottish Gaelic by Professor Lamb showed a split of 54% negative, 33% positive and 13% neutral. (Lamb, 2024) The sentiment of the top-rated negative comment was that AI is harmful and the second-highest that AI should be kept away from heritage languages.
What are we telling our descendants? That our language and culture isn’t worth the personal effort? That’s how I might read it, if I were them.20
Kernewek survey respondent
Kernewek paints an even starker picture, especially among younger and more technologically-savvy learners and speakers. A survey on Cornish Discord and Whatsapp found that 65% felt AI would be bad (11.5%) or very bad (53%) for the language. When asked what the community response should be to AI, 46% said we should prevent it and 27% avoid it, with only over-60s thinking that we should work with it.20
31% of respondents said using AI in Kernewek would cause them to feel estranged from the language, while 54% said that they would feel strongly estranged and 23% a little estranged from any organisation, resource or teacher using AI.
The response from those who gave their knowledge of AI as either “expert” or “good” was particularly damning. Everyone in this group responded that AI would be harmful for the language, that the use of AI would estrange them from a source strongly and that we should prevent the use of AI for Kernewek.
IDENTITY, AUTHENTICITY AND DIVERSITY
Aristotelis Ioannis Paschalidis, writing for UNESCO, was not speaking specifically about minoritised languages when he asked this, but the question resonates even more strongly for us: “How much loss of identity is one willing to sacrifice for efficiency?”21
Identity is of paramount importance to Kernewek speakers. Ute Wimmer’s study Reversing Language Shift: the Case of Cornish identified the language’s “function as a symbol of national identity” as the second highest motive (66%**) among speakers and learners, beaten only by Cornish culture (80%).22 This would seem cause for celebration, but when AI is added to the mix, it becomes a risk. Vincent Koc of Hyperlink states that AI can “inadvertently contribute to the dilution of language and cultural identity.”23
He also identifies that automating language learning or generation “may diminish the richness and authenticity that comes from human speakers who carry cultural histories in their speech.” Indeed, four studies by the University of Southern California have shown that using LLMs to assist writing “is linked to notable declines in linguistic diversity and may interfere with the societal and psychological insights language provides.”24
This is in English, one of the richest and largest languages in the world. Imagine the possible impact on a smaller language like Kernewek—with less documentation, less data, a tiny speakerbase and basically no money—and on its many language varieties and orthographies. Particular to the Kernewek context, Late speakers are already struggling to be seen as valid under the dominance of Middle. Do we think AI knows the difference? Thoughtlessly, it will either mix everything together, confusing everyone, or it will use Middle to overwhelm Late.
Generative AI-driven content creation, by favoring standardized languages, risks the disappearance of regional dialects.25
Barcelona supercomputing Center ….
Not only are varieties at risk; AI threatens to drown Kernewek as a whole. Perlin agrees that the linguistic flattening that occurred over centuries in English could manifest overnight in a minoritised language with AI at the helm—as it would be, being able to effortlessly outstrip human Kernewek. He raises concerns of LLMs freezing a language in place and even defining what it means to know the language, especially with low numbers of native speakers.26
Garbage translations multiply online like fake news. Native speakers of the languages in question are bypassed as being “too hard to find,” compared with automated methods of vetting that are completely disconnected from real-life communication. While larger and more powerful language communities may be able to hold the bots to account and even make strategic use of them, it is all too easy to imagine [a minority language] being overwhelmed.26
Ross Perlin, Endangered Language Alliance
Uncontrolled and in the hands of tech giants, synthetic Kernewek will outnumber and outmanoeuvre human Kernewek.
DATA SOVEREIGNTY AND COLONIALISM
Indigenous data sovereignty is the right of [an indigenous nation] to govern the collection, ownership, and application of its own data.27
Native Nations Institute
There are, however, indigenous cultures that are working on a more equitable relationship with AI. Tech without the giant requires resources, but it allows communities to retain data sovereignty over the cultural asset that is their language. Te Mana Raraunga, the Māori Data Sovereignty Network, has created a list of principles for the creation, use and sharing of Māori data, prioritising the need to enhance control for current and future Māori.
They raise a key point that should be considered carefully by stewards of linguistic and cultural knowledge: “Data from us, and about us and our resources, are valuable assets. Once control of it is lost, it is difficult to regain.”28 Decisions must not be taken lightly or hastily; we can always say “yes” if we have previously said “no” to a particular dataset’s use, but can never say “no” if we have already said “yes”.
The AI field, like any other space, is occupied by people who are set in their ways and unintentionally have a very colonial perspective.29
Michael Running Wolf, First Languages AI Reality
This is vital in the context of the potential control of Kernewek data by powerful external corporations. Capitalist extractivism has long been a bane on societies in the imperial periphery and our Cornish society is no different, having faced centuries of its wealth and natural resources being stripped and sold by and large for the profit of those outside Cornwall.
The book Indigenous Data Sovereignty and Policy notes that current data relations can be seen as “a continuation of the processes and underlying belief systems of extraction, exploitation, accumulation and dispossession that have been visited on Indigenous populations through historical colonialism.”30 This extractive understanding of information is, they note, not disrupted but rather replicated by paying people for their data.
Ultimately, our language must not lie in outside hands governed by proprietary principles that do not allow us sufficient sovereignty over one of our most valuable natural resources: our language. We must have open data principles, not bow to corporate control. We must steer and steward the use of our data, rather than expose it to use against our interests and for the pockets of big tech.
Rather than approaching language preservation as a technical problem, I think indigenous communities need to be politically empowered, whether that be funding from governments or legal protections to use their languages.31
Dr. Fintan Mallory, Durham University
We must prioritise language-as-community and seek open, equitable and ethical use of our language, heritage and other cultural assets. We must avoid thinking of AI as the magic that it promises and invest in basic research, driven by our own community. Corporations will not save us and, indeed, may do us great harm.
NO CORNISH ON A DEAD PLANET
Global capitalism and governments […] are addicted to ‘free’ market ideology over the wellbeing of communities, people and the planet.32
Cymdeithas yr Iaith Maniffesto 2022
Honestly, most takedowns of AI would have hit this point already. It’s one of the main arguments against Generative AI, but in case you’re not familiar with it, we will briefly look over the main points.
Water used in cooling AI data centers must be drinkable water. AI guzzles this water. The University of California has reported that “global water demand from AI could reach 4.2-6.6 billion cubic meters by 2027. That exceeds 50 percent of the UK’s annual water use in 2023.”33 All this while the Global Commission on the Economics of Water has declared “a rapidly accelerating water crisis” to which Kernewek should not be contributing.34
We have become utterly dependent on private technologies manufactured and controlled by a handful of opaque companies [who] appear mostly indifferent to the social consequences of their activities and only invest minimally if obliged by government regulations to enhance their public image.35
Iker Erdocia, Dublin City University
AI requires vast quantities of hardware at the cost of mining rare earth minerals. These are difficult to extract and purify and come with heavy environmental and social costs. They are often extracted from mines in countries with poorer environmental and labour protections. Reset states that “communities living near these mines, often indigenous or minority groups, regularly face land degradation, water contamination and human rights abuses. Much of this can be directly linked to the AI hardware.”36 When the hardware inevitably cooks and is useless, it is then thrown out as e-waste into poor communities. The potential advancement of Kernewek must not come at the expense of our sister indigenous and minority communities.
Training an also AI requires huge amounts of energy, soon perhaps as much as a small country37 and has an enormous carbon footprint.38 What is clear is that—through water usage, extractive industry, energy consumption and carbon footprint—AI is bad news for the struggling environment of the planet we live on and there is no Cornish on a dead planet.
MAKING AI AN EX-PARROT
Rather than making minority languages more accessible, AI is now creating an ever expanding minefield for students and speakers of those languages to navigate.39
mit technology review
We have heard of the vast improbability of getting AI to be able to mimic Kernewek in light of the costs in data, work, time and technology. We have considered the likely choice of cold negligence or surveillance product and the importance of data sovereignty. We have read about the effects on the livelihoods of Cornish speakers, as well as the the catastrophic costs to the environment and indigenous peoples.
We have learned that linguistic flattening by AI impoverishes its subjects and how AI may decide for us how our language must operate. We have seen the inescapability of language as human and the risks of creating ‘learners’ who cannot learn and ‘speakers’ who cannot speak. We have seen the dangers to reputation and trust for any organisation who would shovel what is seen as ‘slop’.
We have heard why giving in to the juggernaut of AI would be a mistake for Kernewek and how our community does not support our laying down of the shield. Instead, we must fight. We must make Kernewek a space as free of slop as possible, we must educate botlickers into ethical and effective language learning and use, we must avoid second-hand thinking.
We must make our language a no AI zone, a network of reliable humans and their human creations, built on authenticity, community, effort and trust: a Kernewek for the people, of the people and by the people.
KERNEWEK YN-DANN GEVALAV
Mes yn sur y hyllyn ni gwellhe taklow dres termyn? Y fydh res meur a weres a gompanis SK, mes y talvia dhyn. Yn trist, Gabriel Nicholas, kesvroder hwithrans orth an Center for Democracy and Technology, re drovyas pan wrug kompani tek fondya gallosow selyek rag unn yeth, i a omgeslowenha yn ughel hag ena movya yn-rag.7
Kompanis tek bras yw yndella poran: kompanis. Ymons i ena rag gwaynya budh. Y’n gwettha prys, ny wra marghas rewlys gans yethow bras ri kentryn dhe gevarghewi yn gwellhe rag an re byghan.
Oll a’n deknegieth kows, chiow konnyk ha systemow ynterweythres lev usys hedhyw yw an askorrasow a hwithrans kenwerthel. Dhe vos sogh, yth yns i po rag dendyl arghans a’th kedhlow, po gwertha gwara ha gonisyow, po delenwel dha dybyansow. Nyns yw tra vyth a’n SK ma rag an les kemmyn. […] Mar nag eus argyans erbysek krev lowr, na wra gwaytya kompanis bras dhe fyski dhe askorra systemow kows Kembrek, Godhalek po Kernewek.8
Prof. Ian McLoughlin, pennskol kint
Ha mars ervirons bos SK Kernewek aventur a yll gwaynya budh, possybyl yw bos agan studh gweth ages dell via gans forsakyans. Dell lever Dr. Fintan Mallor, an fordh vrassa a waynya budh rag kompanis SK arghesys yn privedh yw kedreylya aga thoulys yn devisyow aspians.9 Drefen bos Kernewek onan a’n yethow boghes y’n RU nag yw aspiadow yn es y’n eur ma, hemm yw peryl kowrek rag gweythresieth Kernewek ha’gan strif a-barth omdhetermyans yn stat a vynn galweythegi dissent.
Ha ni ow tochya Kernewek ha’y savla yn-dann gevalav, gwren ni mires orth an kost denel. My a gellis ow soodh 13 bloodh yn yethow dhe SK kettooth ha dell veu eskorrans Sowsnek hewul lowr dhe askusya sevel orth tyli den. Y’n kas diwirhaval may kevyn SK hag a yll askorra Kernewek da, prag y hwrussa nebonan omankombra ow pe kowser? An tybyans a SK ow tenna oll an bewnans a’m taves ertach ha ni ow kwynnel dhe dreusvewa dell on yw skruthus.
Yn sempel, budh yw gorthenebel orth tus. Hedre vo SK an degen nowydh flamm a vudh, y fydh gorthenebel orth tus. Ha yeth yw hy thus.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Nyns eus styr dhe gesunyansow a lytherennow war skrin heb dewis ha heb mynnas.10
Ross Perlin, Endangered Language Alliance
Kyn nag yw yeth dibarow dhe dhensys, onan a’n rannow chif a vos denel yw. Ny yll bos lehes dhe gedhlow hepken, mes yth yw argerdh sosyel dres eghen.11 Ni oll a wor py mar synthesek y sen skoodhyans prener der SK po fatel yll SK fyllel orth konvedhes arliwyow. Dell gampol Dr. Mallory, “Yeth [yw] neppyth moy kepar hag enev a gemeneth. Ny yllir gwitha hemma yn jynn. Ny yllir assoylya kudyn denel kepar ha yethladhans gans gwel a yeth hag a remov an gerann denel.”12
Ny yll SK konvedhes Kernewek po taves vyth aral. Papynjay chonsus yw: y targan py ger yw gwirhaval wosa an huni kyns.13 Ny yll agan konvedhes. Ny yll mynnes tra vyth. Mar kwra derivas orthis y vos pes da dha weres, gow yw. My a vynn agan kemeneth dhe devi, mes ny wra kans jynn-amontya a yll ‘kewsel Kernewek’ keworra orti. Y hwra unn den—ow tri tybyansow ha govenegow hag ownow ha gwanderyow—ha ny dybav y hwra an jynnys-amontya kernwegorek keworra unn den hogen orth agan kemeneth.
Gwettha, mar kwra, yma dustuni a-dhyworth Microsoft hag a brof y hwra an devnydh a SKDin war oberennow yeth, unweyth an seythen hogen, aperya gallos godhvosel a dhyski, ow ledya orth omworrans lehes gans an desten, gorfydhyans y’n deknegieth ha sleyneth sprallys a assoylya kudynnow yn anserghek.14 Der usya toulys SK dhe ‘dhyski’ Kernewek, possybyl yw ni dhe shyndya gallos dyski an yeth vytholl heb an kroch ma. Ni a wra gul mimyoryon yn le Kernewegoryon.
Ynwedh Perlin a boslev an elven dhenel, ow leverel pan wren ni synsi kemeneth avel kres agan yethow, dell wren, an papynjay chonsus a yll bos klewys kepar ha defolyans.15 Y’n eur ma, my a aswon pan eus nebonan owth usya ‘Kernewek’ SK dhymm. An tybyans ny wrav vy unn jydh godhvos pan eus estren—nebonan a wrussen vy dynerghi mar pe lyver po klass ganses—ow popettya diwawen ow hengerens ha kewsel dresta yw bedhrosus. Yma dhe’n dra an wan dhistowgh a drevesigeth, a berghenegyans pan yllir gwerthveurhe, a bapynjaya pan yllir junya agan kesgan.
Unver yw skolheyk Hawai’i henwys Noah Ha‘alilio Solomon: “Ankensi yw, drefen ni dhe vos kofhes a’n prysyow oll re beu agan gonisogeth ha yeth perghenegys. Ni re beu owth omladh dre dhens hag ewines yn batel gales a-barth dasvewheans yeth.[…] Y hwra pobel krysi bos hemma representyans ewn a’n yeth a Hawai’i.”16
TREST HAG OMGLEWANS AN GEMENETH
Hir re beu an kil-lash gorthjynn ow kovryjyon mes lemmyn yma va ow terri an arenep dell hevel.17
NBC NEWS
Tardh an arvedhennow rag SK y honan (clanker, tinskin, toaster), y askorras (slop, dross, brainrot) ha’y usyoryon (slopper, groksucker, botlicker, second-hand thinker)—keffrys hag erel selys moy yn kler war geryow kas gwir dell ov attes gans aga heworra—a re hwedhel a stons ollgemmyn a wogrys ha divlases war-tu hag an deknegieth ha’y devnydh war an kesrosweyth Sowsnek ha yethow bras erel.18 Kynth yw an stons yn-mysk gwesyon dek ha korforeth hwath gwresek, rag an boblek gemmyn y hwra SK “dos ha bos keschanjyadow gans taklow tamm kawgh.”19
Pella, nyns yw marnas yethow moyhariv gans an gwel negedhek ma a SK avel podrek. Sampel uskis a gampollow media sosyel ha meusi ow tochya SK ha Godhalek Alban gans Professor Lamb a dhiskwedhas fals a 54% negedhek, 33% posedhek ha 13% heptu. (Lamb, 2024) Sentiment an kampol negedhek an moyha talvesys o bos SK dregynnus hag an nessa y talvia dhyn lettya SK rag kestav gans tavosow ertach.
Pyth eson ni ow leverel orth agan diyskynysi? Ny dal agan yeth ha gonisogeth an strivyans personel? Hemm yw martesen fatel wrussen vy y redya, a pen vy i.20
Gorthebydh sondyans Kernewek
Kernewek a baynt aven moy serth, yn arbennik gans dyskoryon ha kowsoryon yowynka ha moy skentel gans tek. Sondyans war Discord ha Whatsapp Kernewek a drovyas bos 65% a grysis y fia SK drog (11.5%) po pur dhrog (53%) rag an yeth. Pan veu govynnys pyth a dal bos gorthyp an gemeneth orth SK, 46% a leveris y kodh y hedhi ha 27% y woheles, gans an dus moy ha 60 bloodh hepken ow tybi y kodh oberi ganso.20
31% a worthebydhyon an sondyans a leveris y hwrussa an devnydh a SK yn Kernewek aga fellhe a’n yeth, hag ynwedh 54% a leveris y fiens i pellhes yn krev ha 23% pellhes tamm a by kowethas, asnodh po dyskador pynag ow tevnydhya SK.
An gorthyp a’n re a leveris bos aga godhvos a SK po “konnyk” po “da” o dampnus yn arbennik. Pubonan y’n bagas ma a worthebis y fia SK dregynnus rag Kernewek, y hwrussa an devnydh a SK gans pennfenten aga fellhe a’n bennfenten na yn krev hag y kodh dhyn hedhi an devnydh a SK rag Kernewek.
HONANIETH, LELDER HA DIVERSETH
Nyns esa Aristotelis Ioannis Paschalidis, ow skrifa a-barth UNESCO, ow kewsel yn komparek a-dro dhe yethow lyharivhes pan wrug ev y wovyn, mes an govyn a dhassen yn kreffa ragon: “Pygemmys koll a honanieth a vynnir sakrifia rag effeythuster?”21
Honanieth yw a’n moyha bri rag Kernewegoryon. Studhyans Ute Wimmer Reversing Language Shift: the Case of Cornish a henow “gweythres [an yeth] avel arwodh a honanieth kenedhlek” avel an nessa ughella skila (66%**) yn-mysk kowsoryon ha dyskoryon, fethys gans gonisogeth Kernow (80%) hepken.22 Yth havalsa hemma bos acheson solempnyans, mes pan vo SK keworrys, y teu ha bos peryl. Vincent Koc a Hyperlink a lever y hyll SK “kevri dre wall orth an gwannheans a yeth ha honanieth wonisogethel”.23
Ev a aswon ynwedh y hallsa awtomategi dyski po dinythi yeth “lehe an rychedh ha lelder hag a dheu a gowsoryon dhenel neb a dheg istoriow gonisogethel y’ga hows”. Yn hwir, peswar studhyans gwrys gans Pennskol Kaliforni Soth re dhiskwedhas bos devnydhya PYB dhe weres gans skrifa “kelmys orth dyfygyansow nosedhek yn diverseth yethel hag y hyll mellya gans an konvedhes brysoniethel ha kowethasel yw proviys gans yeth.”24
Ha hemm yw yn Sowsnek, onan a’n yethow an ryccha ha brassa y’n bys. Dismyk an effeyth war yeth byghanna kepar ha Kernewek—gans le a dhogvennans, le a gedhlow, sel kowsoryon munys hag ogas hag arghans mann—ha war y lies orgraf hag eghen yeth. Yn arbennik yn gettesten Kernewek, seulabrys yma kowsoryon Diwedhes ow strivya dhe vos gwelys avel vas gans gwartheyvans Kres. A dybyn y hwor SK an dyffrans? Heb preder, y hwra po kemyska puptra warbarth, ow sowdheni pubonan, po devnydhya Kres dhe fetha Diwedhes.
An gwruthyl a dhalgh herdhys gans SK Dinythus, dre favera yethow savonegys, a argyl an vansyans a rannyethow ranndiryel.25
Kresen woramontyorieth Barcelona
Nyns yw eghennow hepken yn peryl; SK a wodros beudhi Kernewek yn tien. Akordys yw Perlin y hallsa an platheans yethel a hwarva dres kansbledhynnyow yn Sowsnek hwarvos dres nos yn yeth lyharivhes gans SK orth an fronnow—dell via, ow pos gallosek a bassya Kernewek denel heb assay. Ev a venek prederow yn kever PYB ow rewi yeth yn hy le ha hogen ow settya pyth yw an styr a wodhvos an yeth, yn arbennik gans niverow munys a gowsoryon deythyek.26
Treylyansow leun a atal a liesha warlinen kepar ha nowodhow fug. Kowsoryon deythyek a’n yethow ma yw passyes avel bos “re gales dhe drovya”, komparys orth fordhow awtomategys a surheans kwalita hag yw disjunys yn tien a geskomunyans y’n bys gwir. Kynth yw possybyl rag kemenethow yeth brassa ha moy gallosek synsi an bottys ma dhe akont ha’ga devnydhya yn stratejek hogen, re es yw dismygi [yeth lyhariv] ow pos reverthys.26
Ross Perlin, Endangered Language Alliance
Heb kontrol hag yn diwla an gewri deknegieth, Kernewek synthesek a wra gornivera ha gorthrabellhe Kernewek denel.
SOVRANEDH KEDHLOW HA KOLONEGIETH
Sovranedh kedhlow teythyek yw an gwir gans [kenedhel teythyek] a woverna an kuntel, perghenogeth ha gweytha a’y hedhlow hy honan.27
Native Nations Institute
Byttegyns, yma gonisogethow teythyek hag usi owth oberi war geskowethyans moy ewnhynsek gans SK. Tek heb an kowr a res asnodhow, mes y as kemenethow gwitha sovranedh kedhlow war an gerthen wonisogethel hag yw aga yeth. Te Mana Raraunga, Rosweyth Sovranedh Kedhlow Māori, re wrug rol a bennrewlys rag an gwruthyl, devnydhya ha kevrenna a gedhlow Māori, ow ragwirhe an edhom a grefhe maystri rag Māori a-lemmyn hag a dheu.
I a venek poynt posek hag a dalvia bos konsidrys gans rach gans stywards a skians yethel ha gonisogethel: “Kedhlow ahanan, a-dro dhyn ha’gan asnodhow, yw kerthennow a bris. Pan vo maystri kellys, kales yw y dhaskemeres.”28 Ny dal gul erviransow yn skav po yn uskis; y hyllyn pupprys leverel “ea” mar kwrussyn leverel “na” kyns orth us sett kedhlow, mes ny yllyn nevra leverel “na” mar kwrussyn leverel “ea” seulabrys.
An desten SK, kepar ha pub le aral, yw leun a dus hag yw settys y’ga maneryow ha gans gwel pur drevesigel yn tidowl.29
Michael Running Wolf, First Languages AI Reality
Hemm yw pur bosek y’n gettesten a’n kontrol possybyl a gedhlow Kernewek gans korforethow gallosek a-ves. Estenegieth jatelydhek re beu molleth war gowethasow y’n amal emperourethek ha nyns yw kowethas Kernewek dyffrans, wosa enebi kansvledhynnyow a’y rychys hag asnodhow naturek ow pos destryppys ha gwerthys dre vras gans budh tus yn-mes a Gernow.
An lyver henwys Indigenous Data Sovereignty and Policy a verk lemmyn y hyllir gweles perthynyansow kedhlow avel “pesyans a’n argerdhow ha systemow-krysi isworwedhek a estennans, drogusyans, kuntellyans ha diberghenogeth re beu gwrys war boblansow Teythyek dres trevesigeth istorek.”30 An konvedhes estennek ma a gedhlow yw, dell verkons, hevelebys a-der goderrys gans tyli pobel rag aga hedhlow.
Wostiwedh, res yw ma na vo agan yeth gorrys yn diwla a-ves routys gans pennrewlys perghenogel na as dhyn sovranedh lowr a onan a’gan asnodhow naturel an moyha posek: agan yeth. Res yw dhyn kavos pennrewlys kedhlow ygor, a-der plegya orth kontrol korforethel. Res yw dhyn lewya ha gidya an devnydh a’gan kedhlow, a-der y usya erbynn agan lesow ha rag pocketys tek bras.
A-der drehedhes an arwithans a davosow avel kudyn teknegiethel, my a dyb bos res dhe gemenethow teythyek bos reythhes yn politek, po der arghasans a wovernansow po dre dhifresyansow laghel dhe dhevnydhya aga yethow.31
Dr. Fintan Mallory, Pennskol Durham
Res yw dhyn ragwirhe yeth-avel-kemeneth ha hwilas devnydh ygor, ewnhynsek hag ethegel a’gan kerthennow yeth, ertach ha gonisogethel. Res yw dhyn goheles tybi a SK avel an hus mayth ambos ha kevarghewi yn hwithrans selyek, lewys gans agan kemeneth. Ny wra korforethow agan selwel ha, hogen, i a yll agan shyndya.
NYNS EUS KERNEWEK WAR BLANET MAROW
Governansow ha kevalav ollvysel […] yw omres dhe ideologieth marghas ‘rydh’ moy es dell yns omres dhe sewena kemenethow, pobel ha’n planet.32
Cymdeithas yr Iaith Maniffesto 2022
An brassa rann a vreusyansow a SK a wrussa meneges hemma seulabrys. Onan a’n argyansow brassa yw erbynn SK Dinythus, mes rag own bos ankoth dhis, ni a wra mires orth an chif boyntys.
Res yw bos evadow an dowr goyeynhe pub kresen kedhlow SK. Y kollenk an dowr ma. Pennskol Kaliforni re dherivas “y hallsa demond dowr ollvysel SK hedhes 4.2-6.6 bilvil metrow kubek erbynn 2027. Henn yw moy es 50 kansran a us dowr bledhynnyek an RU yn 2023.”33 Y kettermyn, an Desedhek Ollvysel Erbysieth Dowr a dheklaryas “barras dowr ow tardha yn uskis” ma na dal Kernewek kevri dhodho.34
Ni re dheuth ha bos yn hwir omres dhe deknegiethow privedh gwrys ha kontrolys gans dornas a gompanis diskler [hag] a hevel bos mygyl dre vras orth an sewyansow sosyel a’ga gwriansow ha kevri yn ispoyntel marnas mars yns i konstrinys gans rewlys an wovernans dhe wellhe aga imach poblek.35
Iker Erdocia, Pennskol Sita Dulyn
Yma edhom dhe SK a vynsow kowrek a galesweyth orth kost palas monyow tanow. Kales yw estenna ha purhe an re ma hag yma kostow kerghynedhel ha sosyel poos. Estennys yns i yn fenowgh a hwelyow yn powyow gans difresyansow lakka rag lavur ha’n kerghynnedh. Reset a lever “yn fenowgh y hwra kemenethow yw trigys yn ogas dhe’n hwelyow, yn fenowgh bagasow lyhariv po teythyek, enebi gwethheans an tir, defolyans an dowr hag abusyans gwiryow denel. Meur a hemma a yll bos kelmys yn tidro orth an galesweyth SK.”36 Pan yw an galesweyth kegys yn sertan hag euver, ena tewlys yw avel e-wast yn kemenethow boghosek. Res yw nyns yw an avonsyans possybyl a Gernewek orth kost agan kemenethow hwor lyhariv ha teythyek.
Ynwedh res yw myns hujes a nerth rag trenya SK, yn skon martesen an keth myns ha pow byghan37 hag yma ol troos karbon kowrek.38 Kler yw—der usadow dowr, diwysyans estennek, konsumyans nerth hag ol troos karbon—bos SK yeyn nowodhow rag kerghynnedh ow strivya a’n planet mayth on ni trigys warnodho ha nyns eus Kernewek war blanet marow.
GUL DHE SK BOS EKS-PAPYNJAY
A-der gul dhe yethow lyhariv bos moy hedhadow, lemmyn yma SK ow kwruthyl tardhek pupprys owth omlesa rag studhyoryon ha kowsoryon a’n yethow ma dhe wolya.39
mit technology review
Ni re glewas a’n anwirhevelepter efan a wul dhe SK gallos mimya Kernewek yn golow an kostys yn kedhlow, ober, termyn ha teknegieth. Ni re gonsidras lycklod an dewisynter dispresyans yeyn po askorras-aspia ha’n posekter a sovranedh kedhlow. Ni re redyas a-dro dhe’n effeythyow war vewnansow Kernewegoryon, keffrys ha’n kostys katastrofek rag an kerghynnedh ha poblow teythyek.
Ni re dhyskas y hwra platheans yethel gans SK boghosekhe y destennow ha fatel yll SK martesen ervira a’gan parth fatel godh dh’agan yeth oberi. Ni re welas an anwoheladewder a yeth avel denel ha’n peryllyow a wul ‘dyskoryon’ na yll dyski ha ‘kowsoryon’ na yll kewsel. Ni re welas an peryllyow orth bri ha fydhyans rag kowethasow a wrussa palas an pyth hag yw gwelys avel ‘skomblans’.
Ni re glewas prag y fia omblegya orth an jagganat a SK error rag Kernewek ha dell na vynn agan kemeneth skoodhya gorra an skoos a-dhyworthyn. Yn y le, res yw dhyn batalyas. Res yw dhyn gul dhe Gernewek bos spas mar rydh a skomblans dell yll bos, res yw adhyski orth botlapyoryon yn dyski ha devnydh yeth yn ethegel hag yn effeythus, res yw goheles tybi wortaswerth.
Res yw dhyn gul dh’agan yeth bos parth heb SK, rosweyth a dus fydhyadow ha’ga gwriansow denel, drehevys war lelder, kemeneth, assay ha trest: Kernewek hag yw a-barth an bobel, a’n bobel ha gans an bobel.
Niwlen Ster
Notennow
* A prime example is the laughably-unaffordable restaurant RenMor, which The Headland Hotel thinks is a version of “Re’n Mor”, which they believe means “by the sea” as in “next to the sea” but actually means “by the sea!” like saying “by Zeus!”. This is both hilarious and enraging.
** A figure perhaps lower than it should be if you consider that many of the “emotional motives” which were not counted in this category, such as “I’m Cornish, what better reason do you need?”, do also refer to identity.
FENTENNOW
1. Judah, J. (2025) How AI and Wikipedia have sent vulnerable languages into a doom spiral, MIT Technology Review.
2. Ackermann, A. (2023) When AI doesn’t speak your language, Coda.
3. Crichton, D. (2024) AI and the Death of Human Languages, Lux.
4. Lamb, W. (2024). Could Artificial Intelligence save Scottish Gaelic?, The University of Edinburgh.
5. Dencik, L. (/2025) AI Inequalities: Minority Languages, TUC Cymru.
6. Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Microsoft Research, India. (2020). The State and Fate of Linguistic Diversity and Inclusion in the NLP World. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
7. Ackermann, A. (op cit)
8. McLoughlin, I. (2018) How to teach AI to speak Welsh (and other minority languages), The Conversation.
9. Mallory, F. (2025) RISE UP Panel Discussion & Q&A: What AI Can and Cannot Do for Minoritised Languages, YouTube.
10. Perlin, R. (2024) AI Won’t Protect Endangered Languages, The Dial.
11. RISE UP (2025) #4 RISE UP Event Summary: What AI Can and Cannot Do For Minoritised Languages, RISE UP.
12. Mallory, F. (2024) European Day of Languages: Will lesser spoken languages soon only be kept alive by AI technology? Durham University.
13. Bender, E., Gebru, T., McMillan-Major, A., & Mitchell, M. (2021) On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
14. Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025) The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers. Microsoft.
15. Perlin, R. (op cit)
16. Judah, J. (op cit)
17. Abbruzzese, J., & Wile, R. (2025) Is an AI backlash brewing? What ‘clanker’ says about growing frustrations with emerging tech, NBC News.
18. Webster, K. (2025) Why Using ChatGPT at Work Could Hurt Your Reputation, Inc. Magazine.
19. Herrman, J. (2024) Is That AI? Or Does It Just Suck?, Intelligencer.
20. Wilson, L. (2025) Skians Kreftus ha Kernewek/Artificial Intelligence and Cornish
21. Paschalidis, A. I. (2025) AI and the great linguistic flattening, UNESCO.
22. Wimmer, U. (2010). Reversing Language Shift: the Case of Cornish. Cornish Language Board, p. 113
23. Koc, V. (2025) Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges, ResearchGate.
24. Sourati, Z., Karimi-Malekabadi, F., & Ozcan, M. (2025) The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Models, ResearchGate.
25. Melero, M. (2024) The Future of Language (and Cultural) Diversity in the Age of AI, CLARIN.
26. Perlin, R. (op cit)
27. Russo Carroll, S., Rodriguez Lonebear, D., & Martinez, A. (2017). Data Governance for Native Nation Rebuilding, Native Nations Institute.
28. Te Mana Raraunga. (2018). Frequently Asked Questions, Te Mana Raraunga.
29. Ackermann, A. (op cit)
30. Walter, M., Kukutai, T., Carroll, S. R., & Rodriguez-Lonebear, D. (Eds.). (2020). Indigenous Data Sovereignty and Policy. Taylor & Francis, p. 24
31. Mallory, F. (op cit)
32. Cymdeithas yr Iaith (2022) Cymru Rydd, Cymru Werdd, Cymru Gymraeg., p. 27
33. O’Sullivan, L. (2025). How AI’s Failure on Linguistic Diversity is Deepening Global Inequality, RESET – Digital for Good.
34. Harvey, F. (2024). Global water crisis leaves half of world food production at risk in next 25 years, The Guardian.
35. Erdocia, I., Migge, B., & Schneider, B. (2024). Language is not a data set—Why overcoming ideologies of dataism is more important than ever in the age of AI. Journal of Sociolinguistics, 28(5), p. 23
36. O’Sullivan, L. (op cit)
37. Erdenesanaa, D. (2023) A.I. Could Soon Need as Much Electricity as an Entire Country, The New York Times
38. Heikkilä, M. (2022) We’re getting a better idea of AI’s true carbon footprint, MIT Technology Review.
39. Judah, J. (op cit)#4 #AI #ArtificialIntelligence #Breus #Cornish #Cornwall #data #generativeAI #history #jynn #kedhlow #Kernewek #Kernow #Kernowek #LLM #machine #PYB #SK #SKDinythus #SkiansKreftus #Sordya
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RELX | Reed Elsevier Drives Global Innovation Through Purpose-Driven Tech Careers
RELX | Reed Elsevier, the shared services arm of RELX, a leading global information and analytics company, reinforces its position as the Philippines’ premier destination for impactful technology careers.
As the company’s Philippine operations continue to drive innovation for global markets, RELX | Reed Elsevier demonstrates how meaningful tech roles extend far beyond traditional coding to create solutions that advance different sectors across the globe.
“Our purpose is to benefit society by developing products that help researchers advance scientific knowledge; doctors and nurses improve the lives of patients; lawyers promote the rule of law; and consumers make informed decisions,” according to RELX’s global purpose statement.
“This commitment to using data and analytics for good defines who we are as a company.”
https://twitter.com/tbcnewsph/status/1963819060485050703
Tech for Good: Global Impact from the Philippines
RELX’s Philippine teams contribute to solutions that address some of the world’s most pressing challenges. Their work supports scientific research that leads to medical breakthroughs, enables legal systems to operate more efficiently, and helps organizations make data-driven decisions that benefit society.
Through its Philippine hub spanning Manila, Iloilo, Cebu, and Davao, RELX | Reed Elsevier connects Filipino tech talent with projects that have immediate global impact.
From supporting AI-powered analytics for healthcare research to helping create digital solutions that help legal professionals navigate complex cases, the company’s technology teams are at the forefront of innovations that shape entire industries.
Guided by RELX’s global purpose to “enable professionals and businesses to make better decisions, get better results, and be more productive,” the Philippine teams exemplify how technology can drive positive change on a global scale.
Central to RELX | Reed Elsevier’s success is its award-winning workplace culture, which earned the company the recognition as one of the Top 3 Inspiring Workplaces in Asia by the Inspiring Workplaces Group in its 2025 rankings.
The company’s commitment to employee development is exemplified through One RELX | Reed Elsevier University (ORU), which has trained employees across five specialized learning divisions. These programs range from core professional skills to advanced courses in AI, machine learning, data analytics, and business skills.
This culture also fosters comprehensive diversity, equity, and inclusion (DEI) programs that create a workplace culture of belonging. This culminates in RELX | Reed Elsevier’s Employee Resource Groups, namely Women’s Circle, Pride Circle, Enabled (Disability), Mosaic (Multiculturalism), and Soul Circle (Religious Tolerance).
This fosters an environment where diverse perspectives drive better technology solutions.
“Every day across RELX, our employees are inspired to undertake initiatives that make unique contributions to society and the communities in which we operate,” the company’s global EVP affirms—an ethos clearly reflected in the inclusive culture nurtured within RELX | Reed Elsevier.
“Our people are our greatest asset, and we invest in them accordingly,” said Albert Villagracia, Vice President for Human Resources at RELX | Reed Elsevier. “More than career opportunities, we provide career transformation, enabling our talent to grow alongside the rapidly evolving tech landscape.”
https://twitter.com/tbcnewsph/status/1963818829152178208
Servant Leadership that Values Employees
This people-first culture extends naturally into RELX | Reed Elsevier’s progressive approach to leadership development, which prioritizes service over hierarchy. The company embeds servant leadership principles into its management framework, emphasizing humility, active listening, and employee support over traditional command-and-control styles.
“I’ve had supportive managers and mentors who encouraged me to pursue certifications, pitch improvements, and present solutions that impact multiple teams,” shared Elaiza, a Data Analyst turned Business Analyst and Project Manager at RELX | Reed Elsevier. “It made me realize how much growth is possible when you step outside your comfort zone with the right support to guide you.”
This approach mirrors RELX’s broader vision of responsible leadership—empowering people and promoting innovation that benefits both customers and society.
As RELX | Reed Elsevier continues to expand its Philippine operations, the company remains committed to fostering talent across software engineering, data science, AI/ML engineering, product development, and digital innovation roles.
The organization’s approach to attracting professionals centers on demonstrating how technology careers can extend beyond traditional boundaries to create meaningful global impact.
“Our purpose guides our actions beyond the products that we develop. It defines us as a company,” states the RELX purpose statement—a philosophy that continues to resonate through every innovation emerging from RELX | Reed Elsevier.
#BUSINESS #CSR #events #Labor #latest #news #Philippines #ReedElsevier #RELX #Technology #workforce
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Is Resin Printing Worth the Mess? Brutally Honest Breakdown for First-Timers
1,526 words, 8 minutes read time.
If you’ve been lurking in the shadows of 3D printing forums or scanning YouTube for the next big step in your printing game, chances are you’ve stumbled on resin printing. It’s that tantalizing tech that promises jaw-dropping detail, surfaces so smooth they make FDM prints look like sandpaper, and the kind of precision that makes miniatures and prototypes scream quality. But here’s the real talk: resin printing comes with a mess and a handful of headaches that many first-timers don’t see coming. So, is it worth diving into the resin pool, or should you stick to good ol’ filament? Let’s rip off the band-aid and get gritty on the truth of resin printing.
What Is Resin Printing? A Quick Overview
Before we dissect the good, the bad, and the ugly, it’s important to get clear on what resin printing actually is. Unlike FDM printers that melt and extrude plastic filament layer by layer, resin printers use a vat of liquid photopolymer resin cured by light. The most common types you’ll hear about are SLA (Stereolithography), MSLA (Masked Stereolithography), and DLP (Digital Light Processing). All use UV light to harden the resin in very thin, precise layers, which is why the level of detail you get is miles ahead of filament printing.
Resin printing is a fundamentally different beast—it’s more about light chemistry than hot plastic. That difference brings massive rewards in detail and finish, but also a totally different workflow that can feel like stepping into an alien lab if you’re used to FDM.
The Good: Why Resin Printing Rocks
Let’s start with the shine—resin printing delivers insane detail and surface smoothness that filament printers can’t touch. For guys who are into tabletop gaming, collectibles, or prototyping tiny mechanical parts, resin prints can capture the crisp edges and subtle curves you thought only existed in CAD renders. The resolution is typically measured in microns, not millimeters, which means you can pick out textures on a miniature’s armor or the intricate lattice on a prototype bracket with pinpoint accuracy.
Beyond beauty, resin prints can be incredibly strong and functional, depending on the resin you use. There are tough engineering resins, flexible ones, and even biocompatible varieties for dental or medical applications. This versatility means resin printing is carving out a solid place not just with hobbyists, but with businesses looking for rapid, high-fidelity prototyping without resorting to expensive CNC or injection molding.
Another bonus is how fast resin printers can spit out parts. Sure, you’re still building layer by layer, but curing a whole layer at once rather than tracing it with a nozzle often means speedier prints for small, detailed objects. When you want quality and speed in the same package, resin printing has your back.
The Bad: The Mess and Headaches of Resin Printing
Here’s where things get real. The downside to resin printing is all about the mess and the safety headaches that come with working with liquid resin. This stuff isn’t your run-of-the-mill filament spool you toss in and forget. Resin is a toxic, smelly chemical cocktail that demands respect and careful handling. Direct skin contact can cause irritation or allergic reactions, and the fumes aren’t something you want lingering in your man cave.
The post-processing is a chore you won’t escape. Once your print is done, you need to wash it, usually in isopropyl alcohol, to strip off uncured resin. Then, you have to cure it under UV light to harden it fully. This washing and curing routine isn’t just another step; it can take as long as the print itself and involves dealing with flammable liquids and sticky resin sludge.
Disposal is another headache. You can’t just pour leftover resin or used alcohol down the drain without risking environmental damage and local code violations. You’ll need to research how to properly cure and dispose of waste resin, which adds another layer of complexity for the newbie.
On top of that, the resin printer itself demands careful cleaning and maintenance. The vats and FEP films (the thin transparent layers at the bottom of resin trays) wear out and need replacing, and any spills can quickly turn your workspace into a nightmare. Without proper ventilation and protective gear like nitrile gloves and safety glasses, you’re flirting with respiratory irritation and skin problems.
Equipment and Setup: What You’ll Need to Manage the Mess
If you’re thinking resin printing sounds awesome but want to avoid turning your garage into a toxic swamp, prepping the right setup is non-negotiable. First up, safety gear isn’t optional — gloves, a respirator or mask rated for organic vapors, and eye protection are your frontline defense. You’ll also want a well-ventilated space or ideally, a dedicated room with a fume extractor. Trust me, the resin smell sticks around and gets old fast.
Next, post-processing tools like an ultrasonic cleaner or a good wash station can save you time and hassle. UV curing stations are essential to finish prints properly—while sunlight can do the job, it’s slow and inconsistent. Some budget printers come with UV lights built-in, but many require a separate device.
Your workspace should be easy to clean and resistant to resin spills. Plastic trays, disposable paper towels, and dedicated resin containers will save your sanity. The resin itself can be messy—be prepared for drips and splashes, especially when pouring and cleaning.
Maintenance and Ongoing Costs
Unlike filament printers where the ongoing costs are mostly filament and maybe a new nozzle now and then, resin printing carries a heavier price tag over time. Resin is more expensive per liter than filament, and waste from failed prints or washing can add up quickly. Consumables like replacement vats, FEP films, gloves, and isopropyl alcohol add to the tally.
Plus, the time cost isn’t trivial. Post-processing can double your total print time, especially if you’re meticulous about cleaning and curing. And neglecting maintenance or safety can lead to poor print quality or health issues.
First-Timer Tips: How to Survive and Thrive
If you’re still here and seriously thinking about dipping your toes into resin printing, here’s some hard-earned advice. Start small with cheap resins and basic printers before dropping serious cash. Never skip safety protocols—those gloves and goggles exist for a reason.
Plan your post-processing workflow before your first print. Set up a dedicated cleaning area, and always have proper waste disposal methods ready. Expect a learning curve; don’t get discouraged by early fails or messy spills. Clean resin off your tools and surfaces immediately; once it cures, it’s a nightmare to remove.
One of the biggest rookie mistakes is rushing prints or post-processing to save time. Resin printing rewards patience and precision. Follow manufacturer instructions closely, experiment with settings gradually, and join forums or communities to swap tips.
Is It Worth It? The Final Verdict
So, is resin printing worth the mess? The honest answer is: it depends. If you crave ultra-high detail, smooth surfaces, and can handle a bit of chemistry lab discipline, resin printing opens doors that filament can’t. Miniature painters, jewelers, model makers, and prototype developers will appreciate the leaps in quality and speed.
However, if you’re sensitive to chemicals, don’t want to invest in extra gear or spend significant time on post-processing, resin might not be your best first choice. FDM printing still rocks for durability, ease, and low cost.
The tech is evolving, and newer resins and machines are getting safer and less messy, but it’s still a commitment. Understanding the risks, costs, and workflow upfront will help you decide if this next-level tech deserves a spot in your printing arsenal.
Conclusion
Resin printing isn’t just a step up from filament; it’s a whole new game with different rules. It demands respect for the chemicals, time for cleanup, and patience to master. But the payoff—mind-blowing detail and finish—makes it an addiction for those who love pushing 3D printing’s limits.
If you’re ready to take the plunge or want to share your resin printing war stories, drop a comment below or reach out directly. And don’t forget to subscribe to our newsletter for more raw, honest 3D printing insights. This community’s all about keeping it real and getting the most out of our gear.
D. Bryan King
Sources
- All3DP: Resin 3D Printing Pros and Cons
- 3D Insider: What Is Resin 3D Printing?
- Formlabs: Resin vs FDM 3D Printing
- MakerBot: Resin 3D Printing Guide
- Creality: How to Clean a Resin 3D Printer
- MatterHackers: Safely Using Resin 3D Printers
- 3D Hubs: FDM vs Resin Printing
- Digital Trends: How Resin 3D Printing Works
- Prusa Printers: How to Clean Resin Prints
- Liebert Pub: Safety Considerations for Resin 3D Printing
- Hackaday: Resin 3D Printing – How Messy Is It?
- MakeUseOf: Is Resin 3D Printing Worth It?
- Tom’s Guide: Best Resin 3D Printers of 2024
- 3DPrint.com: Minimizing Resin Printing Mess
- YouTube: Resin 3D Printing Setup and Cleanup Tips
Disclaimer:
The views and opinions expressed in this post are solely those of the author. The information provided is based on personal research, experience, and understanding of the subject matter at the time of writing. Readers should consult relevant experts or authorities for specific guidance related to their unique situations.
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#3dPrinterResinWaste #3dPrintingResinProsAndCons #bestResinPrinters #cleaningResinPrints #isResinPrintingWorthIt #resin3dPrintCleanup #resin3dPrintCuring #resin3dPrinterParts #resin3DPrinterSetup #resin3dPrinting #resin3dPrintingCost #resin3dPrintingDetail #resin3dPrintingEquipment #resin3dPrintingGuide #resin3dPrintingIsopropylAlcohol #resin3dPrintingMistakes #resin3dPrintingQuality #resin3dPrintingSpeed #resin3dPrintingToxicity #resin3dPrintingUVLight #resinPrinterCleaning #resinPrinterMaintenance #resinPrinterSafetyGear #resinPrintingAdvantages #resinPrintingAlternatives #resinPrintingBeginners #resinPrintingCons #resinPrintingConsumables #resinPrintingDetails #resinPrintingDisadvantages #resinPrintingDisposal #resinPrintingDurability #resinPrintingEssentials #resinPrintingForBeginners #resinPrintingForPrototyping #resinPrintingFumes #resinPrintingGloves #resinPrintingHealthPrecautions #resinPrintingHealthRisks #resinPrintingMess #resinPrintingMiniatures #resinPrintingPostCure #resinPrintingPostProcessing #resinPrintingPros #resinPrintingResinTypes #resinPrintingReviews #resinPrintingSafety #resinPrintingSetupTips #resinPrintingSmell #resinPrintingTechnology #resinPrintingTips #resinPrintingTipsAndTricks #resinPrintingVentilation #resinPrintingWasteManagement #resinPrintingWorkflow #resinPrintingWorkspace #resinVsFdm #toxicResinDangers #UVCuringResinPrints
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Hi friends Sam Dogen a financial advisor they say that in the year 2018 he was going to watch Soft Ball game with his friend Bob on a weekend there Bob had bought his new Tesla Model 3 car which was selling a lot in the market Bob was doing a lot of show off there that how does this car run
on autopilot he was driving his car with his I phone and was saying many interesting things like I heard this in news recently on 9th September a lady gave birth to a baby in Philadelphia in the front seat of Tesla and the delivery happened, when Tesla was running on auto pilot because of which,
that baby is also called as World’s First Tesla Baby so Bob was saying such interesting things to everyone Sam was shocked by listening to all these things he was shocked because that how did Bob a 31 year old pre school teacher had bought a $53,000 car which is obviously a lot of money
according to Sam it was their biggest financial mistake which he shouldn’t have done and at the same time, there was a hype about Tesla after listening to all those things, Sam drove that car one day he says that the experience of driving this was very different even he liked the Tesla Model
3 and even he wanted to buy that car but because this car was very costly to him and as he was a financial advisor, he didn’t want to do that mistake so as a financial advisor what he did was instead of buying this $53,000 car he started calculating it’s opportunity cost where he saw,
if he invest this much money of his Savings what can be better opportunity for him than this car then he started doing research about Tesla Company or Elon Musk’s company he started to realize about this company potential and finally after doing all these things he decided
that instead of buying a Tesla Model 3 of $53,000, will buy the Tesla Stocks worth $53,000 in October 2018 on the per share value of $298 bought the Tesla stocks and guess what after some time, these Tesla stocks reached $367 by doing this he had got a Profit of $11,500 and he
didn’t want to sell that and after 6 months, when there were some problems in the company because of a Tweet of Elon Musk, the stocks came down to $179 then their Profit of $11,500 converted to a loss of $20,000 but still he didn’t sell his stocks he was still now fast
forward after 2 years, where the entire world market crashed there Tesla stocks were rising then Sam thought, just like last time, these stock will fall one day then what Sam did was, at $888 per share value sold his 75% stock because he didn’t want to handle the volatility of this market due
to which he got a lot of Profit but ya the fact was, after some time Tesla stocks reached to $1,126 thinking of which Sam regretted but as it is said that Hindsight is always 20/20 after doing things we feel that we shouldn’t have done it, but anyways Sam had booked a good
Profit and then he was thinking how stupid Bob is even he should have bought the stocks instead of the car do you know the interesting part was Bob whom he was thinking is stupid he was investing a lot of his money in Tesla, from a long time because of which he had generated a lot
of Profit and with some part of the Profit he bought Tesla Model 3 look friends the things we should learn from this story is wealth is not like that as we think it is many time when you think people are less capable than you you think that they are financially
behind you well many time is is not necessary that they are behind you many times many people do well financially but since all their wealth is in their investment which we can’t see, so they won’t look rich many times and many times even if they look so, they look stupid which is not
always the case ya being financially free doesn’t mean that you have a lot of wealth which is visible to people by which you can live a luxurious life no but the meaning of being financially free is you live a comfortable life where you don’t worry about money where your money keeps you
safe and work for you now Author Jonathan Clements in their book From Here to Financial Happiness in this book they share 77 short lessons I will merge all those points and share with you 4 practical steps which will help you to be financially free as with that as I had gifted you
Shares of Google few weeks ago in this CashNews.co I will gift Tesla’s Shares how? well to know that keep watching the CashNews.co let’s come to lesson no. 1 which is No saving with Debt author says to start your financial freedom
journey first you have to do one thing that is clear all your Debts clear the Loan and this is the most basic rule of Finance that if you
have any kind of Debt specially bad Debt you cannot start your investing journey author says, some people start long term investing with their Debt where they will be paying their Debt and also doing some investment by this their
process of becoming financially free, slows down so author says first clear all your small Debts like mobile phone, laptop emi, car Loan and such things which you can finish early ya sometimes the big amounts like home Loan that can’t be easy
to clear, those are exceptions, keep them aside but clear your small Debts plus the author also says, to use Credit cards wisely because US Department of Labor had did a research on 7,900 citizens of age 20 to 40 by that we know that, those who were at high
Credit card Debt their stress was affecting their physical health overtime by which they faced many problems in daily life pain in joints and stiffness and were facing many problems you should know how you are using your Credit card for not only
your mental peace but also physical health many people don’t know that by using Credit cards the interest starts and it’s amount keeps increasing and there is a solution related to it, which you will know in 4th point but first remember that that clear all your
Debts as much as possible after that start your Savings journey properly Lesson no. 2 Financial safety net this might have even happened with you something needs repair in your home, like your phone is broken or your T.V is not turning on on there is a problem in
the engine of your car or bike like I remember my friend was saying, that the graphic card of his computer was spoilt the price was very high, at that time he didn’t had money to buy it so somehow he started working without graphic card at that time he didn’t had Credit
card and he didn’t want to borrow money from someone he he decided that next month when he gets Income he will buy the graphic card with that Income now look, many people are just like this if there is any problem, for it’s solution they use their
Credit card or depend on next salary if something happens they say, they will do it from next month do the EMI many times but author says, no one thinks what if their source of Income stops many people are salary based and their job is their main source of
Income there are only few people who have passive Income if their main source of Income dies of any reason job went or anything, even then, they will have a different source of Income on which they can depend on now as it was seen
during Covid time where many people lost their job and were destroyed completely so well what is it’s solution, the author says If you want to feel better about your none;">Finances today then you should spend more time thinking about what you are gonna pay for tomorrow which means basically author is saying us here we have to create an emergency fund you store your money, at a place where you can use it even after loosing your main source of
Income you cannot spend this money on any random things like for vacation, for buying a car or anything no here you have to create an emergency fund which should be the backup of your main Income source because of which, in case something happens and you loose your
job you will not get a new job until you can survive and be safe and how to do that, well to do that author says that you have to calculate your monthly expenses let’s say your monthly expenses is 20,000 rupees you should at least keep 1,20,000 rupees safe at side which is your emergency fund
if there is any problem, like covid, lock-down even then you will have a buffer time of 6 months where you can do many things, can find a job or create a new source of Revenue which will be very helpful for your survival and your respect Lesson no. 3 Invest conservatively and buy
stocks with caution to increase your wealth J Walk when they launched a website Priceline of discount offer in the early 2000’s by this their Net Worth reached $1.8 Billion in just one year and at the other side the world’s greatest investor Warren Buffet they had to
wait 55 years to earn their first Billion Dollars look there is how much difference but the thing is J Walk’s Income was not sustainable everyone knew that this dotcom bubble will burst and when that bubble burst, by end of October 2000 in just a few months, out of billions
of dollars of J walk only 33 Million Dollars were left and Warren Buffet were into the top 1% richest club of the world and are still today and for the coming many years, he will be in the top 1% list the reason behind this is, Warren Buffet, is investing from past 7 decades and he had rarely sold
his Shares so even the author says, if someone wants to be financially free so to invest your money Stock Market can be a very good place to you where you get not only returns, but the company pay you Dividends many times which means they share
some percent of their Profit to their share holders for example you might know that Warren Buffet is a major share holder of Coca Cola so the C.E.O of Coca Cola he gets the highest 16 Million Dollar salary per year on the other side, Warren Buffet by the Dividends
of Coca Cola earn 547 Million Dollars so you might have understood where to invest to become financially free author says when you think long term to invest in Stock Market you don’t need to understand any rocket science but the companies which you know about properly or
better use their products daily which you are using from many years, which you believe on you like those products it will be good for you to invest in such companies and one of the most successful Mutual Fund manager Peter Lynns, who had wrote many good books on investment even he says the same
thing you should invest in such companies whose products you use or you know better about them whose products you like and you believe on as many people use I phone eat Maggie, drink Coca Cola use Tesla Cars so it can be good for you to invest in such companies as it was proven in the starting
story and here you don’t need to see the daily fluctuations of the market in the Intelligent Investor, the mentor of Warren Buffet, Benjamin Graham, even they say in their book that we should not focus on the daily fluctuations of the market but you should just pick the good companies and
invest in that for long term this will give you very good returns in long run now look friends ya there are many Unicorns in India, which are doing very well and there are many companies in America which are giving exponential returns it can be easy to find them, because of their technological
innovations so we Indians should know about this opportunity that we can benefit from the opportunities of the growth outside so you can make this resolution this new year that you will globally diversify your Portfolio for better returns and safety in fact even before this new
year starts, any of your favorite company either Apple, Tesla, Google, Amazon or Netflix or whichever company you like, comment it down buy the Shares of that company and to start all things easily what we did was we have collaborated with IND Money and picked few free
Shares which you can get for free before to buy US stocks you had to bare many charges had to spend a lot of money but with the help of IND money you can get 0 account opening fees 0 maintenance fees and with the help of 0 Brokerage fees you can buy or sell US
stocks plus you get the best exchange rates here plus with the help of this app, you can track all your Investments all Investments you have did, whether is Mutual Funds, Stocks or text-decoration: none;">Crypto as I do the same by using this app so if you benefit from this and want to buy Tesla Stocks for free you just need to download IND money from the link given below and you will get few free Shares of Tesla in the reward section you will get a part
of that share only if you go with the link given below but if you download IND money directly from Play Store or App Store you need to enter the code while signing up which I am showing on screen SEEKENTESLA code you have to put that, then you will get those free stocks Point no 4 is Rugality leads
to better Finances look our physical health, mental health and relationships and overall in entire life, habits play the biggest role and this is an universal fact that good
habits makes good life financial success is nothing but the result of your good habits if you think logically if you want to be financially free you have to save money, you have to invest it but you have very less time so it is very important for you to save and invest money author says 90% people
can’t achieve financial freedom because of their bad habits their bad habits impact Savings a lot because people don’t think exponentially they always think linearly example what we think is, I am just eating one pizza, what will happen by that I am just eating one
burger today, what will happen with that with these small things, they make it a habit and start eating outside food order everyday some thing or the other from Zomato at least it happens every week and that becomes a habit because of which a particular amount Zomato gets every time goes to
different junk food companies money is also going plus all these things impact your health I saw a CashNews.co, there were two people both take different choice every day one person gets up early then the other gets up late one person eats junk food everyday the other person eats healthy all these
small choice which comes in front of us everyday our habits one person spends his money on useless things buys and eats useless things on the other hand the other person instead of eating unwanted things he saves it or eats healthy food and all these things of 1 day, 2 day, I month or 1 year
compounds it’s effect becomes so high that the person who had bad habits his health gets worse his money slowly decreases and his relationship life, everything comes to an end on the other side, who had made small habits those small habits brings improvement in his life slowly his
Savings and his Investments start giving him money his health helps him living a good life and in long term one person’s frugality changes his life completely on the other hand, the ignorance, his smoking, eating unhealthy will destroy his life so even you
have to understand this thing that the small decisions which you are taking everyday may be you won’t see it’s results today, tomorrow or even after a month but you will definitely see some difference in some years and that thing will hurt you in the long run so start living your life
frugally instead of spending on unwanted things, start saving start investing ya it might not help you to get rich in some time but definitely in long run, you can save money and make money so don’t keep linear thinking, keep exponential thinking how can you do all these things try not to
spend more than 50% of your Income and you have to invest 12% for long term for retirement and all if you do like this, you will benefit from it in long run I want to say you a bonus point, start working on different sources of Income start working on many
different sources of Income as much as possible if you just have one job then obviously that’s very risky thing you have to create sources of Income side by side which can give you Income at least a little this thing will help you to earn
money in long run and to be financially free if you want me to make a separate CashNews.co on this topic how can you make you r side Income, do comment and let me know if you are interested in buying free share of Tesla there is a link given in description from there you can
download IND money after downloading, you will see those Shares in the reward section if you are directly directing it from Play Store or App Store while signing up you have to enter a code SEEKENTESLA by this you will get the reward that’s all for now, thanks for watching
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Now that you’re fully informed, watch this amazing video on FROM HERE TO FINANCIAL HAPPINESS 💸 ENRICH YOUR LIFE IN 77 DAYS – FINANCE BOOK SUMMARY. With over 2074088 views, this video deepens your understanding of Finance.CashNews, your go-to portal for financial news and insights.
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Hi friends Sam Dogen a financial advisor they say that in the year 2018 he was going to watch Soft Ball game with his friend Bob on a weekend there Bob had bought his new Tesla Model 3 car which was selling a lot in the market Bob was doing a lot of show off there that how does this car run
on autopilot he was driving his car with his I phone and was saying many interesting things like I heard this in news recently on 9th September a lady gave birth to a baby in Philadelphia in the front seat of Tesla and the delivery happened, when Tesla was running on auto pilot because of which,
that baby is also called as World’s First Tesla Baby so Bob was saying such interesting things to everyone Sam was shocked by listening to all these things he was shocked because that how did Bob a 31 year old pre school teacher had bought a $53,000 car which is obviously a lot of money
according to Sam it was their biggest financial mistake which he shouldn’t have done and at the same time, there was a hype about Tesla after listening to all those things, Sam drove that car one day he says that the experience of driving this was very different even he liked the Tesla Model
3 and even he wanted to buy that car but because this car was very costly to him and as he was a financial advisor, he didn’t want to do that mistake so as a financial advisor what he did was instead of buying this $53,000 car he started calculating it’s opportunity cost where he saw,
if he invest this much money of his Savings what can be better opportunity for him than this car then he started doing research about Tesla Company or Elon Musk’s company he started to realize about this company potential and finally after doing all these things he decided
that instead of buying a Tesla Model 3 of $53,000, will buy the Tesla Stocks worth $53,000 in October 2018 on the per share value of $298 bought the Tesla stocks and guess what after some time, these Tesla stocks reached $367 by doing this he had got a Profit of $11,500 and he
didn’t want to sell that and after 6 months, when there were some problems in the company because of a Tweet of Elon Musk, the stocks came down to $179 then their Profit of $11,500 converted to a loss of $20,000 but still he didn’t sell his stocks he was still now fast
forward after 2 years, where the entire world market crashed there Tesla stocks were rising then Sam thought, just like last time, these stock will fall one day then what Sam did was, at $888 per share value sold his 75% stock because he didn’t want to handle the volatility of this market due
to which he got a lot of Profit but ya the fact was, after some time Tesla stocks reached to $1,126 thinking of which Sam regretted but as it is said that Hindsight is always 20/20 after doing things we feel that we shouldn’t have done it, but anyways Sam had booked a good
Profit and then he was thinking how stupid Bob is even he should have bought the stocks instead of the car do you know the interesting part was Bob whom he was thinking is stupid he was investing a lot of his money in Tesla, from a long time because of which he had generated a lot
of Profit and with some part of the Profit he bought Tesla Model 3 look friends the things we should learn from this story is wealth is not like that as we think it is many time when you think people are less capable than you you think that they are financially
behind you well many time is is not necessary that they are behind you many times many people do well financially but since all their wealth is in their investment which we can’t see, so they won’t look rich many times and many times even if they look so, they look stupid which is not
always the case ya being financially free doesn’t mean that you have a lot of wealth which is visible to people by which you can live a luxurious life no but the meaning of being financially free is you live a comfortable life where you don’t worry about money where your money keeps you
safe and work for you now Author Jonathan Clements in their book From Here to Financial Happiness in this book they share 77 short lessons I will merge all those points and share with you 4 practical steps which will help you to be financially free as with that as I had gifted you
Shares of Google few weeks ago in this CashNews.co I will gift Tesla’s Shares how? well to know that keep watching the CashNews.co let’s come to lesson no. 1 which is No saving with Debt author says to start your financial freedom
journey first you have to do one thing that is clear all your Debts clear the Loan and this is the most basic rule of Finance that if you
have any kind of Debt specially bad Debt you cannot start your investing journey author says, some people start long term investing with their Debt where they will be paying their Debt and also doing some investment by this their
process of becoming financially free, slows down so author says first clear all your small Debts like mobile phone, laptop emi, car Loan and such things which you can finish early ya sometimes the big amounts like home Loan that can’t be easy
to clear, those are exceptions, keep them aside but clear your small Debts plus the author also says, to use Credit cards wisely because US Department of Labor had did a research on 7,900 citizens of age 20 to 40 by that we know that, those who were at high
Credit card Debt their stress was affecting their physical health overtime by which they faced many problems in daily life pain in joints and stiffness and were facing many problems you should know how you are using your Credit card for not only
your mental peace but also physical health many people don’t know that by using Credit cards the interest starts and it’s amount keeps increasing and there is a solution related to it, which you will know in 4th point but first remember that that clear all your
Debts as much as possible after that start your Savings journey properly Lesson no. 2 Financial safety net this might have even happened with you something needs repair in your home, like your phone is broken or your T.V is not turning on on there is a problem in
the engine of your car or bike like I remember my friend was saying, that the graphic card of his computer was spoilt the price was very high, at that time he didn’t had money to buy it so somehow he started working without graphic card at that time he didn’t had Credit
card and he didn’t want to borrow money from someone he he decided that next month when he gets Income he will buy the graphic card with that Income now look, many people are just like this if there is any problem, for it’s solution they use their
Credit card or depend on next salary if something happens they say, they will do it from next month do the EMI many times but author says, no one thinks what if their source of Income stops many people are salary based and their job is their main source of
Income there are only few people who have passive Income if their main source of Income dies of any reason job went or anything, even then, they will have a different source of Income on which they can depend on now as it was seen
during Covid time where many people lost their job and were destroyed completely so well what is it’s solution, the author says If you want to feel better about your none;">Finances today then you should spend more time thinking about what you are gonna pay for tomorrow which means basically author is saying us here we have to create an emergency fund you store your money, at a place where you can use it even after loosing your main source of
Income you cannot spend this money on any random things like for vacation, for buying a car or anything no here you have to create an emergency fund which should be the backup of your main Income source because of which, in case something happens and you loose your
job you will not get a new job until you can survive and be safe and how to do that, well to do that author says that you have to calculate your monthly expenses let’s say your monthly expenses is 20,000 rupees you should at least keep 1,20,000 rupees safe at side which is your emergency fund
if there is any problem, like covid, lock-down even then you will have a buffer time of 6 months where you can do many things, can find a job or create a new source of Revenue which will be very helpful for your survival and your respect Lesson no. 3 Invest conservatively and buy
stocks with caution to increase your wealth J Walk when they launched a website Priceline of discount offer in the early 2000’s by this their Net Worth reached $1.8 Billion in just one year and at the other side the world’s greatest investor Warren Buffet they had to
wait 55 years to earn their first Billion Dollars look there is how much difference but the thing is J Walk’s Income was not sustainable everyone knew that this dotcom bubble will burst and when that bubble burst, by end of October 2000 in just a few months, out of billions
of dollars of J walk only 33 Million Dollars were left and Warren Buffet were into the top 1% richest club of the world and are still today and for the coming many years, he will be in the top 1% list the reason behind this is, Warren Buffet, is investing from past 7 decades and he had rarely sold
his Shares so even the author says, if someone wants to be financially free so to invest your money Stock Market can be a very good place to you where you get not only returns, but the company pay you Dividends many times which means they share
some percent of their Profit to their share holders for example you might know that Warren Buffet is a major share holder of Coca Cola so the C.E.O of Coca Cola he gets the highest 16 Million Dollar salary per year on the other side, Warren Buffet by the Dividends
of Coca Cola earn 547 Million Dollars so you might have understood where to invest to become financially free author says when you think long term to invest in Stock Market you don’t need to understand any rocket science but the companies which you know about properly or
better use their products daily which you are using from many years, which you believe on you like those products it will be good for you to invest in such companies and one of the most successful Mutual Fund manager Peter Lynns, who had wrote many good books on investment even he says the same
thing you should invest in such companies whose products you use or you know better about them whose products you like and you believe on as many people use I phone eat Maggie, drink Coca Cola use Tesla Cars so it can be good for you to invest in such companies as it was proven in the starting
story and here you don’t need to see the daily fluctuations of the market in the Intelligent Investor, the mentor of Warren Buffet, Benjamin Graham, even they say in their book that we should not focus on the daily fluctuations of the market but you should just pick the good companies and
invest in that for long term this will give you very good returns in long run now look friends ya there are many Unicorns in India, which are doing very well and there are many companies in America which are giving exponential returns it can be easy to find them, because of their technological
innovations so we Indians should know about this opportunity that we can benefit from the opportunities of the growth outside so you can make this resolution this new year that you will globally diversify your Portfolio for better returns and safety in fact even before this new
year starts, any of your favorite company either Apple, Tesla, Google, Amazon or Netflix or whichever company you like, comment it down buy the Shares of that company and to start all things easily what we did was we have collaborated with IND Money and picked few free
Shares which you can get for free before to buy US stocks you had to bare many charges had to spend a lot of money but with the help of IND money you can get 0 account opening fees 0 maintenance fees and with the help of 0 Brokerage fees you can buy or sell US
stocks plus you get the best exchange rates here plus with the help of this app, you can track all your Investments all Investments you have did, whether is Mutual Funds, Stocks or text-decoration: none;">Crypto as I do the same by using this app so if you benefit from this and want to buy Tesla Stocks for free you just need to download IND money from the link given below and you will get few free Shares of Tesla in the reward section you will get a part
of that share only if you go with the link given below but if you download IND money directly from Play Store or App Store you need to enter the code while signing up which I am showing on screen SEEKENTESLA code you have to put that, then you will get those free stocks Point no 4 is Rugality leads
to better Finances look our physical health, mental health and relationships and overall in entire life, habits play the biggest role and this is an universal fact that good
habits makes good life financial success is nothing but the result of your good habits if you think logically if you want to be financially free you have to save money, you have to invest it but you have very less time so it is very important for you to save and invest money author says 90% people
can’t achieve financial freedom because of their bad habits their bad habits impact Savings a lot because people don’t think exponentially they always think linearly example what we think is, I am just eating one pizza, what will happen by that I am just eating one
burger today, what will happen with that with these small things, they make it a habit and start eating outside food order everyday some thing or the other from Zomato at least it happens every week and that becomes a habit because of which a particular amount Zomato gets every time goes to
different junk food companies money is also going plus all these things impact your health I saw a CashNews.co, there were two people both take different choice every day one person gets up early then the other gets up late one person eats junk food everyday the other person eats healthy all these
small choice which comes in front of us everyday our habits one person spends his money on useless things buys and eats useless things on the other hand the other person instead of eating unwanted things he saves it or eats healthy food and all these things of 1 day, 2 day, I month or 1 year
compounds it’s effect becomes so high that the person who had bad habits his health gets worse his money slowly decreases and his relationship life, everything comes to an end on the other side, who had made small habits those small habits brings improvement in his life slowly his
Savings and his Investments start giving him money his health helps him living a good life and in long term one person’s frugality changes his life completely on the other hand, the ignorance, his smoking, eating unhealthy will destroy his life so even you
have to understand this thing that the small decisions which you are taking everyday may be you won’t see it’s results today, tomorrow or even after a month but you will definitely see some difference in some years and that thing will hurt you in the long run so start living your life
frugally instead of spending on unwanted things, start saving start investing ya it might not help you to get rich in some time but definitely in long run, you can save money and make money so don’t keep linear thinking, keep exponential thinking how can you do all these things try not to
spend more than 50% of your Income and you have to invest 12% for long term for retirement and all if you do like this, you will benefit from it in long run I want to say you a bonus point, start working on different sources of Income start working on many
different sources of Income as much as possible if you just have one job then obviously that’s very risky thing you have to create sources of Income side by side which can give you Income at least a little this thing will help you to earn
money in long run and to be financially free if you want me to make a separate CashNews.co on this topic how can you make you r side Income, do comment and let me know if you are interested in buying free share of Tesla there is a link given in description from there you can
download IND money after downloading, you will see those Shares in the reward section if you are directly directing it from Play Store or App Store while signing up you have to enter a code SEEKENTESLA by this you will get the reward that’s all for now, thanks for watching
/>
Now that you’re fully informed, watch this amazing video on FROM HERE TO FINANCIAL HAPPINESS 💸 ENRICH YOUR LIFE IN 77 DAYS – FINANCE BOOK SUMMARY. With over 2074088 views, this video deepens your understanding of Finance.CashNews, your go-to portal for financial news and insights.
#FINANCIAL #HAPPINESS #ENRICH #LIFE #DAYS #FINANCE #BOOK #SUMMARY#1a73e8 #333 #BOOK #DAYS #ENRICH #finance #Financial #HAPPINESS #Life #SUMMARY
-
Hi friends Sam Dogen a financial advisor they say that in the year 2018 he was going to watch Soft Ball game with his friend Bob on a weekend there Bob had bought his new Tesla Model 3 car which was selling a lot in the market Bob was doing a lot of show off there that how does this car run
on autopilot he was driving his car with his I phone and was saying many interesting things like I heard this in news recently on 9th September a lady gave birth to a baby in Philadelphia in the front seat of Tesla and the delivery happened, when Tesla was running on auto pilot because of which,
that baby is also called as World’s First Tesla Baby so Bob was saying such interesting things to everyone Sam was shocked by listening to all these things he was shocked because that how did Bob a 31 year old pre school teacher had bought a $53,000 car which is obviously a lot of money
according to Sam it was their biggest financial mistake which he shouldn’t have done and at the same time, there was a hype about Tesla after listening to all those things, Sam drove that car one day he says that the experience of driving this was very different even he liked the Tesla Model
3 and even he wanted to buy that car but because this car was very costly to him and as he was a financial advisor, he didn’t want to do that mistake so as a financial advisor what he did was instead of buying this $53,000 car he started calculating it’s opportunity cost where he saw,
if he invest this much money of his Savings what can be better opportunity for him than this car then he started doing research about Tesla Company or Elon Musk’s company he started to realize about this company potential and finally after doing all these things he decided
that instead of buying a Tesla Model 3 of $53,000, will buy the Tesla Stocks worth $53,000 in October 2018 on the per share value of $298 bought the Tesla stocks and guess what after some time, these Tesla stocks reached $367 by doing this he had got a Profit of $11,500 and he
didn’t want to sell that and after 6 months, when there were some problems in the company because of a Tweet of Elon Musk, the stocks came down to $179 then their Profit of $11,500 converted to a loss of $20,000 but still he didn’t sell his stocks he was still now fast
forward after 2 years, where the entire world market crashed there Tesla stocks were rising then Sam thought, just like last time, these stock will fall one day then what Sam did was, at $888 per share value sold his 75% stock because he didn’t want to handle the volatility of this market due
to which he got a lot of Profit but ya the fact was, after some time Tesla stocks reached to $1,126 thinking of which Sam regretted but as it is said that Hindsight is always 20/20 after doing things we feel that we shouldn’t have done it, but anyways Sam had booked a good
Profit and then he was thinking how stupid Bob is even he should have bought the stocks instead of the car do you know the interesting part was Bob whom he was thinking is stupid he was investing a lot of his money in Tesla, from a long time because of which he had generated a lot
of Profit and with some part of the Profit he bought Tesla Model 3 look friends the things we should learn from this story is wealth is not like that as we think it is many time when you think people are less capable than you you think that they are financially
behind you well many time is is not necessary that they are behind you many times many people do well financially but since all their wealth is in their investment which we can’t see, so they won’t look rich many times and many times even if they look so, they look stupid which is not
always the case ya being financially free doesn’t mean that you have a lot of wealth which is visible to people by which you can live a luxurious life no but the meaning of being financially free is you live a comfortable life where you don’t worry about money where your money keeps you
safe and work for you now Author Jonathan Clements in their book From Here to Financial Happiness in this book they share 77 short lessons I will merge all those points and share with you 4 practical steps which will help you to be financially free as with that as I had gifted you
Shares of Google few weeks ago in this CashNews.co I will gift Tesla’s Shares how? well to know that keep watching the CashNews.co let’s come to lesson no. 1 which is No saving with Debt author says to start your financial freedom
journey first you have to do one thing that is clear all your Debts clear the Loan and this is the most basic rule of Finance that if you
have any kind of Debt specially bad Debt you cannot start your investing journey author says, some people start long term investing with their Debt where they will be paying their Debt and also doing some investment by this their
process of becoming financially free, slows down so author says first clear all your small Debts like mobile phone, laptop emi, car Loan and such things which you can finish early ya sometimes the big amounts like home Loan that can’t be easy
to clear, those are exceptions, keep them aside but clear your small Debts plus the author also says, to use Credit cards wisely because US Department of Labor had did a research on 7,900 citizens of age 20 to 40 by that we know that, those who were at high
Credit card Debt their stress was affecting their physical health overtime by which they faced many problems in daily life pain in joints and stiffness and were facing many problems you should know how you are using your Credit card for not only
your mental peace but also physical health many people don’t know that by using Credit cards the interest starts and it’s amount keeps increasing and there is a solution related to it, which you will know in 4th point but first remember that that clear all your
Debts as much as possible after that start your Savings journey properly Lesson no. 2 Financial safety net this might have even happened with you something needs repair in your home, like your phone is broken or your T.V is not turning on on there is a problem in
the engine of your car or bike like I remember my friend was saying, that the graphic card of his computer was spoilt the price was very high, at that time he didn’t had money to buy it so somehow he started working without graphic card at that time he didn’t had Credit
card and he didn’t want to borrow money from someone he he decided that next month when he gets Income he will buy the graphic card with that Income now look, many people are just like this if there is any problem, for it’s solution they use their
Credit card or depend on next salary if something happens they say, they will do it from next month do the EMI many times but author says, no one thinks what if their source of Income stops many people are salary based and their job is their main source of
Income there are only few people who have passive Income if their main source of Income dies of any reason job went or anything, even then, they will have a different source of Income on which they can depend on now as it was seen
during Covid time where many people lost their job and were destroyed completely so well what is it’s solution, the author says If you want to feel better about your none;">Finances today then you should spend more time thinking about what you are gonna pay for tomorrow which means basically author is saying us here we have to create an emergency fund you store your money, at a place where you can use it even after loosing your main source of
Income you cannot spend this money on any random things like for vacation, for buying a car or anything no here you have to create an emergency fund which should be the backup of your main Income source because of which, in case something happens and you loose your
job you will not get a new job until you can survive and be safe and how to do that, well to do that author says that you have to calculate your monthly expenses let’s say your monthly expenses is 20,000 rupees you should at least keep 1,20,000 rupees safe at side which is your emergency fund
if there is any problem, like covid, lock-down even then you will have a buffer time of 6 months where you can do many things, can find a job or create a new source of Revenue which will be very helpful for your survival and your respect Lesson no. 3 Invest conservatively and buy
stocks with caution to increase your wealth J Walk when they launched a website Priceline of discount offer in the early 2000’s by this their Net Worth reached $1.8 Billion in just one year and at the other side the world’s greatest investor Warren Buffet they had to
wait 55 years to earn their first Billion Dollars look there is how much difference but the thing is J Walk’s Income was not sustainable everyone knew that this dotcom bubble will burst and when that bubble burst, by end of October 2000 in just a few months, out of billions
of dollars of J walk only 33 Million Dollars were left and Warren Buffet were into the top 1% richest club of the world and are still today and for the coming many years, he will be in the top 1% list the reason behind this is, Warren Buffet, is investing from past 7 decades and he had rarely sold
his Shares so even the author says, if someone wants to be financially free so to invest your money Stock Market can be a very good place to you where you get not only returns, but the company pay you Dividends many times which means they share
some percent of their Profit to their share holders for example you might know that Warren Buffet is a major share holder of Coca Cola so the C.E.O of Coca Cola he gets the highest 16 Million Dollar salary per year on the other side, Warren Buffet by the Dividends
of Coca Cola earn 547 Million Dollars so you might have understood where to invest to become financially free author says when you think long term to invest in Stock Market you don’t need to understand any rocket science but the companies which you know about properly or
better use their products daily which you are using from many years, which you believe on you like those products it will be good for you to invest in such companies and one of the most successful Mutual Fund manager Peter Lynns, who had wrote many good books on investment even he says the same
thing you should invest in such companies whose products you use or you know better about them whose products you like and you believe on as many people use I phone eat Maggie, drink Coca Cola use Tesla Cars so it can be good for you to invest in such companies as it was proven in the starting
story and here you don’t need to see the daily fluctuations of the market in the Intelligent Investor, the mentor of Warren Buffet, Benjamin Graham, even they say in their book that we should not focus on the daily fluctuations of the market but you should just pick the good companies and
invest in that for long term this will give you very good returns in long run now look friends ya there are many Unicorns in India, which are doing very well and there are many companies in America which are giving exponential returns it can be easy to find them, because of their technological
innovations so we Indians should know about this opportunity that we can benefit from the opportunities of the growth outside so you can make this resolution this new year that you will globally diversify your Portfolio for better returns and safety in fact even before this new
year starts, any of your favorite company either Apple, Tesla, Google, Amazon or Netflix or whichever company you like, comment it down buy the Shares of that company and to start all things easily what we did was we have collaborated with IND Money and picked few free
Shares which you can get for free before to buy US stocks you had to bare many charges had to spend a lot of money but with the help of IND money you can get 0 account opening fees 0 maintenance fees and with the help of 0 Brokerage fees you can buy or sell US
stocks plus you get the best exchange rates here plus with the help of this app, you can track all your Investments all Investments you have did, whether is Mutual Funds, Stocks or text-decoration: none;">Crypto as I do the same by using this app so if you benefit from this and want to buy Tesla Stocks for free you just need to download IND money from the link given below and you will get few free Shares of Tesla in the reward section you will get a part
of that share only if you go with the link given below but if you download IND money directly from Play Store or App Store you need to enter the code while signing up which I am showing on screen SEEKENTESLA code you have to put that, then you will get those free stocks Point no 4 is Rugality leads
to better Finances look our physical health, mental health and relationships and overall in entire life, habits play the biggest role and this is an universal fact that good
habits makes good life financial success is nothing but the result of your good habits if you think logically if you want to be financially free you have to save money, you have to invest it but you have very less time so it is very important for you to save and invest money author says 90% people
can’t achieve financial freedom because of their bad habits their bad habits impact Savings a lot because people don’t think exponentially they always think linearly example what we think is, I am just eating one pizza, what will happen by that I am just eating one
burger today, what will happen with that with these small things, they make it a habit and start eating outside food order everyday some thing or the other from Zomato at least it happens every week and that becomes a habit because of which a particular amount Zomato gets every time goes to
different junk food companies money is also going plus all these things impact your health I saw a CashNews.co, there were two people both take different choice every day one person gets up early then the other gets up late one person eats junk food everyday the other person eats healthy all these
small choice which comes in front of us everyday our habits one person spends his money on useless things buys and eats useless things on the other hand the other person instead of eating unwanted things he saves it or eats healthy food and all these things of 1 day, 2 day, I month or 1 year
compounds it’s effect becomes so high that the person who had bad habits his health gets worse his money slowly decreases and his relationship life, everything comes to an end on the other side, who had made small habits those small habits brings improvement in his life slowly his
Savings and his Investments start giving him money his health helps him living a good life and in long term one person’s frugality changes his life completely on the other hand, the ignorance, his smoking, eating unhealthy will destroy his life so even you
have to understand this thing that the small decisions which you are taking everyday may be you won’t see it’s results today, tomorrow or even after a month but you will definitely see some difference in some years and that thing will hurt you in the long run so start living your life
frugally instead of spending on unwanted things, start saving start investing ya it might not help you to get rich in some time but definitely in long run, you can save money and make money so don’t keep linear thinking, keep exponential thinking how can you do all these things try not to
spend more than 50% of your Income and you have to invest 12% for long term for retirement and all if you do like this, you will benefit from it in long run I want to say you a bonus point, start working on different sources of Income start working on many
different sources of Income as much as possible if you just have one job then obviously that’s very risky thing you have to create sources of Income side by side which can give you Income at least a little this thing will help you to earn
money in long run and to be financially free if you want me to make a separate CashNews.co on this topic how can you make you r side Income, do comment and let me know if you are interested in buying free share of Tesla there is a link given in description from there you can
download IND money after downloading, you will see those Shares in the reward section if you are directly directing it from Play Store or App Store while signing up you have to enter a code SEEKENTESLA by this you will get the reward that’s all for now, thanks for watching
/>
Now that you’re fully informed, watch this amazing video on FROM HERE TO FINANCIAL HAPPINESS 💸 ENRICH YOUR LIFE IN 77 DAYS – FINANCE BOOK SUMMARY. With over 2074088 views, this video deepens your understanding of Finance.CashNews, your go-to portal for financial news and insights.
#FINANCIAL #HAPPINESS #ENRICH #LIFE #DAYS #FINANCE #BOOK #SUMMARY#1a73e8 #333 #BOOK #DAYS #ENRICH #finance #Financial #HAPPINESS #Life #SUMMARY
-
Hi friends Sam Dogen a financial advisor they say that in the year 2018 he was going to watch Soft Ball game with his friend Bob on a weekend there Bob had bought his new Tesla Model 3 car which was selling a lot in the market Bob was doing a lot of show off there that how does this car run
on autopilot he was driving his car with his I phone and was saying many interesting things like I heard this in news recently on 9th September a lady gave birth to a baby in Philadelphia in the front seat of Tesla and the delivery happened, when Tesla was running on auto pilot because of which,
that baby is also called as World’s First Tesla Baby so Bob was saying such interesting things to everyone Sam was shocked by listening to all these things he was shocked because that how did Bob a 31 year old pre school teacher had bought a $53,000 car which is obviously a lot of money
according to Sam it was their biggest financial mistake which he shouldn’t have done and at the same time, there was a hype about Tesla after listening to all those things, Sam drove that car one day he says that the experience of driving this was very different even he liked the Tesla Model
3 and even he wanted to buy that car but because this car was very costly to him and as he was a financial advisor, he didn’t want to do that mistake so as a financial advisor what he did was instead of buying this $53,000 car he started calculating it’s opportunity cost where he saw,
if he invest this much money of his Savings what can be better opportunity for him than this car then he started doing research about Tesla Company or Elon Musk’s company he started to realize about this company potential and finally after doing all these things he decided
that instead of buying a Tesla Model 3 of $53,000, will buy the Tesla Stocks worth $53,000 in October 2018 on the per share value of $298 bought the Tesla stocks and guess what after some time, these Tesla stocks reached $367 by doing this he had got a Profit of $11,500 and he
didn’t want to sell that and after 6 months, when there were some problems in the company because of a Tweet of Elon Musk, the stocks came down to $179 then their Profit of $11,500 converted to a loss of $20,000 but still he didn’t sell his stocks he was still now fast
forward after 2 years, where the entire world market crashed there Tesla stocks were rising then Sam thought, just like last time, these stock will fall one day then what Sam did was, at $888 per share value sold his 75% stock because he didn’t want to handle the volatility of this market due
to which he got a lot of Profit but ya the fact was, after some time Tesla stocks reached to $1,126 thinking of which Sam regretted but as it is said that Hindsight is always 20/20 after doing things we feel that we shouldn’t have done it, but anyways Sam had booked a good
Profit and then he was thinking how stupid Bob is even he should have bought the stocks instead of the car do you know the interesting part was Bob whom he was thinking is stupid he was investing a lot of his money in Tesla, from a long time because of which he had generated a lot
of Profit and with some part of the Profit he bought Tesla Model 3 look friends the things we should learn from this story is wealth is not like that as we think it is many time when you think people are less capable than you you think that they are financially
behind you well many time is is not necessary that they are behind you many times many people do well financially but since all their wealth is in their investment which we can’t see, so they won’t look rich many times and many times even if they look so, they look stupid which is not
always the case ya being financially free doesn’t mean that you have a lot of wealth which is visible to people by which you can live a luxurious life no but the meaning of being financially free is you live a comfortable life where you don’t worry about money where your money keeps you
safe and work for you now Author Jonathan Clements in their book From Here to Financial Happiness in this book they share 77 short lessons I will merge all those points and share with you 4 practical steps which will help you to be financially free as with that as I had gifted you
Shares of Google few weeks ago in this CashNews.co I will gift Tesla’s Shares how? well to know that keep watching the CashNews.co let’s come to lesson no. 1 which is No saving with Debt author says to start your financial freedom
journey first you have to do one thing that is clear all your Debts clear the Loan and this is the most basic rule of Finance that if you
have any kind of Debt specially bad Debt you cannot start your investing journey author says, some people start long term investing with their Debt where they will be paying their Debt and also doing some investment by this their
process of becoming financially free, slows down so author says first clear all your small Debts like mobile phone, laptop emi, car Loan and such things which you can finish early ya sometimes the big amounts like home Loan that can’t be easy
to clear, those are exceptions, keep them aside but clear your small Debts plus the author also says, to use Credit cards wisely because US Department of Labor had did a research on 7,900 citizens of age 20 to 40 by that we know that, those who were at high
Credit card Debt their stress was affecting their physical health overtime by which they faced many problems in daily life pain in joints and stiffness and were facing many problems you should know how you are using your Credit card for not only
your mental peace but also physical health many people don’t know that by using Credit cards the interest starts and it’s amount keeps increasing and there is a solution related to it, which you will know in 4th point but first remember that that clear all your
Debts as much as possible after that start your Savings journey properly Lesson no. 2 Financial safety net this might have even happened with you something needs repair in your home, like your phone is broken or your T.V is not turning on on there is a problem in
the engine of your car or bike like I remember my friend was saying, that the graphic card of his computer was spoilt the price was very high, at that time he didn’t had money to buy it so somehow he started working without graphic card at that time he didn’t had Credit
card and he didn’t want to borrow money from someone he he decided that next month when he gets Income he will buy the graphic card with that Income now look, many people are just like this if there is any problem, for it’s solution they use their
Credit card or depend on next salary if something happens they say, they will do it from next month do the EMI many times but author says, no one thinks what if their source of Income stops many people are salary based and their job is their main source of
Income there are only few people who have passive Income if their main source of Income dies of any reason job went or anything, even then, they will have a different source of Income on which they can depend on now as it was seen
during Covid time where many people lost their job and were destroyed completely so well what is it’s solution, the author says If you want to feel better about your none;">Finances today then you should spend more time thinking about what you are gonna pay for tomorrow which means basically author is saying us here we have to create an emergency fund you store your money, at a place where you can use it even after loosing your main source of
Income you cannot spend this money on any random things like for vacation, for buying a car or anything no here you have to create an emergency fund which should be the backup of your main Income source because of which, in case something happens and you loose your
job you will not get a new job until you can survive and be safe and how to do that, well to do that author says that you have to calculate your monthly expenses let’s say your monthly expenses is 20,000 rupees you should at least keep 1,20,000 rupees safe at side which is your emergency fund
if there is any problem, like covid, lock-down even then you will have a buffer time of 6 months where you can do many things, can find a job or create a new source of Revenue which will be very helpful for your survival and your respect Lesson no. 3 Invest conservatively and buy
stocks with caution to increase your wealth J Walk when they launched a website Priceline of discount offer in the early 2000’s by this their Net Worth reached $1.8 Billion in just one year and at the other side the world’s greatest investor Warren Buffet they had to
wait 55 years to earn their first Billion Dollars look there is how much difference but the thing is J Walk’s Income was not sustainable everyone knew that this dotcom bubble will burst and when that bubble burst, by end of October 2000 in just a few months, out of billions
of dollars of J walk only 33 Million Dollars were left and Warren Buffet were into the top 1% richest club of the world and are still today and for the coming many years, he will be in the top 1% list the reason behind this is, Warren Buffet, is investing from past 7 decades and he had rarely sold
his Shares so even the author says, if someone wants to be financially free so to invest your money Stock Market can be a very good place to you where you get not only returns, but the company pay you Dividends many times which means they share
some percent of their Profit to their share holders for example you might know that Warren Buffet is a major share holder of Coca Cola so the C.E.O of Coca Cola he gets the highest 16 Million Dollar salary per year on the other side, Warren Buffet by the Dividends
of Coca Cola earn 547 Million Dollars so you might have understood where to invest to become financially free author says when you think long term to invest in Stock Market you don’t need to understand any rocket science but the companies which you know about properly or
better use their products daily which you are using from many years, which you believe on you like those products it will be good for you to invest in such companies and one of the most successful Mutual Fund manager Peter Lynns, who had wrote many good books on investment even he says the same
thing you should invest in such companies whose products you use or you know better about them whose products you like and you believe on as many people use I phone eat Maggie, drink Coca Cola use Tesla Cars so it can be good for you to invest in such companies as it was proven in the starting
story and here you don’t need to see the daily fluctuations of the market in the Intelligent Investor, the mentor of Warren Buffet, Benjamin Graham, even they say in their book that we should not focus on the daily fluctuations of the market but you should just pick the good companies and
invest in that for long term this will give you very good returns in long run now look friends ya there are many Unicorns in India, which are doing very well and there are many companies in America which are giving exponential returns it can be easy to find them, because of their technological
innovations so we Indians should know about this opportunity that we can benefit from the opportunities of the growth outside so you can make this resolution this new year that you will globally diversify your Portfolio for better returns and safety in fact even before this new
year starts, any of your favorite company either Apple, Tesla, Google, Amazon or Netflix or whichever company you like, comment it down buy the Shares of that company and to start all things easily what we did was we have collaborated with IND Money and picked few free
Shares which you can get for free before to buy US stocks you had to bare many charges had to spend a lot of money but with the help of IND money you can get 0 account opening fees 0 maintenance fees and with the help of 0 Brokerage fees you can buy or sell US
stocks plus you get the best exchange rates here plus with the help of this app, you can track all your Investments all Investments you have did, whether is Mutual Funds, Stocks or text-decoration: none;">Crypto as I do the same by using this app so if you benefit from this and want to buy Tesla Stocks for free you just need to download IND money from the link given below and you will get few free Shares of Tesla in the reward section you will get a part
of that share only if you go with the link given below but if you download IND money directly from Play Store or App Store you need to enter the code while signing up which I am showing on screen SEEKENTESLA code you have to put that, then you will get those free stocks Point no 4 is Rugality leads
to better Finances look our physical health, mental health and relationships and overall in entire life, habits play the biggest role and this is an universal fact that good
habits makes good life financial success is nothing but the result of your good habits if you think logically if you want to be financially free you have to save money, you have to invest it but you have very less time so it is very important for you to save and invest money author says 90% people
can’t achieve financial freedom because of their bad habits their bad habits impact Savings a lot because people don’t think exponentially they always think linearly example what we think is, I am just eating one pizza, what will happen by that I am just eating one
burger today, what will happen with that with these small things, they make it a habit and start eating outside food order everyday some thing or the other from Zomato at least it happens every week and that becomes a habit because of which a particular amount Zomato gets every time goes to
different junk food companies money is also going plus all these things impact your health I saw a CashNews.co, there were two people both take different choice every day one person gets up early then the other gets up late one person eats junk food everyday the other person eats healthy all these
small choice which comes in front of us everyday our habits one person spends his money on useless things buys and eats useless things on the other hand the other person instead of eating unwanted things he saves it or eats healthy food and all these things of 1 day, 2 day, I month or 1 year
compounds it’s effect becomes so high that the person who had bad habits his health gets worse his money slowly decreases and his relationship life, everything comes to an end on the other side, who had made small habits those small habits brings improvement in his life slowly his
Savings and his Investments start giving him money his health helps him living a good life and in long term one person’s frugality changes his life completely on the other hand, the ignorance, his smoking, eating unhealthy will destroy his life so even you
have to understand this thing that the small decisions which you are taking everyday may be you won’t see it’s results today, tomorrow or even after a month but you will definitely see some difference in some years and that thing will hurt you in the long run so start living your life
frugally instead of spending on unwanted things, start saving start investing ya it might not help you to get rich in some time but definitely in long run, you can save money and make money so don’t keep linear thinking, keep exponential thinking how can you do all these things try not to
spend more than 50% of your Income and you have to invest 12% for long term for retirement and all if you do like this, you will benefit from it in long run I want to say you a bonus point, start working on different sources of Income start working on many
different sources of Income as much as possible if you just have one job then obviously that’s very risky thing you have to create sources of Income side by side which can give you Income at least a little this thing will help you to earn
money in long run and to be financially free if you want me to make a separate CashNews.co on this topic how can you make you r side Income, do comment and let me know if you are interested in buying free share of Tesla there is a link given in description from there you can
download IND money after downloading, you will see those Shares in the reward section if you are directly directing it from Play Store or App Store while signing up you have to enter a code SEEKENTESLA by this you will get the reward that’s all for now, thanks for watching
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Hi friends Sam Dogen a financial advisor they say that in the year 2018 he was going to watch Soft Ball game with his friend Bob on a weekend there Bob had bought his new Tesla Model 3 car which was selling a lot in the market Bob was doing a lot of show off there that how does this car run
on autopilot he was driving his car with his I phone and was saying many interesting things like I heard this in news recently on 9th September a lady gave birth to a baby in Philadelphia in the front seat of Tesla and the delivery happened, when Tesla was running on auto pilot because of which,
that baby is also called as World’s First Tesla Baby so Bob was saying such interesting things to everyone Sam was shocked by listening to all these things he was shocked because that how did Bob a 31 year old pre school teacher had bought a $53,000 car which is obviously a lot of money
according to Sam it was their biggest financial mistake which he shouldn’t have done and at the same time, there was a hype about Tesla after listening to all those things, Sam drove that car one day he says that the experience of driving this was very different even he liked the Tesla Model
3 and even he wanted to buy that car but because this car was very costly to him and as he was a financial advisor, he didn’t want to do that mistake so as a financial advisor what he did was instead of buying this $53,000 car he started calculating it’s opportunity cost where he saw,
if he invest this much money of his Savings what can be better opportunity for him than this car then he started doing research about Tesla Company or Elon Musk’s company he started to realize about this company potential and finally after doing all these things he decided
that instead of buying a Tesla Model 3 of $53,000, will buy the Tesla Stocks worth $53,000 in October 2018 on the per share value of $298 bought the Tesla stocks and guess what after some time, these Tesla stocks reached $367 by doing this he had got a Profit of $11,500 and he
didn’t want to sell that and after 6 months, when there were some problems in the company because of a Tweet of Elon Musk, the stocks came down to $179 then their Profit of $11,500 converted to a loss of $20,000 but still he didn’t sell his stocks he was still now fast
forward after 2 years, where the entire world market crashed there Tesla stocks were rising then Sam thought, just like last time, these stock will fall one day then what Sam did was, at $888 per share value sold his 75% stock because he didn’t want to handle the volatility of this market due
to which he got a lot of Profit but ya the fact was, after some time Tesla stocks reached to $1,126 thinking of which Sam regretted but as it is said that Hindsight is always 20/20 after doing things we feel that we shouldn’t have done it, but anyways Sam had booked a good
Profit and then he was thinking how stupid Bob is even he should have bought the stocks instead of the car do you know the interesting part was Bob whom he was thinking is stupid he was investing a lot of his money in Tesla, from a long time because of which he had generated a lot
of Profit and with some part of the Profit he bought Tesla Model 3 look friends the things we should learn from this story is wealth is not like that as we think it is many time when you think people are less capable than you you think that they are financially
behind you well many time is is not necessary that they are behind you many times many people do well financially but since all their wealth is in their investment which we can’t see, so they won’t look rich many times and many times even if they look so, they look stupid which is not
always the case ya being financially free doesn’t mean that you have a lot of wealth which is visible to people by which you can live a luxurious life no but the meaning of being financially free is you live a comfortable life where you don’t worry about money where your money keeps you
safe and work for you now Author Jonathan Clements in their book From Here to Financial Happiness in this book they share 77 short lessons I will merge all those points and share with you 4 practical steps which will help you to be financially free as with that as I had gifted you
Shares of Google few weeks ago in this CashNews.co I will gift Tesla’s Shares how? well to know that keep watching the CashNews.co let’s come to lesson no. 1 which is No saving with Debt author says to start your financial freedom
journey first you have to do one thing that is clear all your Debts clear the Loan and this is the most basic rule of Finance that if you
have any kind of Debt specially bad Debt you cannot start your investing journey author says, some people start long term investing with their Debt where they will be paying their Debt and also doing some investment by this their
process of becoming financially free, slows down so author says first clear all your small Debts like mobile phone, laptop emi, car Loan and such things which you can finish early ya sometimes the big amounts like home Loan that can’t be easy
to clear, those are exceptions, keep them aside but clear your small Debts plus the author also says, to use Credit cards wisely because US Department of Labor had did a research on 7,900 citizens of age 20 to 40 by that we know that, those who were at high
Credit card Debt their stress was affecting their physical health overtime by which they faced many problems in daily life pain in joints and stiffness and were facing many problems you should know how you are using your Credit card for not only
your mental peace but also physical health many people don’t know that by using Credit cards the interest starts and it’s amount keeps increasing and there is a solution related to it, which you will know in 4th point but first remember that that clear all your
Debts as much as possible after that start your Savings journey properly Lesson no. 2 Financial safety net this might have even happened with you something needs repair in your home, like your phone is broken or your T.V is not turning on on there is a problem in
the engine of your car or bike like I remember my friend was saying, that the graphic card of his computer was spoilt the price was very high, at that time he didn’t had money to buy it so somehow he started working without graphic card at that time he didn’t had Credit
card and he didn’t want to borrow money from someone he he decided that next month when he gets Income he will buy the graphic card with that Income now look, many people are just like this if there is any problem, for it’s solution they use their
Credit card or depend on next salary if something happens they say, they will do it from next month do the EMI many times but author says, no one thinks what if their source of Income stops many people are salary based and their job is their main source of
Income there are only few people who have passive Income if their main source of Income dies of any reason job went or anything, even then, they will have a different source of Income on which they can depend on now as it was seen
during Covid time where many people lost their job and were destroyed completely so well what is it’s solution, the author says If you want to feel better about your none;">Finances today then you should spend more time thinking about what you are gonna pay for tomorrow which means basically author is saying us here we have to create an emergency fund you store your money, at a place where you can use it even after loosing your main source of
Income you cannot spend this money on any random things like for vacation, for buying a car or anything no here you have to create an emergency fund which should be the backup of your main Income source because of which, in case something happens and you loose your
job you will not get a new job until you can survive and be safe and how to do that, well to do that author says that you have to calculate your monthly expenses let’s say your monthly expenses is 20,000 rupees you should at least keep 1,20,000 rupees safe at side which is your emergency fund
if there is any problem, like covid, lock-down even then you will have a buffer time of 6 months where you can do many things, can find a job or create a new source of Revenue which will be very helpful for your survival and your respect Lesson no. 3 Invest conservatively and buy
stocks with caution to increase your wealth J Walk when they launched a website Priceline of discount offer in the early 2000’s by this their Net Worth reached $1.8 Billion in just one year and at the other side the world’s greatest investor Warren Buffet they had to
wait 55 years to earn their first Billion Dollars look there is how much difference but the thing is J Walk’s Income was not sustainable everyone knew that this dotcom bubble will burst and when that bubble burst, by end of October 2000 in just a few months, out of billions
of dollars of J walk only 33 Million Dollars were left and Warren Buffet were into the top 1% richest club of the world and are still today and for the coming many years, he will be in the top 1% list the reason behind this is, Warren Buffet, is investing from past 7 decades and he had rarely sold
his Shares so even the author says, if someone wants to be financially free so to invest your money Stock Market can be a very good place to you where you get not only returns, but the company pay you Dividends many times which means they share
some percent of their Profit to their share holders for example you might know that Warren Buffet is a major share holder of Coca Cola so the C.E.O of Coca Cola he gets the highest 16 Million Dollar salary per year on the other side, Warren Buffet by the Dividends
of Coca Cola earn 547 Million Dollars so you might have understood where to invest to become financially free author says when you think long term to invest in Stock Market you don’t need to understand any rocket science but the companies which you know about properly or
better use their products daily which you are using from many years, which you believe on you like those products it will be good for you to invest in such companies and one of the most successful Mutual Fund manager Peter Lynns, who had wrote many good books on investment even he says the same
thing you should invest in such companies whose products you use or you know better about them whose products you like and you believe on as many people use I phone eat Maggie, drink Coca Cola use Tesla Cars so it can be good for you to invest in such companies as it was proven in the starting
story and here you don’t need to see the daily fluctuations of the market in the Intelligent Investor, the mentor of Warren Buffet, Benjamin Graham, even they say in their book that we should not focus on the daily fluctuations of the market but you should just pick the good companies and
invest in that for long term this will give you very good returns in long run now look friends ya there are many Unicorns in India, which are doing very well and there are many companies in America which are giving exponential returns it can be easy to find them, because of their technological
innovations so we Indians should know about this opportunity that we can benefit from the opportunities of the growth outside so you can make this resolution this new year that you will globally diversify your Portfolio for better returns and safety in fact even before this new
year starts, any of your favorite company either Apple, Tesla, Google, Amazon or Netflix or whichever company you like, comment it down buy the Shares of that company and to start all things easily what we did was we have collaborated with IND Money and picked few free
Shares which you can get for free before to buy US stocks you had to bare many charges had to spend a lot of money but with the help of IND money you can get 0 account opening fees 0 maintenance fees and with the help of 0 Brokerage fees you can buy or sell US
stocks plus you get the best exchange rates here plus with the help of this app, you can track all your Investments all Investments you have did, whether is Mutual Funds, Stocks or text-decoration: none;">Crypto as I do the same by using this app so if you benefit from this and want to buy Tesla Stocks for free you just need to download IND money from the link given below and you will get few free Shares of Tesla in the reward section you will get a part
of that share only if you go with the link given below but if you download IND money directly from Play Store or App Store you need to enter the code while signing up which I am showing on screen SEEKENTESLA code you have to put that, then you will get those free stocks Point no 4 is Rugality leads
to better Finances look our physical health, mental health and relationships and overall in entire life, habits play the biggest role and this is an universal fact that good
habits makes good life financial success is nothing but the result of your good habits if you think logically if you want to be financially free you have to save money, you have to invest it but you have very less time so it is very important for you to save and invest money author says 90% people
can’t achieve financial freedom because of their bad habits their bad habits impact Savings a lot because people don’t think exponentially they always think linearly example what we think is, I am just eating one pizza, what will happen by that I am just eating one
burger today, what will happen with that with these small things, they make it a habit and start eating outside food order everyday some thing or the other from Zomato at least it happens every week and that becomes a habit because of which a particular amount Zomato gets every time goes to
different junk food companies money is also going plus all these things impact your health I saw a CashNews.co, there were two people both take different choice every day one person gets up early then the other gets up late one person eats junk food everyday the other person eats healthy all these
small choice which comes in front of us everyday our habits one person spends his money on useless things buys and eats useless things on the other hand the other person instead of eating unwanted things he saves it or eats healthy food and all these things of 1 day, 2 day, I month or 1 year
compounds it’s effect becomes so high that the person who had bad habits his health gets worse his money slowly decreases and his relationship life, everything comes to an end on the other side, who had made small habits those small habits brings improvement in his life slowly his
Savings and his Investments start giving him money his health helps him living a good life and in long term one person’s frugality changes his life completely on the other hand, the ignorance, his smoking, eating unhealthy will destroy his life so even you
have to understand this thing that the small decisions which you are taking everyday may be you won’t see it’s results today, tomorrow or even after a month but you will definitely see some difference in some years and that thing will hurt you in the long run so start living your life
frugally instead of spending on unwanted things, start saving start investing ya it might not help you to get rich in some time but definitely in long run, you can save money and make money so don’t keep linear thinking, keep exponential thinking how can you do all these things try not to
spend more than 50% of your Income and you have to invest 12% for long term for retirement and all if you do like this, you will benefit from it in long run I want to say you a bonus point, start working on different sources of Income start working on many
different sources of Income as much as possible if you just have one job then obviously that’s very risky thing you have to create sources of Income side by side which can give you Income at least a little this thing will help you to earn
money in long run and to be financially free if you want me to make a separate CashNews.co on this topic how can you make you r side Income, do comment and let me know if you are interested in buying free share of Tesla there is a link given in description from there you can
download IND money after downloading, you will see those Shares in the reward section if you are directly directing it from Play Store or App Store while signing up you have to enter a code SEEKENTESLA by this you will get the reward that’s all for now, thanks for watching
/>
Now that you’re fully informed, watch this amazing video on FROM HERE TO FINANCIAL HAPPINESS 💸 ENRICH YOUR LIFE IN 77 DAYS – FINANCE BOOK SUMMARY. With over 2074088 views, this video deepens your understanding of Finance.CashNews, your go-to portal for financial news and insights.
#FINANCIAL #HAPPINESS #ENRICH #LIFE #DAYS #FINANCE #BOOK #SUMMARY#1a73e8 #333 #BOOK #DAYS #ENRICH #finance #Financial #HAPPINESS #Life #SUMMARY
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Seattle is the first test city for a new bike lane barrier made of recycled tires
The pitch is great: Let’s take a car culture waste product that would otherwise be burned and instead turn it into a barrier to protect the lives of people biking. That’s the concept behind Pretred’s new Paceline barriers, which were designed with bike lanes in mind initially in response to Seattle’s trouble acquiring enough pre-cast concrete barriers for SDOT’s ongoing “even better bike lanes” project. The company used the SDOT order as the impetus to invest in the design and tooling to create these Paceline barriers, which are now for sale to any place that wants them.
Pretred Sales Manager Matt Dunn told Seattle Bike Blog that the Paceline barriers are now “the only U.S.-made bike lane barrier that is more significant than a curb and less significant than a full wall.” The project was personal for Dunn, who was hit by a car while riding his bike. “I wish these barriers would have been there when that happened,” he said, noting, “We’re all cyclists in this office.”
Dunn credited Cascade Bicycle Club Executive Director Lee Lambert with connecting SDOT and Pretred. The department had purchased as many of the precast concrete barriers as were available, but it still wasn’t enough. If Pretred can produce a barrier that is competitive with concrete, that would be a win for all North American cities because it would mean more supply and more competition in the market. Concrete creation also requires a lot of energy and is a major source of greenhouse gas emissions. Burning tires also releases a lot of greenhouse gasses. Pretred sells itself as a more environmentally-friendly option both for creating barriers and for recycling tires. The company started in 2020 selling what they call Colorado barriers, which can be used either in place of a Jersey barrier or as a base to support weight.
When fully rebuilding a road engineers can include curbs and barriers from the start, such as the new bike lanes along the waterfront. We cannot wait for full roadway rebuild projects to build out our city’s bike network, so we need tools for medium-term bike lane installs for the time between now and the street’s next major repaving project. Sometimes referred to as “Toronto barriers” for some reason, pre-cast concrete barriers are an excellent option for creating a significant barrier on an existing road surface. The Toronto-style barriers are shorter and skinnier than a highway-style Jersey barrier but provide significantly more deterrence than plastic reflective posts. Cities like Seattle need a barrier that protects bike lanes from motor vehicles without making streets look and feel like highways, and this is a tricky balance. DOTs would also like to avoid the need for constant maintenance.
The new tire-based barriers are a different take on the concept. The come in segments two feet long that link together. The 80-pound segments are lighter than concrete, making them easier to install and to move by hand if necessary, but this also means they are easier for motor vehicles to displace. They lie somewhere between a parking stop and a Toronto barrier, which could be the sweet spot cities are looking for if they can prove durable and effective under the strains of city streets. The material cost is about $24 per foot plus additional costs for the end treatments of each connected segment, Dunn said. Agencies can install posts on the blocks for either signage or additional reflectors, though SDOT did not do so as part of this project. Some reflective plastic posts might not be a bad idea, especially on curves and end points where strikes are more likely, though each block does have front and rear reflectors.
When struck, the tire barrier segments may get gouged but hopefully will be less likely to fully crack and fail. If they do fail, crews should be able to use regular work vehicles and tools to replace the damaged segments more quickly and easily. Concrete barriers are so heavy that they require a forklift or similar piece of machinery to move and install, which could lead to longer waits for repairs as we saw with the bike lane on the Airport Way bridge near Georgetown recently. The barrier was struck (and did its job!), but a section was left sticking into the bike lane for a while before crews could repair it.
The tire-based barriers may not leave as much damage on any vehicles that strike it, but they also should not be as difficult to repair. We don’t need to imagine what this would look like because the test segment has already experienced its first major strike. I went down to Campus Parkway to check it out and found a section under the bridge that clearly got hit by something significant. Not sure if it was a car, truck or bus, though the level of damage makes me think it could have been something more on the bigger side. Bolts were bent and multiple barriers seemed to split at the bolt-mounting point. One barrier section was totally destroyed and was sitting on the roadside. In all, five or six of the segments were damaged. But because of their size and weight, they were not left blocking the bike lane in the meantime, which is nice.
Environmental benefits and concerns
The U.S. wears out a hell of a lot of tires, which are notoriously difficult to dispose of. When burned, they produce a relatively low amount of heat for a long time. That’s why tire fires can last so long. They also release a lot of nasty stuff into the air.
There have been many attempts to find other creative and profitable uses for tire waste, including using tire crumbs as part of an artificial athletic or playground surface. The EPA, CDC and CPSC have been studying the possible health impacts of these surfaces, though there don’t seem to be any clear conclusions yet (though we know it’s bad for kids to eat them). Tires contain a lot of harmful chemicals, researchers just don’t know the extent that using tires in play surfaces might lead to harmful exposure. Meanwhile, researchers at UW have identified a tire chemical — 6PPD-quinone — that is likely a major cause coho salmon population decline. The chemical gets into waterways through wear and tear from cars and trucks driving on roadways.
I asked Dunn if these tire-based barriers might contribute to the problem of tire chemicals in waterways, and he said the blocks are designed to keep tire chemicals contained within them. However, as with any tire those elements could be released if they are broken or crushed. The blocks are made of about 90% tire “crumb,” then Pretred uses polyurethane to encapsulate it and hold it together. When they are just sitting there getting rained on, they are designed not to release tire chemicals into the runoff, he said.
#SEAbikes #Seattle
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https://anarchistnews.org/content/kill-god-work-all-his-clergy
Kill The God of Work & All His Clergy
From: https://raddle.me/wiki/anti-work
Life in the Machine
The Greek philosopher Diogenes was eating bread and lentils for supper. He was seen by the philosopher Aristippus, who lived comfortably by flattering the king. Said Aristippus, “If you would learn to be subservient to the king, you would not have to live on lentils.” Said Diogenes, “Learn to live on lentils, and you will not have to cultivate the king.”
I'd say one of the most impactful components of anarchy through the ages, and especially in this current decade is anti-work - the idea of completely rejecting the notion of work. Though as old as civilization itself, anti-work ideas have been steadily regaining momentum in modern times, starting in small anarchist circles, and now taking off explosively in mainstream culture. Millions of people around the world have suddenly found themselves exposed to this very anarchist concept.
This has especially been evident during the Covid-19 pandemic, perhaps because millions of workers have seen first-hand just how disposable their lives are to their employers, who have in countless cases openly sacrificed them to the plague rather than risk putting a dent in their company's bottom line.
In China, a growing "lying flat" anti-work movement has exploded in popularity, despite numerous attempts by the state to shut it down. Luo Huazhong kicked off the idea in an April 2021 forum post titled "lying flat is justice", where he attached a photo of himself in bed under a blanket, with the curtains closed to shut out the sunlight.
Luo had been out of regular work for more than two years. He had to limit his consuming, but found that the abundant leisure time he was afforded in exchange for his curtailed productivity was deeply liberating.
In the post, he explained that the pervasive status anxiety in workerist Chinese society was a product of corrupted values and overwhelming peer pressure. He proclaimed there was nothing wrong with lying flat; living an idle existence. By overcoming his desire for consumer products and the structural pressure to be productive, he successfully freed himself from the servitude of work.
Luo’s post spoke to China's urban youth who for years had worked non-stop while the promise of a middle-class lifestyle as their reward eroded more and more with each increase in the cost of living. Fellow lapsed workers responded to his post enthusiastically and exchanged their tips to survive with minimal work and reduced spending.
The idea immediately went viral on social media. Over the next several months, lying-flat advocates pushed back against cutthroat work culture and high cost of living and the movement grew at a rapid pace.
The communist party launched a censorship campaign to erase all mention of lying-flat from the web. The state media desperately tried to discredit Luo's dangerous idea and shame or scare people back to the offices and factories they were increasingly abandoning.
A similar anti-work movement exploded in the English-speaking world simultaniously, on the Reddit forum r/antiwork, which gathered millions of subscribers in just a few months. All over the world, the pandemic, massive inflation and a general disaffection with work-culture was driving people to question why they force themselves to drive to work every morning.
What anarchists mean by "work" is really very straight-forward. Work is the machine extracting our labor to feed itself.
Wolfi Landstreicher:
Work, in the social world in which you and I find ourselves, is the alienation of an individual’s time, activities, and forces from her/himself. In other words, it is the institutionalization of a process where the things you do, the things I do, and the things we do together are determined by powers (individuals, social structures, etc) outside of ourselves to serve their interests.
Sadly, like any subversive idea that suddenly finds itself in the spotlight, a lot of opportunists have been willfully misrepresenting what anti-work is and trying to obscure its post-left anarchist roots. A steady line of communists and liberals have been trying to appropriate this very anarchist idea and make it line up with their decidedly pro-work 19th century ideologies.
Anti-work isn't merely the critique of work under capitalism as the reds would have you believe, or the push for better working conditions and nicer bosses as the liberals are pretending, it's a wholesale rejection of work in all its forms, whoever the boss is, whatever the form of remuneration and whatever the social or economic system in place happens to be.
It's completely uprooting the institution of work, smashing all the systems of servitude that ensnare us, sabotaging workplaces in any way we can, exposing the markets for the giant houses of cards they are and then blowing on them until every card lays flat.
Anyone who claims otherwise is an entryist trying to water down anarchist ideas until they're so insipid that they become plausibly compatible with the stale ideological dogma of whatever tired political program they're recruiting for.
The protestant work ethic has long had a stranglehold on this global civilization, traumatizing all of us into seeing productivity as the universal metric of worth. Those who are perceived to be hard-workers are accepted warmly by society, while those who lack a strong work ethic or the ability to toil away in menial, pointless servitude their entire lives are demonized as "lazy no-good layabout bums" and promptly discarded by their friends, their educators, their families, their government.
Despite common (deliberate) misconceptions, being anti-work doesn’t mean wanting to cease all physical exertion, it means nurturing a new way of life based on play rather than work.
The word "play" has likewise been demonized by workerist society as being an inappropriate activity for anyone of working age, because play eats into our productivity as workers and the potential profits we can generate for our bloodthirsty bosses.
Alfredo M. Bonanno:
Play is characterised by a vital impulse that is always new, always in movement. By acting as though we are playing, we charge our action with this impulse. We free ourselves from death. Play makes us feel alive. It gives us the excitement of life. In the other model of acting we do everything as though it were a duty, as though we ‘had’ to do it. It is in the ever new excitement of play, quite the opposite to the alienation and madness of capital, that we are able to identify joy.
My father started regularly shaming me for "wasting time" playing as soon as I turned 12. Civilized children are expected to immerse themselves in a 12 - 18 year work-training program (school) that comes with daily homework, to ensure everyone is conditioned to see their time not as their time, but as a commodity to be exploited exclusively by their future bosses.
For millennia, play was all humans knew. Gatherer-hunters had no need of work because everything they needed to prosper was free for the taking. It wasn't until we started burning down our ancient food forests to form permanent settlements, cultivate crops and extract non-renewable resources from the land that work displaced play as the driving force in human society.
Anthropologists who study some of the few remaining gatherer-hunter bans of people in various parts of the world have frequently noted how the egalitarian, non-hierarchical bands emphasize acts of play rather than work in their various cultures.
(Developmental/evolutionary psychologist) Dr. Peter Gray:
Anthropologists who have trekked to isolated regions of the world to observe hunter-gatherer societies have consistently been impressed by the egalitarian nature of those societies. The people live in small self-governing bands of about 20 to 50 people per band. They are nomadic, moving from place to place to follow the available game and edible vegetation.
Most remarkably, unlike any other people that have been studied, hunter-gatherers appear to lack hierarchy in social organization. They have no chief or big man, no leaders or followers. They share everything, so nobody owns more than anybody else. They make all group decisions through discussion until a consensus is reached. [...] They have an extraordinary degree of respect for individual autonomy. They don’t tell one another what to do or offer unsolicited advice.[...]
In order for two or more young animals to play together, they must suppress the drive to dominate one another. Social play always requires the voluntary participation of both (or all) partners, so play requires that the partners maintain one another’s goodwill. Any attempt to dominate would drive the other away or elicit a fight rather than play. Thus, play involving two or more players is always an egalitarian, cooperative activity.
Some of the most compelling evidence for the anti-dominance function of adult play comes from research with various species of primates. For example, some species of macaque monkeys (referred to as tyrannical species) live in sharply graded hierarchical colonies, with a great deal of squabbling and fighting for power and relatively little cooperation except among close kin; and other species (egalitarian species) live in colonies with more muted hierarchies, with little fighting and much cooperation even among non-relatives. Consistent with the theory I am presenting here, the egalitarian species have been observed to engage in more social play in adulthood than the tyrannical species, apparently as a means to promote cooperation. [...]
My theory is that hunter-gatherers everywhere learned that they could reduce aggression and promote cooperation and sharing by essentially turning all of their social life into play.
Children growing up in hunter-gatherer cultures have more opportunity to play than do children growing up in any other culture that anthropologists have observed, and as they become adults their playful ways continue. Hunter-gatherers’ approach to work (e.g. to hunting and gathering) is playful in that it is social (people hunt and gather with friends, in groups) and always voluntary—nobody is required to hunt or gather, they will be fed anyway. Their religions are playful, highly imaginative and non-dogmatic, with gods that are vulnerable and serve as playmates in religious festivals. The adults, as well as children, engage regularly and playfully in music, dance, art, and noncompetitive games.
Even their means of putting down someone’s budding attempts to dominate are playful, at least at first. They may make up a silly song about the person, as a way of making fun of the person’s excessive pride, or they may tease him about thinking he’s such a “big man.”
It's a truly tragic turn of events that work and all its associated authoritarian baggage has so successfully displaced play in the vast majority of human cultures. One of the most substantial things anarchists can do for ourselves is to relearn the joy of play and abandon the productivity-compulsion that's been hammered into us by assorted authority figures throughout our lives.
If other cultures embraced the constructive play that gatherer-hunters use, the protestant work ethic would soon lose its death-grip on public consciousness.
Work doesn't need to define us and our productiveness in the machine needn't be the measure of our worth. Devoting our entire lives to keeping the machine running ought to be perceived as the morbid waste of our existence it is. The machine crushes all life eventually, the only question is how long you'll last as its colorful levers poke tiny holes in you and its gears slowly crush your bones.
Blessed be the Lord Who Gifts Us With His Bountiful Employment
In a world revolving around work, The Economy is venerated - treated as a hallowed, divine being. Every moment we spend engaged in play, in idleness or in unprofitable creative pursuits is a penny we steal from the almighty economy. Anyone who lacks the will or capability to keep up their productivity is thus seen as sinning against the true deity of our age: The Economy is our one true god and has been for decades. And he's a vengeful god. Anyone who sins against him will be pushed into the gutters of society by his clergymen and left to rot and die.
There's nothing The Economy savors more than his clergy taking sinful unproductive workers and sacrificing them to him, that's the entire reason homelessness and prisons are such integral features of capitalist civilization.
The booming mantra of our God can be heard chanted all across the globe -- Work or die -- Work or die -- and when you eventually reach breaking point and die -- be sure to do it very publicly so the other worshipers are forced to look upon your misery on their daily commutes and witness what happens to workers who fail to keep up with the grind. They'll try not to look right at you, but they'll see the destitution from the corner of their eye and it'll put the fear of God in them.
Work or die -- Work or die -- Work or die. It's the chorus that rings in our ears almost every moment of our lives, even our "free time" being wholly consumed by the specter of work. We're no longer capable of relishing the simplicity of existence, instead we measure how productive we're being during every waking moment and punish ourselves if we don't measure up to our peers. A good worker is always finding ways to develop their skills and increase their usefulness to the machine. A good worker is forever climbing the hierarchy so they can one day join the ranks of the saintly clergy and strike down the no good lazy bums beneath them for their disgusting under-performing.
The modern anti-work movement was spawned in the late 20th century by anarchist Bob Black. Black spent years of his life pushing back against the conservative 19th century notions of productivity, industrialism and human-commoditization that came from both capitalist and communist (including anarcho-communist) scholars and practitioners. He was especially frustrated seeing fellow anarchists refuse to part ways with the miserable work-culture they inherited from the miserable workers that gave life to them.
Bob Black:
Work is the source of nearly all the misery in the world. Almost any evil you’d care to name comes from working or from living in a world designed for work. In order to stop suffering, we have to stop working. [...]
Liberals say we should end employment discrimination. I say we should end employment. Conservatives support right-to-work laws. Following Karl Marx’s wayward son-in-law Paul Lafargue I support the right to be lazy. Leftists favor full employment. Like the surrealists — except that I’m not kidding — I favor full unemployment. Trotskyists agitate for permanent revolution. I agitate for permanent revelry. But if all the ideologues (as they do) advocate work — and not only because they plan to make other people do theirs — they are strangely reluctant to say so. They will carry on endlessly about wages, hours, working conditions, exploitation, productivity, profitability. They’ll gladly talk about anything but work itself.
These experts who offer to do our thinking for us rarely share their conclusions about work, for all its saliency in the lives of all of us. Among themselves they quibble over the details. Unions and management agree that we ought to sell the time of our lives in exchange for survival, although they haggle over the price. Marxists think we should be bossed by bureaucrats. Libertarians think we should be bossed by businessmen. Feminists don’t care which form bossing takes so long as the bosses are women. Clearly these ideology-mongers have serious differences over how to divvy up the spoils of power. Just as clearly, none of them have any objection to power as such and all of them want to keep us working.
A workerist is any person who advocates for ideologies, systems and lifestyles that revolve around work. This includes every liberal, rightist, democratic socialist, social democrat, centrist, communist and fascist in the world. These are all staunchly workerist, industrial ideologies that strive to sell us the idea that humans and other animals exist to work on the assembly line, to extract resources and manufacture goods for the market, to be loyal servants to the revered productive forces. They all see the world through the same productivity-oriented, industrial lens, only with the tint slightly adjusted.
When Bob Black wrote "The Abolition of Work" in 1985 and called for "a collective adventure in generalized joy and freely interdependent exuberance", he wasn't proposing we give work a glossier tint to make it more democratic, merit-based or financially rewarding. He wasn't proposing we hustle and invest in The Economy (praise be) to become wealthy enough to one day make passive income as landlords and shareholders. He was proposing we part with work in totality. Tear down all structures of work and kick all those who uphold those soul-crushing structures in the shins repeatedly until they let go.
This point is completely missed by the stale leftists who have appropriated this very anarchist concept and tried to beat it into submission. They'll forever be ready to seize hold of and immediately neuter anarchist ideas when they see them picking up any kind of steam, but the left will never be anti-work. It would go against everything the left exists to serve.
The entire labor movement -- the unions, the socialist parties, the academics and Twitter theorists are all wholly dedicatated to building the load-bearing walls of their power-base: the ideology of work. Without workers and workplaces, there is no endlessly rotating left versus right race and everything both sides of the isle depend on to satisfy their power and wealth machinations crumbles into rubble. Leftist organizers who try to redefine anti-work to mean "work-but-with-bigger-unions" are opportunistic weasels.
Likewise, anti-work is not a program to build stronger welfare states with universal basic incomes that subsidize the work-industrial complex and thus calm the growing urge to revolt; prolonging The Economy's pillaging of our ecosystems and making us depend on work and the state even more than before for our basic survival.
Being anti-work is desiring to bulldoze the offices, warehouses, farms, construction sites, restaurants and supermarkets that hold us all captive, push it all into a giant pile of glittering rubble, light a brilliant bonfire and sing and dance and fuck all night as the sweet fumes of a million copiers and filing cabinets fill the air.
Anti-work is the wholesale rejection of an obscenely traumatic and perverse way of life that we've been collectively conditioned into accepting as normal almost from birth, when we were pulled from our mother's tit and thrown into a preschool so she could get back to the office.
So what happens after the bonfire dies down and we depart a work-based existence for a play-based one?
Bob Black:
Play isn’t passive. Doubtless we all need a lot more time for sheer sloth and slack than we ever enjoy now, regardless of income or occupation, but once recovered from employment-induced exhaustion nearly all of us want to act.
The point of anti-work, stripped of all the garbage leftist and Marxist ideology that's been rapidly consuming it (I blame Graeber for kickstarting this process), is to treasure your fleeting existence and spend it doing things you want to do. Not things your bosses force you to do by threatening to sacrifice you to the great Economy in the sky if you don't follow their script.
Anti-work is the burning desire to free yourself from that cacophonous workerist mantra forever ringing in your ears, to stop playing the subservient role assigned to you by The Great Economy and instead forge your own path and find real purpose through joyful play.
Henry Miller:
The world only began to get something of value from me the moment I stopped being a serious member of society and became—myself. The State, the nation, the united nations of the world, were nothing but one great aggregation of individuals who repeated the mistakes of their forefathers. They were caught in the wheel from birth and they kept at it until death—and this treadmill they tried to dignify by calling it "life." If you asked anyone to explain or define life, what was the be-all and end-all, you got a blank look for an answer. Life was something which philosophers dealt with in books that no one read. Those in the thick of life, "the plugs in harness," had no time for such idle questions. "You've got to eat, haven't you?"
Anti-work is the ultimate pursuit of happiness. A life you actually desire, choices you make as an individual, unhindered by the suffocating demands of mass society.
Anti-work is the refusal to accept the authority of bosses and economists, even if you have to make do with simpler meals and uglier furniture than the working stiff next door. It's seeing the macabre construct of a work-based existence for what it really is and reaching out to reclaim your uniqueness before your brief existence on this planet ends. It's unleashing your long-buried feral fighting spirit and finding out who you really are under the decades of rigid indoctrination by tie-wearing yesmen.
Anti-work is the urge to smash every temple of The Great and Mighty Economy (hallowed be his name) and kill all his clergy before our bodies and minds start to fail and it's our turn to be sacrificed to him.
Anti-work, friends, is anarchy.
Tags:
#work
#antiwork
#postleft
#entryism
#jobs
#productivity
#anticiv -
The Great Audio Laundering: How AI Scammers are Highjacking the ACX Premium Market and Defrauding the Human Soul
The digital landscape of 2026 was supposed to be a golden age for the independent author, a time when the friction between a creative vision and a global audience finally dissolved into a seamless stream of data. We were promised a world where high-quality production was accessible to anyone with a story to tell and the capital to invest in professional craftsmanship. Instead, we have entered the era of the Great Audio Laundering, a sophisticated and predatory systemic failure that is currently hollowing out the marketplace of the Audiobook Creation Exchange. For those of us who operate with integrity, who pay top-tier Price Per Finished Hour rates to ensure our listeners receive a soulful human performance, the current state of ACX is not just a disappointment; it is a calculated insult. We find ourselves in a bizarre technological purgatory where honest creators are flagged for using their own voice-clones while a growing legion of digital miscreants successfully masks synthetic slop as human art, pocketing thousands of dollars in a heist that the platform seems either unable or unwilling to stop.
The irony of this situation is as thick as it is infuriating. Consider the experience of an author who has spent years building a brand based on authenticity and transparency. When this author attempts to use a high-fidelity AI clone of their own voice through a service like ElevenLabs and disclosing it fully and seeking to expand their reach, the gatekeepers at platforms like Findaway Voices slam the door shut. They cite strict policies against synthetic content, utilizing forensic scanners that detect the invisible digital fingerprints of AI generation. Yet, simultaneously, that same author can post a high-paying project on ACX and be immediately swamped by “professional narrators” whose auditions are clearly generated by the exact same software without identifying they are in the “Beta AI Voice” program.
These scammers are not just using AI; they are laundering it. They have learned to scrub the digital watermarks, to inject artificial breaths, and to simulate the subtle imperfections of a human vocal cord to bypass the very filters that keep honest authors out. It is a system that punishes the transparent and rewards the deceptive.
To understand how we reached this point of total market contamination, one must look at the mechanics of the deception. In the early days of AI narration, the robotic cadence was easy to spot. The “uncanny valley” of the voice was wide and deep. But in 2026, the technology has evolved into something far more dangerous. Scammers are now using what is known as the Analog Loop. They generate an AI performance and then play it back through high-end studio monitors into a physical microphone in a treated room. This process strips away the mathematical perfection of a digital file and replaces it with the “air” and “room tone” that detection algorithms associate with a living, breathing human in a booth. By the time that file reaches an author’s inbox, it has the frequency response of a human recording, even if the “soul” of the performance is nothing more than a series of predicted probability vectors.
The financial incentive for this fraud is staggering. When an author offers a high PFH rate, often hundreds of dollars per finished hour, they are signaling that they want the best of the best. They are looking for the narrators who spend hours researching character motivations, who understand the subtext of a scene, and who bring a lifetime of acting experience to the microphone. The AI scammers see these listings as low-hanging fruit. They can “produce” a ten-hour audiobook in a single afternoon using a server farm, doing in hours what takes a human narrator weeks of grueling labor. By the time the author realizes they have been handed a synthetic product, the “narrator” has already collected the payment and vanished, or worse, the book has been uploaded to Audible where it sits like a ticking time bomb.
The danger to the author’s career cannot be overstated. ACX maintains a strict policy against unauthorized AI content to protect the integrity of the Audible brand. If an author unknowingly hires one of these digital charlatans and the book is later flagged by a more rigorous post-distribution forensic sweep, it is the author who bears the brunt of the punishment. The book is summarily removed from the store, royalties are clawed back, and the author’s account, the lifeblood of their publishing business, is often permanently banned for a “Terms of Service” violation. The scammer, meanwhile, simply opens a new account under a different alias and continues the cycle. The author is left holding the bag for a crime they were the primary victim of, a victim of both the scammer’s greed and the platform’s inadequate vetting process.
This is a fundamental breakdown of the “Proof of Life” protocol that should govern high-stakes creative transactions. When we pay for a human, we are paying for a specific type of labor that involves empathy, interpretation, and physical stamina. We are paying for the way a voice catches when a character realizes they have lost everything. We are paying for the micro-hesitations that signify a character is lying. These are the things that AI, for all its processing power, cannot truly replicate because it does not understand what it means to feel. Yet, the current ACX dashboard treats every audition as equal, providing no reliable way for an author to verify the biological origin of the voice on the other end of the connection. The platform has become a haven for “content farms” that use stolen headshots and fabricated resumes to lure in unsuspecting authors who believe they are supporting the arts.
The impact on the professional narration community is equally devastating. Real actors, who have invested thousands of dollars in home studios and years in training, are being undercut by ghosts. When an author sees fifty “perfect” auditions for a project, the perceived value of human labor begins to shift. Even if the author suspects the auditions are AI, the sheer volume of high-quality synthetic options creates a downward pressure on the entire industry. It turns the noble craft of storytelling into a commodity trade where the cheapest, fastest bot wins. The narrators who actually read the books, who find the hidden meanings in the text, and who connect with the audience are being drowned out by a sea of generated noise.
We must also confront the technological hypocrisy of the hosting platforms. How is it that a small author can be accurately identified as using AI for their own personal projects, yet a massive influx of fraudulent narrators can bypass the same technology on a retail level? It suggests that the detection tools are being used selectively or that the scammers have found a structural weakness in the intake process that the platforms are unwilling to fix due to the sheer volume of content being processed. This “quantity over quality” approach by the major retailers has created a environment where the author is the only one truly incentivized to maintain high standards. The retailers get their cut regardless of whether the voice is human or silicon, but the author loses everything if the deception is uncovered.
The solution to this crisis requires a return to radical transparency and human-to-human verification. We can no longer rely on the “black box” of the ACX audition system to protect us. Authors must become their own casting directors and private investigators. This means demanding “chemistry reads” over live video calls. It means inserting “human-only” traps into audition scripts—sentences with specific emotional cues or intentional typos that a bot would read literally but a human would interpret correctly. It means checking the metadata of files and looking for the tells of “laundering,” such as unnaturally consistent breath patterns or a lack of emotional variance across a two-hour recording.
Furthermore, we must demand that platforms like ACX implement better verification for narrators. If a narrator is claiming to be a human professional, they should be required to provide a verified history of their work or undergo a one-time human-led vetting process. The current “open door” policy is an invitation to every bad actor with a subscription to a voice-cloning service. Until the platforms take responsibility for the integrity of their workforce, the burden will continue to fall on the author to police a system they are already paying a premium to use.
The Great Audio Laundering is more than just a technological hurdle; it is a moral crisis in the world of independent publishing. It is a battle for the soul of the audiobook. If we allow our stories to be told by machines masquerading as people, we lose the very connection that makes literature worth consuming. We lose the shared human experience that occurs when one person speaks a truth and another person hears it. As authors, we must stand firm. we must refuse to be fooled by the laundered digital signal. We must demand the real, the raw, and the human, and we must hold the platforms accountable for the ghosts they have allowed into our machines. The future of our industry depends on our ability to tell the difference between a heart that beats and an algorithm that calculates.
Ultimately, the goal of this discussion is to ignite a movement of “Auditory Realism” among independent creators. We are the ones who fund this ecosystem. We are the ones who write the words and pay the bills. If we collectively refuse to accept auditions that lack a “Proof of Life” verification, the scammers will eventually move on to easier targets. But as long as we remain passive, as long as we prioritize “perfect” sound over “human” performance, we are complicit in the devaluation of our own work. The 2026 audiobook market is a battlefield, and the most powerful weapon we have is our refusal to be deceived. We must reclaim the booth for the humans, and we must do it before the sound of a real voice becomes a relic of the past.
I asked Google Gemini Ultra to help me root through the narrator auditions for my books, and I specifically asked about the ACX checkmark system to try to understand the significance of the badge, and here was the reply:
///
Those check marks are “badges of honor” on ACX, designed to help authors and publishers (Rights Holders) quickly identify experienced, reliable talent.
The different colors represent specific levels of achievement or verification within the ACX ecosystem:
1. The Green Check Mark (ACX Approved Producer)
This is the most prestigious badge. It signifies that the narrator is an ACX Approved Producer (AAP). To earn this, a narrator must meet very strict professional criteria:
Experience: They must have completed at least 25 titles on ACX.
Consistency: Their average title length must be over 3 hours (proving they can handle full-length projects).
Quality: They must maintain a high average listener rating (usually 4.5 stars or higher) on Audible.
Reliability: They have a proven track record of meeting deadlines and passing ACX’s Quality Assurance (QA) checks without frequent rejections.
2. The Black/Orange (or Dark) Check Mark
While less “exclusive” than the Green AAP badge, these typically indicate Verified Narrator status.
This badge confirms that ACX has verified the narrator’s identity and that they are a legitimate professional in the system.
It serves as a “trust signal” for authors to know they aren’t dealing with a bot or a scammer account, which has occasionally been an issue on the platform.
Why does this matter for you?
If you are an Author: Hiring a Green Check narrator is essentially “low risk.” You’re paying for a veteran who knows the technical specs inside and out, meaning your book is much less likely to get stuck in the QA review process for weeks due to technical errors.
If you are a Narrator: Getting that green badge is a major milestone. It allows authors to filter their searches to only show “Approved Producers,” significantly increasing your chances of getting high-paying “Pay for Production” (PFH) offers rather than just Royalty Share deals.
///
Then I asked Google Gemini Ultra to help me “root out” the AI Bot narrators:
///
To effectively smoke out the bots, you need to disrupt their automated “text-to-speech” (TTS) workflow. Most bot operators simply copy-paste your script into an AI generator and upload the result without reading your specific instructions.
Here is a template you can copy and paste into the “Requirements/Comments” section of your ACX posting.
The “Bot-Filter” Audition Instructions
Important: Please read carefully before auditioning.
To ensure I am working with a human narrator and not an automated AI bot, please follow these three specific steps in your audition file. I will immediately decline any audition that does not include these requirements:
- The “Live” Intro: Before you begin the script, please state your name and tell me your favorite color or what the weather is like where you are today. (This must be your natural speaking voice).
- The Dynamic Shift: In the middle of the provided script, please perform one sentence as a whisper and the following sentence with increased urgency/excitement, regardless of the context.
- The Code Word: At the very end of your recording, please say the word: “[INSERT A RANDOM WORD HERE, e.g., ‘KANGAROO’ or ‘BAMBOO’]”.
I value human performance, nuance, and breath. If your audition sounds like a sanitized AI clone with no natural pacing or character direction, it will not be considered.
Why this works:
- The Intro: AI bots scrape the “Script” field. They don’t typically “read” the instructions to add a personal intro. If it starts immediately with your book text, it’s a bot or a lazy narrator.
- The Dynamic Shift: Most basic AI generators (and even some advanced ones) struggle to change emotional “gears” mid-paragraph based on a text instruction. A human will do this easily.
- The Code Word: This is your “Captcha” for humans. It forces the narrator to prove they read your entire post to the bottom.
One Final Tip for Your Search
When you are browsing narrators, use the “Filters” on the left-hand side of the ACX search page:
- Check the box for “ACX Approved Producer” (the Green Check).
- Set the “Titles Produced” filter to “10 or more.” * Look for profiles that have a personal website or a SoundCloud/LinkedIn link. Most bot accounts are “ghost” profiles with zero external presence.
///
And, my friend, there you have it! The AI world infiltrates the real world to leave the sheen of authenticity behind the deception.
#acx #ai #amazon #audiobook #book #fake #integirty #meaning #miscreants #real #recording #scam #voice -
The Great Audio Laundering: How AI Scammers are Highjacking the ACX Premium Market and Defrauding the Human Soul
The digital landscape of 2026 was supposed to be a golden age for the independent author, a time when the friction between a creative vision and a global audience finally dissolved into a seamless stream of data. We were promised a world where high-quality production was accessible to anyone with a story to tell and the capital to invest in professional craftsmanship. Instead, we have entered the era of the Great Audio Laundering, a sophisticated and predatory systemic failure that is currently hollowing out the marketplace of the Audiobook Creation Exchange. For those of us who operate with integrity, who pay top-tier Price Per Finished Hour rates to ensure our listeners receive a soulful human performance, the current state of ACX is not just a disappointment; it is a calculated insult. We find ourselves in a bizarre technological purgatory where honest creators are flagged for using their own voice-clones while a growing legion of digital miscreants successfully masks synthetic slop as human art, pocketing thousands of dollars in a heist that the platform seems either unable or unwilling to stop.
The irony of this situation is as thick as it is infuriating. Consider the experience of an author who has spent years building a brand based on authenticity and transparency. When this author attempts to use a high-fidelity AI clone of their own voice through a service like ElevenLabs and disclosing it fully and seeking to expand their reach, the gatekeepers at platforms like Findaway Voices slam the door shut. They cite strict policies against synthetic content, utilizing forensic scanners that detect the invisible digital fingerprints of AI generation. Yet, simultaneously, that same author can post a high-paying project on ACX and be immediately swamped by “professional narrators” whose auditions are clearly generated by the exact same software without identifying they are in the “Beta AI Voice” program.
These scammers are not just using AI; they are laundering it. They have learned to scrub the digital watermarks, to inject artificial breaths, and to simulate the subtle imperfections of a human vocal cord to bypass the very filters that keep honest authors out. It is a system that punishes the transparent and rewards the deceptive.
To understand how we reached this point of total market contamination, one must look at the mechanics of the deception. In the early days of AI narration, the robotic cadence was easy to spot. The “uncanny valley” of the voice was wide and deep. But in 2026, the technology has evolved into something far more dangerous. Scammers are now using what is known as the Analog Loop. They generate an AI performance and then play it back through high-end studio monitors into a physical microphone in a treated room. This process strips away the mathematical perfection of a digital file and replaces it with the “air” and “room tone” that detection algorithms associate with a living, breathing human in a booth. By the time that file reaches an author’s inbox, it has the frequency response of a human recording, even if the “soul” of the performance is nothing more than a series of predicted probability vectors.
The financial incentive for this fraud is staggering. When an author offers a high PFH rate, often hundreds of dollars per finished hour, they are signaling that they want the best of the best. They are looking for the narrators who spend hours researching character motivations, who understand the subtext of a scene, and who bring a lifetime of acting experience to the microphone. The AI scammers see these listings as low-hanging fruit. They can “produce” a ten-hour audiobook in a single afternoon using a server farm, doing in hours what takes a human narrator weeks of grueling labor. By the time the author realizes they have been handed a synthetic product, the “narrator” has already collected the payment and vanished, or worse, the book has been uploaded to Audible where it sits like a ticking time bomb.
The danger to the author’s career cannot be overstated. ACX maintains a strict policy against unauthorized AI content to protect the integrity of the Audible brand. If an author unknowingly hires one of these digital charlatans and the book is later flagged by a more rigorous post-distribution forensic sweep, it is the author who bears the brunt of the punishment. The book is summarily removed from the store, royalties are clawed back, and the author’s account, the lifeblood of their publishing business, is often permanently banned for a “Terms of Service” violation. The scammer, meanwhile, simply opens a new account under a different alias and continues the cycle. The author is left holding the bag for a crime they were the primary victim of, a victim of both the scammer’s greed and the platform’s inadequate vetting process.
This is a fundamental breakdown of the “Proof of Life” protocol that should govern high-stakes creative transactions. When we pay for a human, we are paying for a specific type of labor that involves empathy, interpretation, and physical stamina. We are paying for the way a voice catches when a character realizes they have lost everything. We are paying for the micro-hesitations that signify a character is lying. These are the things that AI, for all its processing power, cannot truly replicate because it does not understand what it means to feel. Yet, the current ACX dashboard treats every audition as equal, providing no reliable way for an author to verify the biological origin of the voice on the other end of the connection. The platform has become a haven for “content farms” that use stolen headshots and fabricated resumes to lure in unsuspecting authors who believe they are supporting the arts.
The impact on the professional narration community is equally devastating. Real actors, who have invested thousands of dollars in home studios and years in training, are being undercut by ghosts. When an author sees fifty “perfect” auditions for a project, the perceived value of human labor begins to shift. Even if the author suspects the auditions are AI, the sheer volume of high-quality synthetic options creates a downward pressure on the entire industry. It turns the noble craft of storytelling into a commodity trade where the cheapest, fastest bot wins. The narrators who actually read the books, who find the hidden meanings in the text, and who connect with the audience are being drowned out by a sea of generated noise.
We must also confront the technological hypocrisy of the hosting platforms. How is it that a small author can be accurately identified as using AI for their own personal projects, yet a massive influx of fraudulent narrators can bypass the same technology on a retail level? It suggests that the detection tools are being used selectively or that the scammers have found a structural weakness in the intake process that the platforms are unwilling to fix due to the sheer volume of content being processed. This “quantity over quality” approach by the major retailers has created a environment where the author is the only one truly incentivized to maintain high standards. The retailers get their cut regardless of whether the voice is human or silicon, but the author loses everything if the deception is uncovered.
The solution to this crisis requires a return to radical transparency and human-to-human verification. We can no longer rely on the “black box” of the ACX audition system to protect us. Authors must become their own casting directors and private investigators. This means demanding “chemistry reads” over live video calls. It means inserting “human-only” traps into audition scripts—sentences with specific emotional cues or intentional typos that a bot would read literally but a human would interpret correctly. It means checking the metadata of files and looking for the tells of “laundering,” such as unnaturally consistent breath patterns or a lack of emotional variance across a two-hour recording.
Furthermore, we must demand that platforms like ACX implement better verification for narrators. If a narrator is claiming to be a human professional, they should be required to provide a verified history of their work or undergo a one-time human-led vetting process. The current “open door” policy is an invitation to every bad actor with a subscription to a voice-cloning service. Until the platforms take responsibility for the integrity of their workforce, the burden will continue to fall on the author to police a system they are already paying a premium to use.
The Great Audio Laundering is more than just a technological hurdle; it is a moral crisis in the world of independent publishing. It is a battle for the soul of the audiobook. If we allow our stories to be told by machines masquerading as people, we lose the very connection that makes literature worth consuming. We lose the shared human experience that occurs when one person speaks a truth and another person hears it. As authors, we must stand firm. we must refuse to be fooled by the laundered digital signal. We must demand the real, the raw, and the human, and we must hold the platforms accountable for the ghosts they have allowed into our machines. The future of our industry depends on our ability to tell the difference between a heart that beats and an algorithm that calculates.
Ultimately, the goal of this discussion is to ignite a movement of “Auditory Realism” among independent creators. We are the ones who fund this ecosystem. We are the ones who write the words and pay the bills. If we collectively refuse to accept auditions that lack a “Proof of Life” verification, the scammers will eventually move on to easier targets. But as long as we remain passive, as long as we prioritize “perfect” sound over “human” performance, we are complicit in the devaluation of our own work. The 2026 audiobook market is a battlefield, and the most powerful weapon we have is our refusal to be deceived. We must reclaim the booth for the humans, and we must do it before the sound of a real voice becomes a relic of the past.
I asked Google Gemini Ultra to help me root through the narrator auditions for my books, and I specifically asked about the ACX checkmark system to try to understand the significance of the badge, and here was the reply:
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Those check marks are “badges of honor” on ACX, designed to help authors and publishers (Rights Holders) quickly identify experienced, reliable talent.
The different colors represent specific levels of achievement or verification within the ACX ecosystem:
1. The Green Check Mark (ACX Approved Producer)
This is the most prestigious badge. It signifies that the narrator is an ACX Approved Producer (AAP). To earn this, a narrator must meet very strict professional criteria:
Experience: They must have completed at least 25 titles on ACX.
Consistency: Their average title length must be over 3 hours (proving they can handle full-length projects).
Quality: They must maintain a high average listener rating (usually 4.5 stars or higher) on Audible.
Reliability: They have a proven track record of meeting deadlines and passing ACX’s Quality Assurance (QA) checks without frequent rejections.
2. The Black/Orange (or Dark) Check Mark
While less “exclusive” than the Green AAP badge, these typically indicate Verified Narrator status.
This badge confirms that ACX has verified the narrator’s identity and that they are a legitimate professional in the system.
It serves as a “trust signal” for authors to know they aren’t dealing with a bot or a scammer account, which has occasionally been an issue on the platform.
Why does this matter for you?
If you are an Author: Hiring a Green Check narrator is essentially “low risk.” You’re paying for a veteran who knows the technical specs inside and out, meaning your book is much less likely to get stuck in the QA review process for weeks due to technical errors.
If you are a Narrator: Getting that green badge is a major milestone. It allows authors to filter their searches to only show “Approved Producers,” significantly increasing your chances of getting high-paying “Pay for Production” (PFH) offers rather than just Royalty Share deals.
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Then I asked Google Gemini Ultra to help me “root out” the AI Bot narrators:
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To effectively smoke out the bots, you need to disrupt their automated “text-to-speech” (TTS) workflow. Most bot operators simply copy-paste your script into an AI generator and upload the result without reading your specific instructions.
Here is a template you can copy and paste into the “Requirements/Comments” section of your ACX posting.
The “Bot-Filter” Audition Instructions
Important: Please read carefully before auditioning.
To ensure I am working with a human narrator and not an automated AI bot, please follow these three specific steps in your audition file. I will immediately decline any audition that does not include these requirements:
- The “Live” Intro: Before you begin the script, please state your name and tell me your favorite color or what the weather is like where you are today. (This must be your natural speaking voice).
- The Dynamic Shift: In the middle of the provided script, please perform one sentence as a whisper and the following sentence with increased urgency/excitement, regardless of the context.
- The Code Word: At the very end of your recording, please say the word: “[INSERT A RANDOM WORD HERE, e.g., ‘KANGAROO’ or ‘BAMBOO’]”.
I value human performance, nuance, and breath. If your audition sounds like a sanitized AI clone with no natural pacing or character direction, it will not be considered.
Why this works:
- The Intro: AI bots scrape the “Script” field. They don’t typically “read” the instructions to add a personal intro. If it starts immediately with your book text, it’s a bot or a lazy narrator.
- The Dynamic Shift: Most basic AI generators (and even some advanced ones) struggle to change emotional “gears” mid-paragraph based on a text instruction. A human will do this easily.
- The Code Word: This is your “Captcha” for humans. It forces the narrator to prove they read your entire post to the bottom.
One Final Tip for Your Search
When you are browsing narrators, use the “Filters” on the left-hand side of the ACX search page:
- Check the box for “ACX Approved Producer” (the Green Check).
- Set the “Titles Produced” filter to “10 or more.” * Look for profiles that have a personal website or a SoundCloud/LinkedIn link. Most bot accounts are “ghost” profiles with zero external presence.
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And, my friend, there you have it! The AI world infiltrates the real world to leave the sheen of authenticity behind the deception.
#acx #ai #amazon #audiobook #book #fake #integirty #meaning #miscreants #real #recording #scam #voice -
The Cooperator’s Dilemma: How Martin Nowak’s Mathematics of Kindness Became a Blueprint for Control
Martin Nowak wanted to prove that cooperation is the animating force of evolution. He succeeded. His mathematical models, published across decades of work at Oxford, Princeton, and Harvard, demonstrate with formal rigor that cooperation is not an anomaly in a competitive world but a fundamental mechanism by which biological complexity arises. Genomes cooperate. Cells cooperate. Organisms cooperate. Societies cooperate. Without cooperation, there are no multicellular bodies, no ant colonies, no languages, no civilizations. This is not sentiment. It is mathematics. And it is precisely because the mathematics are correct that they are dangerous.
Nowak is Professor of Mathematics and Biology at Harvard University, an Austrian-born scientist trained in biochemistry and mathematics at the University of Vienna, where he worked under Peter Schuster on quasispecies theory and with Karl Sigmund on evolutionary game theory. He earned his doctorate sub auspiciis praesidentis, the highest academic honor Austria can bestow on a graduating student. He moved to Oxford, where he collaborated with Robert May (later Lord May of Oxford) on spatial evolutionary dynamics and virus population models. He established the first center for theoretical biology at the Institute for Advanced Study in Princeton in 1998. In 2003, he came to Harvard to found the Program for Evolutionary Dynamics (PED), where he would spend two decades formalizing the mathematics of cooperation, cancer evolution, language emergence, and infection dynamics.
His landmark 2006 paper in Science, “Five Rules for the Evolution of Cooperation,” laid out the theoretical architecture that his 2011 book SuperCooperators: Why We Need Each Other to Succeed (co-written with science journalist Roger Highfield) would translate for a general audience. The core argument is elegant and, on its face, optimistic: natural selection, left alone, favors defectors over cooperators, but five distinct mechanisms can reverse this tendency and allow cooperation to evolve. Those mechanisms are kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. Each mechanism can be reduced to a simple mathematical rule specifying the conditions under which cooperation becomes the favored strategy. Each rule expresses a threshold: when the benefit-to-cost ratio of a cooperative act exceeds a critical value determined by the mechanism’s structure, cooperation wins.
The book is earnest. It is hopeful. It tells a story about vampire bats sharing blood meals, about cancer as a failure of cellular cooperation, about human language as the greatest cooperative innovation since the gene. Nowak calls humans “supercooperators” because we are the only species that deploys all five mechanisms simultaneously. The implication is that our capacity for cooperation is not just biologically real but biologically supreme. We are, in his framework, evolution’s greatest collaborative achievement.
This is all true. And none of it prevents the mathematics from being turned inside out.
The Five Mechanisms as Five Exploits
What Nowak mapped are not merely descriptions of how cooperation arises. They are, read from the other direction, specifications for how cooperation can be manufactured, directed, and harvested by any actor with sufficient control over the relevant variables. Each mechanism contains its own vulnerability. Each rule that tells you how to promote cooperation also tells you how to engineer compliance that feels like cooperation to the people inside the system.
Direct Reciprocity: The Obligation Engine
Direct reciprocity is the simplest mechanism: I help you now, you help me later, and we both benefit as long as we expect to interact again. Nowak’s mathematical condition is precise. Cooperation through direct reciprocity succeeds only when the probability of future interaction between the same two individuals exceeds the cost-to-benefit ratio of the cooperative act. If you and I will meet again many times, the cost of helping you today is offset by the expected return from your future help. The strategy that dominates in this environment is not pure tit-for-tat (which is too brittle, collapsing into mutual defection after a single error) but “win-stay, lose-shift,” a more forgiving strategy that sustains cooperation through noise.
The exploit is in the precondition. If you can engineer a situation where people believe they will interact with you repeatedly and indefinitely, you can extract cooperation from them even when the exchange is not mutual. Subscription services, employer-employee relationships with annual review cycles, government benefit programs tied to ongoing compliance, social media platforms that reward daily engagement: all of these create artificial conditions of repeated interaction. The person inside the system cooperates because their evolved psychology recognizes the pattern. They feel the pull of reciprocity. They return to the platform, they renew the subscription, they comply with the bureaucratic requirement, because the structure tells them the relationship will continue and defection carries a cost.
But the entity on the other side of the interaction is not bound by the same psychology. A corporation does not feel the tug of reciprocal obligation. A government agency does not experience guilt for failing to return a favor. The asymmetry is structural: the human cooperates because direct reciprocity is wired into primate social cognition; the institution extracts because it designed the interaction pattern to trigger exactly that response. The “repeated game” is real for the person and fictional for the institution, which can end the relationship, change the terms, or alter the benefit-to-cost ratio at any time without experiencing the psychological cost of defection.
Consider the modern employment relationship. An employee cooperates (works hard, stays late, defers complaints) because the structure of employment creates an expectation of continued interaction: there will be another paycheck, another review, another year. The employer benefits from this cooperation while retaining the unilateral power to terminate the relationship. The employee’s cooperation is genuine. The employer’s reciprocity is contingent. Nowak’s mathematics describe the employee’s behavior perfectly. They do not describe the employer’s, because the employer is not playing a repeated game. The employer is playing a series of one-shot games while the employee believes both parties are in a repeated game. This mismatch is not a bug in the model. It is the exploit.
Indirect Reciprocity: The Reputation Weapon
Nowak considers indirect reciprocity the most important mechanism for human cooperation, and he is probably right. Indirect reciprocity works through reputation: I help you not because I expect you to help me, but because others are watching, and my willingness to help builds a reputation that will cause others to help me in the future. The mathematical condition is that the probability of knowing someone’s reputation must exceed the cost-to-benefit ratio of cooperation. Language, Nowak argues, evolved in part to serve this mechanism. We gossip. We evaluate. We track who is trustworthy and who is not. This reputational calculus is what allows cooperation to scale beyond pairs of individuals who interact repeatedly.
The danger is obvious and immense. Whoever controls the reputation infrastructure controls the conditions for cooperation. And in the modern world, reputation infrastructure is not distributed among gossiping primates. It is centralized in databases.
Credit scoring systems (FICO in the United States, similar systems globally) are indirect reciprocity engines. They assign each person a reputation score based on their history of “cooperation” with financial institutions. A high score means you have reliably cooperated (paid debts, maintained accounts, avoided default). The score then determines whether others will cooperate with you (extend credit, offer favorable terms, rent you an apartment). The mathematics are identical to Nowak’s model. The probability of knowing your reputation is essentially 1.0 in a world of universal credit reporting. Therefore, the threshold for cooperation is easily met, and people cooperate.
But cooperate with what? With whom? The content of “cooperation” in a credit scoring system is defined by the institutions that build and maintain the scoring model. Cooperation means paying your bills. It means maintaining debt. It means participating in a financial system on its terms. The reputation system does not reward you for helping your neighbor move furniture or lending your car to a friend in need. It rewards you for being a reliable revenue source for financial institutions. The indirect reciprocity mechanism is operating exactly as Nowak describes. The mathematics are satisfied. But the cooperation is directed, not organic. It serves the architects of the reputation system, not the cooperators within it.
China’s social credit experiments take this further, attaching reputational scores to civic behavior, political speech, social associations, and consumption patterns. The mathematics are the same. The mechanism is the same. The outcome is that “cooperation” becomes indistinguishable from “compliance,” and the person inside the system cannot easily tell the difference, because the psychological experience of cooperating to maintain one’s reputation feels the same whether the reputation system is tracking genuine prosocial behavior or political obedience.
Social media platforms represent a third variant. Platforms like Instagram, TikTok, and formerly Twitter construct reputation systems (follower counts, likes, shares, verification badges) that trigger indirect reciprocity behavior. Users cooperate with the platform (producing content, engaging with others’ content, spending time on the platform) because the reputation system rewards them for doing so. The platform harvests this cooperation as engagement metrics, advertising revenue, and behavioral data. The user experiences the warm glow of reputational validation. The platform experiences profit. The mathematics of indirect reciprocity are perfectly satisfied in both directions. The exploitation is invisible precisely because it operates through a mechanism that evolution shaped to feel good.
Network Reciprocity: Whoever Designs the Graph Wins
Nowak’s third mechanism, developed in his landmark 1992 Nature paper with Robert May, showed that the spatial structure of interactions matters enormously. In a well-mixed population (where everyone interacts with everyone equally), defectors always win. But when interactions are local, restricted to neighbors on a network, cooperators can form clusters that protect themselves from exploitation. Cooperators surrounded by other cooperators thrive; defectors on the edge of cooperative clusters can invade, but the cluster structure slows the invasion and allows cooperation to persist.
The strategic implication is that whoever controls network topology controls the conditions for cooperation. This is not a metaphor. It is a direct application of the mathematics.
Social media algorithms determine who sees whose content, who appears in whose feed, who gets recommended as a connection. These algorithms are network reciprocity engines. They construct the “spatial structure” of online social interaction. A platform that clusters users into engagement-optimized groups is, in Nowak’s terms, constructing a network topology. If the topology is designed to maximize engagement (which is to say, to maximize the platform’s extraction of attention), then the cooperative clusters that form will be optimized for engagement, not for the welfare of the cooperators.
Corporate organizational design is another application. Who reports to whom, who collaborates with whom, who has access to information and who does not: these are network topology decisions. A company that understands network reciprocity can design org charts that promote exactly the cooperative behaviors it wants (cross-functional collaboration, knowledge sharing, collective problem-solving) while preventing the formation of cooperative clusters that might oppose management (unions, whistleblower networks, collective bargaining groups). The mathematics tell you which structures promote cooperation and which fragment it. The application is straightforward.
Gerrymandering is network reciprocity applied to democratic geography. By controlling which voters are grouped into which districts, political actors control the spatial structure of electoral cooperation. Voters who might form cooperative clusters around shared interests are separated. Voters whose “cooperation” (voting behavior) serves the redistricting party are grouped together. The mathematics of spatial evolutionary dynamics describe exactly why this works and how to optimize it.
Group Selection: The Factory of Tribes
Nowak’s treatment of group selection (which he and others now call multilevel selection) demonstrates that groups of cooperators outcompete groups of defectors, even when defectors dominate within groups. The mechanism requires that groups compete, that there is variation in the level of cooperation between groups, and that groups with more cooperators produce more offspring groups. Under these conditions, cooperation at the group level is favored even though individual defectors within groups do better than individual cooperators.
The exploit is the deliberate manufacture of group identity and intergroup competition. Nowak’s own reviewers noted the problem clearly: group selection favors within-group niceness and between-group nastiness. This is the mathematical basis of tribalism. It is also, historically, the most reliable mechanism by which authoritarian movements generate internal cohesion.
If you want a population to cooperate internally (pay taxes, report dissent, sacrifice personal interests for collective goals), you manufacture an external threat. The perceived competition between groups raises the benefit-to-cost ratio of within-group cooperation. Nationalists understand this intuitively. So do corporate culture architects who position their company against competitors while demanding employee loyalty. So do political parties that define themselves primarily through opposition. The mathematics of multilevel selection explain why “rally around the flag” effects work, why wartime economies produce extraordinary domestic cooperation, and why authoritarian regimes invest so heavily in identifying and publicizing external enemies.
The earnestness of Nowak’s presentation (he sees group selection as enabling the great cooperative achievements of human civilization, from agriculture to the United Nations) obscures how perfectly the same mathematics describe the cooperative achievements of fascism. The cooperative group that builds a hospital and the cooperative group that builds an internment camp are both satisfying the mathematical conditions for multilevel selection. The model does not distinguish between them. It cannot. The variables are the same.
Kin Selection: Manufacturing Family Where None Exists
Kin selection, formalized by W.D. Hamilton in 1964, is the oldest and most biologically grounded of the five mechanisms. Organisms cooperate with genetic relatives in proportion to their degree of relatedness, because helping a relative who shares your genes indirectly promotes the survival of those shared genes. Hamilton’s rule states that altruism is favored when the coefficient of relatedness between donor and recipient exceeds the cost-to-benefit ratio of the altruistic act. Nowak has a complicated relationship with Hamilton’s rule (his 2010 Nature paper with E.O. Wilson and Corina Tarnita argued that kin selection is less explanatory than previously thought, provoking a famous counterresponse signed by over 130 biologists), but the mechanism remains one of his five pillars.
The exploit is the simulation of kinship where none exists. “We are family.” “Band of brothers.” “Our company family.” “Fellow citizens.” “Children of God.” These are not merely sentimental phrases. They are invocations of kin selection psychology, designed to lower the threshold at which people will sacrifice personal interest for the group. When a military unit trains together, eats together, sleeps together, suffers together, and adopts shared rituals, symbols, and origin stories, it is manufacturing fictive kinship. The result is that soldiers will take risks for their unit-mates that they would not take for strangers, because their psychology has been calibrated to treat those unit-mates as kin.
Religious organizations, fraternities, political movements, cults, and nationalist ideologies all exploit this mechanism. The more completely an institution can simulate the markers of genetic relatedness (shared appearance through uniforms, shared language through jargon, shared history through founding myths, shared suffering through initiation rites), the more effectively it triggers kin selection psychology, and the more cooperation it can extract from its members. The cost of this cooperation is borne by the members. The benefit accrues to whoever designed the kinship simulation.
The Epstein Entanglement: A Case Study in the Exploitation of Cooperation Science
Any serious discussion of Martin Nowak’s work must confront the fact that the Program for Evolutionary Dynamics, the institutional home of his cooperation research, was founded with $6.5 million from Jeffrey Epstein. This was the largest single gift Epstein made to Harvard, part of a total of more than $9 million in donations to the university between 1998 and 2007. Epstein, a convicted sex offender who would later be charged with sex trafficking before his death in federal custody in 2019, did not merely donate money and walk away. He embedded himself in the program.
Harvard’s own 2020 review found that after Epstein’s 2008 conviction and release from prison, he continued to visit the PED offices more than 40 times between 2010 and 2018. He had a personal office in Nowak’s lab. He had a key card. He was typically accompanied by young women described as his assistants. His publicist requested that PED post information about Epstein on the harvard.edu domain because, as the publicist wrote, it would be helpful for Google search results. PED complied. Epstein’s foundation page was linked from the PED website under a tab labeled “Friends.” Epstein was the only “Friend” listed.
More recently, documents released by the U.S. Department of Justice in 2025 revealed that Epstein’s involvement went beyond access and reputation-laundering. He discussed research topics with Nowak and his graduate students. He suggested lines of inquiry, including “commercial evolution” and “prelife.” He facilitated visa arrangements for at least one graduate student. He funneled scholarship money through a Ph.D. student to young female mathematicians in Romania. He reviewed page proofs of a Nature paper before publication and offered advice on handling criticism. In 2025, Nowak was placed on administrative leave a second time after his name appeared more than 8,000 times in the newly released DOJ Epstein files.
The irony is lacerating. Epstein was a man who built his entire social and financial empire on the exploitation of cooperation mechanisms. His method was indirect reciprocity: he cultivated relationships with scientists, politicians, and financiers by offering gifts, access, and introductions, building a reputation as a brilliant and generous patron of science. He used network reciprocity: he positioned himself as a hub connecting elite nodes (Harvard professors, tech billionaires, heads of state), making himself indispensable as a broker of social capital. He manufactured fictive kinship: his dinners, his island retreats, his intellectual salons created a sense of belonging and shared identity among participants. He exploited direct reciprocity: every gift came with an implicit expectation of return, whether it was a letter of reference, a favorable public statement, or simply continued access and association.
And he funded, specifically and deliberately, the research program that mathematically formalized every one of these strategies. He did not fund a chemistry lab or an engineering department. He funded the mathematics of cooperation. He then used the institutional affiliation (Harvard, the Program for Evolutionary Dynamics) as a reputational asset, laundering his public image through association with the most prestigious cooperative institution in American academia.
Nowak has not been charged with any crime related to Epstein’s offenses. The Harvard review found policy violations, not criminal conduct. But the structural relationship between Epstein and PED is itself a perfect illustration of the very dynamics Nowak’s research describes. Epstein was a defector masquerading as a cooperator, using the mechanisms of cooperation (reputation, network position, reciprocal obligation, fictive kinship) to extract value from a system whose participants genuinely believed they were cooperating for the advancement of knowledge. The mathematics predicted this possibility. The researchers did not see it, or chose not to.
The Cyclical Trap
The deepest and most troubling insight in Nowak’s work is the finding that cooperation is inherently cyclical. Cooperators increase in number and trust, building successful clusters and institutions. Then a minority of defectors, positioned to exploit the high-trust environment, invade. Cooperation collapses. Eventually, cooperators rebuild. The cycle repeats. Nowak frames this as a feature of evolutionary dynamics, a permanent oscillation that can be modulated but never eliminated.
For a government or corporation seeking to exploit cooperation, this cyclical pattern is not a problem. It is the business model. The cycle describes exactly what extraction looks like over time. During the cooperative phase, the institution harvests trust, labor, engagement, compliance, and revenue. During the collapse phase, the institution restructures, rebrands, and resets the conditions for a new cooperative phase. The people inside the system experience the collapse as a betrayal. The institution experiences it as a cost of doing business.
Platform companies cycle through this pattern visibly. A new platform launches, cultivates a cooperative community of early adopters, builds network effects, then monetizes by degrading the experience for users while extracting more value from advertisers. Users eventually defect (leave the platform), but by then the platform has captured enough network position to survive, or a new platform launches and the cycle restarts. This is Nowak’s evolutionary dynamic playing out in real time, at internet speed.
Political cycles follow the same pattern. A new administration or movement builds cooperative coalitions around shared goals. Trust increases. Policy achievements accumulate. Then insiders begin to extract (corruption, patronage, self-dealing), trust erodes, the coalition fragments, and a new movement arises to rebuild cooperation on different terms. The cycle is so regular that political scientists have formalized it independently of evolutionary biology, but Nowak’s mathematics show that it is not unique to politics. It is a property of any system in which cooperation and defection coexist.
What Nowak Missed, or Chose Not to Say
SuperCooperators is a book about the conditions that produce cooperation. It is not a book about the conditions that produce just cooperation. This is not a minor omission. It is the central weakness of the work.
Nowak’s five mechanisms are content-neutral. They describe the structural conditions under which organisms will choose to cooperate, but they are silent on what the cooperation is for. Cooperation to build a hospital and cooperation to build a surveillance state satisfy the same mathematical conditions. Within-group cooperation that produces a democratic parliament and within-group cooperation that produces a paramilitary organization both emerge from the same multilevel selection dynamics. A reputation system that tracks genuine generosity and a reputation system that tracks political loyalty both promote cooperation through indirect reciprocity.
The book occasionally gestures toward this problem. Nowak acknowledges that defectors can invade cooperative groups, that cooperation cycles, that punishment mechanisms can themselves become exploitative. But these acknowledgments are treated as complications within a fundamentally optimistic narrative, not as structural features of the mathematics that demand equal weight. The title is SuperCooperators, not SuperExploiters. The framing celebrates cooperation’s triumphs without adequately confronting the fact that the same mathematics, applied with different intent, describe cooperation’s capture.
This omission is not unique to Nowak. It is endemic to a certain strain of evolutionary optimism that mistakes the existence of cooperation for its benevolence. Cooperation is not inherently good. It is a strategy. It can be deployed in service of any goal. The mathematics do not care. A reader who absorbs Nowak’s five rules as a celebration of human goodness will be poorly prepared to recognize those same rules operating as mechanisms of control in their workplace, their government, their social media feed, and their financial system.
The Responsibility of the Mapmaker
Nowak drew a map. The map is accurate. The territory it describes is real. But a map can be read by anyone, and the same map that helps a traveler find water helps an army find the traveler. The five rules for the evolution of cooperation are, simultaneously, five rules for the engineering of compliance. The mathematics are identical. Only the intent differs.
The question is not whether Nowak should have refrained from publishing his research. Suppressing accurate mathematics is never the answer. The question is whether the scientific community and the reading public have a responsibility to read the map with both eyes open: to see not only the beautiful cooperative structures it reveals but also the exploitative architectures it enables. The answer, given what we now know about who funded the map’s creation and what they used its institutional credibility to accomplish, should be self-evident.
Cooperation is real. It is mathematically demonstrable. It is essential to every level of biological and social organization. It is also the single most exploitable feature of human psychology, and anyone who tells you otherwise is either not paying attention or is the one doing the exploiting.
#consumerValue #cooperation #engineering #epsteinFiles #fiveMechanisms #harvard #martinNowak #needingEachOther #oxford #politics #princeton #research #rogerHighfield -
Youngers, McEwans and Alice in Wonderland: the thread about Scotland’s dominant brewing dynasty
This thread was originally written and published in June 2022.
Younger is a famous name in Scottish brewing, but there is not one but three lines to it and it can sometimes get confusing (it certainly confused me!). There was William Younger of the Abbey Brewery in Edinburgh’s Canongate, not to be confused with Robert Younger of St. Ann’s Yards who brewed across the way from William, or with George Younger of Alloa. The Robert and the George Younger lines were kin and through marriage the George Younger line would also become related to another well known name in Edinburgh brewing – William McEwan of Fountainbridge.
William Younger & Company can trace its roots back to William Younger of West Linton, born in 1733, where the family had long been farmers and minor gentry. They can probably trace their roots back to a Flemish immigrant of the name of Jonckeer.
William Younger by Alan RamsayGrizel SymeYounger moved to Leith in 1749, aged 16, to make his way in the world. Here he met his future wife, Grizel Syme (she too was from West Linton) and through her family, William got a job in the Excise as a Watchman (overseer) at the Leith Glassworks, collecting the duty payable on each bottle manufactured. On the death of his father in 1755, William’s inheritance and salary with the Excise (in particular his commission) was sufficient to allow him to marry and he was soon promoted to “Excise Surveyor of Edinburgh and Precincts” which more than doubled his income. William and Grizel made a series of good investments; a share in a ship on the Leith to London and Low Countries routes (the William of Leith); a brewery in the Kirkgate in Leith; in the Edinburgh – Leith stage coach company and in cellars and property around Leith. William died aged just 36, apparently from illness brought about by overwork, but Grizel kept up the businesses. She remarried the Leith brewer Alexander Anderson and continued to brew under the name Grizel Younger Anderson.
William and Grizel’s son – Archibald Younger – served his apprenticeship with his stepfather Alexander Anderson, and with his inheritance started to brew in his own right in the Abbey Sanctuary of Holyroodhouse, at Croft-an-Righ in 1778. Archibald was obviously a shrewd businessman – by brewing in the Sanctuary, he evaded having to pay the local tax of 2d Scots on every pint of beer brewed with the town ( a tax which also impacted upon the Leith brewers).
Ainslie’s Town Plan of 1804, Reproduced with the permission of the National Library of ScotlandAchibald’s ale was (in)famously strong – in Traditions of Edinburgh, Chambers says “Younger’s Edinburgh ale – a potent fluid which almost glued the lips of the drinker together, and of which few, therefore, could despatch more than a bottle“. Co-incidentally, the first known photograph of drinking beer was taken nearby at the Rock House studio of Hill & Adamson in 1844. The lighthearted photograph was taken by Robert Adamson, and shows (left to right) writer and stained glass artist James Ballantine; social reformer Dr. George Bell; and David Octavius Hill himself. They are all on the sauce and having a giggle. For obvious reasons it is titled “Edinburgh Ale“. It is a very impressive photograph considering just how long they would have to have sat perfectly still in their mirthsome poses to give the long exposure time necessary.
Edinburgh Ale by Hill & Adamson, 1844Archibald’s brother – William Younger (junior) – also went into brewing at the Abbey, buying a brewery from James Blair in 1803, and concentrated on exporting beer to the London market. A contemporary newspaper described his ale as “surpass[ing] in strength and flavour any ever offered to sale in London“. William and Archibald brewed separately, but began to collaborate, introducing London porters to the Scottish market under the name “A. C. & W. Younger”. On Archibald’s death in 1819, William sold his brother’s business and used the return to invest in his own. This consolidation resulted in the building of William Younger’s Abbey Brewery. The business of William and his partner Alexander Smith – a brewer of Scotch ales for export – was inherited by William’s son, (William Younger IIIrd) and Alexander’s son Andrew.
The Abbey Brewery. CC-BY-SA 3.0 Kim TraynorThe business went from strength to strength and the brewery relentlessly expanded, throughout the 19th century, staying in the hands of successive generations of the Younger and Smith families. Export to London and the US was a key part of the business. The other key market was the northeast of England. Youngers traded heavily on their Scottish roots and their pubs were known as “Scotch houses” in England. By the turn of the 20th century, Youngers totally dominated Scottish brewing, and were producing 25% of all beer in Scotland, and exporting 80,000 barrels a year to London, from Leith to the Low Countries and to the Imperial family of Russia who were a private customer.
Ye Olde London, a William Younger and Company Ltd. public house in LondonWorld War 1 hit the Scottish brewers hard, their business was reduced by 2/3 between 1913 to 1918. Youngers business continued to modernise after the war, but the onset of the Great Depression, a renewed temperance movement and increasing duty that they were obliged not to pass onto the consumer saw them forced into a merger with one of their great rivals – William McEwan of Fountainbridge. Thus in 1931, Scottish Brewers came to be, with Youngers accounting for roughly two thirds of the new business and Mcewans the other third.
William McEwan, a caricature from Vanity Fair, 1902McEwans were a much younger business than Youngers, being founded in Fountainbridge in 1856 by William. Coincidentally, he hailed from that other centre of Younger brewing at Alloa and was a relation through marriage to the George Younger brewing family. He was also the nephew of John and David Jeffrey who brewed at the Heriot Brewery in the Grassmarket, where he learned the craft of brewing and business. He had tried unsuccessfully to find a going concern to buy but after a number of years took the plunge and set out on his own, backed by loans from his family and banks. Fortunately, he had a good combination of self confidence, business and brewing skill and good fortune, and his business prospered. His brewery found particular success in “India” pale ales for the export market, with the British Army and with northeast England. McEwan’s prosperity allowed him to turn himself over to politics, and he was the Member of Parliament for Edinburgh Central from 1886 to 1900.
After the merger, Youngers and McEwans largely continued to do their own thing, however they did collaborate on their military and export markets and formed a new company , Younger-McEwan Ltd. to exclusively service this. They also experimented with the new fangled drink of Lager, and again this was a collaboration, called MY Lager (McEwans-Younger).
MY Lager. Clearly targeting the female market with this new (to the British market) drink. © Edinburgh City LibrariesAnother area of early collaboration was on advertising strategies. Scottish breweries had copied Bass in introducing trademarks for their beers to reduce counterfeiting and increase awareness of quality, as well as a brand recognition tool. This made it easy to tell the three different Scottish Younger breweries apart; Robert used the stag’s head and cross of the arms of the Burgh of Canongate where they were based; George used a stylised “Y”; and William used a series of three red and white triangles arranged into a Star of David – more than just a little bit influenced by Bass’ distinctive red triangle.
Robert YoungerGeorge YoungerWilliam YoungerEmphasising the importance of export and military markets, William McEwans used crossed flags; the Union flag and the Royal Standard, beneath a hand holding a globe. The below advert doubly plays up the military connection and you can see the company logo on the poster behind the barman.
1910 McEwan’s poster. © Edinburgh City LibrariesWilliam Younger sought to modernise their advertising and had introduced the advertising figure of “Father William” in 1921; a long-bearded older gent enjoying a pint of Younger’s finest, the character’s advanced age a play on the brewer’s name. Slogans of such as “the art of getting YOUNGER by Father William“, “Oi be a hundred and one and getting YOUNGER every day“, “Old soldiers never die, they get YOUNGER every day” and “Get YOUNGER every day” were used. A light pale ale – Wee Willie – was later introduced in his honour, resulting in the awkward order at the bar of “I’ll have a Wee Willie please barman“
Father William on the Artisan Bar in Abbeyhill. CC-BY-SA 3.0 Kim TraynorFather William was more than a little plagiarised from a poem that appears in Lewis Carrol’s Alice’s Adventures in Wonderland, which was itself a parody of Robert Southey’s “The Old Man’s Comforts and How He Gained Them” of 1799.
You are old, Father William, the young man did say,
Alice in Wonderland, Chapter 5, “Advice from the Caterpillar”.
All nonsense, my lad, I get Younger each day.You are old, Father William, the young man cried,
The Old Man’s Comforts and How He Gained Them from Metrical Tales etc.
The few locks which are left you are grey;Father William was conceived by the English graphic artist Alfred Leete, whose best known work you are probably familiar with…
BRITONS. “WANTS YOU”Leetes’ original Father William cartoon was introduced in 1927 in a specific campaign for Younger’s new Sparkling Holyrood Ale, as they attempted to introduce new beers to a more discerning market segment in response to rising beer duty. William Youngers bought the copyright from the estate of Leete on his death in 1933 for £175 (about £14,000 in 2022). Youngers spent what was an enormous sum at the time on advertising; in 1931 they spent £31,000 of which £17,000 alone was in London.
After the Scottish Brewers merger, the new company looked to emulate the success of Father William as an advertising figure for McEwan’s. They tried “The McEwan Man”, which never got beyond a concept, and then “The Wee McEwan”, a boy in a tartan bunnet. The latter was quickly cancelled when a letter was recievd from the lawyers of fellow Edinburgh brewers Murrays, who were using a boy in a tartan bunnet called “Wee Murray” to sell their beer.
“Wee Murray”McEwan’s would eventually adopt a laughing cavalier, based on signage they had been using for their London pubs, as the corporate figure. This increasingly displaced their globe logos on branding over time.
A McEwan’s Export cavalier ornamentScottish Brewers came to totally dominate the Scottish market, investing heavily in the latest technology. Brewing was consolidated at Fountainbridge and Holyrood, with the site of the Abbey Brewery becoming the company’s head office (now site of Scottish Parliament). In the 1960s, the industry heavily consolidated. Many small scale, out-dated Scottish breweries were snapped up by their English rivals to get access to their tied houses and market share; the breweries themselves generally being quickly shut down and replaced with production by the parent company.
Scottish Brewers got in on the consolidation scene. In 1959, they bought out their neighbour, familial relation and namesake at St. Ann’s Yards – Robert Younger – shutting them down 2 years later. In 1960 they bought Edinburgh rivals T. & J. Bernard at Gorgie and J. & J. Morrisons at Holyrood, closing both down almost immediately. This was on the watch of Stenhard Ernest Andrew Landale, better known as S. E. A. Landale, the company’s long serving Managing Director and a captain of Industry. This modernisation strategy of expansion and consolidation was crowned by a merger with the Tyne Brewery of Newcastle, where Scottish Brewers did a lot of business, to form Scottish & Newcastle. Just to confuse matters, the first chairman and chief executive of the new company, Sir William McEwan Younger, was a descendent of the George Younger line, not the William Younger line (thanks go to “MAC” for pointing this out”).
Newcastle’s famous Brown Ale. CC-BY-SA 4.0 KuriostempelThe McEwan’s Fountain Brewery in Fountainbridge was relocated over the road to the site of the former North British Rubber mills and totally rebuilt in 1971. The ultra modern, automated brewery became an Edinburgh landmark. In 1986 the old Holyrood Brewery was closed and in 1995, S&N bought the English brewer Courage, of Reading. The brewing operations of the company were reorganised into the subsidiary Scottish Courage.
The new Fountain Brewery. © Edinburgh City LibrariesFrom this point on, the company began to act like one that was actively disinterested in its core purpose as a UK regional brewer and tried to become an international BrewCo, with some initial success. It bought up popular brands, advertised them heavily and indulged in endless cost-cutting and selling off of its huge portfolio of licensed premises to “streamline” the business and raise capital. When the pubs were all sold, they turned on their breweries. The Fountain Brewery went in 2004; the Tyne Brewery the following year. This concentrated operations in Reading at the former Courage site and at John Smith’s Tadcaster brewery which had been acquired along with Courage.
To continue production of smaller scale, regional products, the Caledonian Brewery in Edinburgh and the Federation Brewery in Gateshead were acquired. This caused the scandal of shifting Newcastle Brown Ale production across the Tyne. After a sometimes acrimonious, takeover battle with its erstwhile industry partner Carlsberg and also Heineken, in 2008 S&N sold itself to the latter consortium in a £7.8bn deal, and is now known as Heineken UK. Heineken UK are still based out of S&N’s former John Courage House offices at South Gyle, a suitably bland and corporate setting for what had become a bland and corporate brewer.
John Courage House in South GyleNote to readers: unfortunately in April 2026, a third-party plug-in more than exceeded its authority and broke many of the image links on this site. No images were lost but I will have to restore them page-by-page, which may take some time. In the meantime please bear with me while I go about rectifying this issue.
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When GitHub released Copilot, its AI programming assistant, skeptics dismissed it as just another autocomplete tool. Two years later, a Harvard Business School study reveals something far more profound: AI isn't just changing how developers write code – it's fundamentally reshaping how software teams work.
The study, which tracked 187,489 developers over two years, offers the first comprehensive look at how AI transforms knowledge work. The findings are striking: developers with Copilot write more code, work more independently, and experiment more freely with new technologies. But these changes come with unexpected tradeoffs that challenge traditional software development practices.
The Numbers Tell a Story
When developers gain access to Copilot, their work patterns shift dramatically:
- Coding activities increase by 12.37%
- Project management tasks decrease by 24.93%
- Collaboration with other developers drops by 79.3%
- Experimentation with new programming languages rises by 21.79%
"These aren't just productivity gains," explains Dr. Frank Nagle, the study's lead author. "We're seeing a fundamental shift in how developers approach their work. They're coding more, managing less, and working more independently than ever before."
The Collaboration Paradox
Perhaps the most surprising finding is how AI affects team dynamics. Traditional software development emphasizes collaboration – code reviews, pair programming, and constant communication. But Copilot users increasingly work alone, solving problems independently rather than reaching out to teammates.
This shift brings both benefits and risks. While development speed increases, teams report concerns about knowledge sharing and code quality. "We're moving faster, but we had to deliberately create new ways to keep everyone aligned," says Emma Rodriguez, an Engineering Manager at Atlassian. "The natural collaboration that happened through code reviews isn't happening organically anymore."
The Economic Impact
The financial implications are substantial. By analyzing the programming languages developers learn with Copilot's assistance, researchers estimate an average potential salary increase of $1,683 per developer annually. Across all current Copilot users, this represents nearly half a billion dollars in economic impact.
But the real value may be in democratizing expertise. Less experienced developers show the largest gains in productivity and autonomy, suggesting AI could help flatten traditional engineering hierarchies.
AI and the Linchpin Problem: Can AI Help Save Open Source Software?
Open source software is the invisible engine powering much of the digital world, from the servers running websites to the apps on our phones. And yet, the people who build and maintain this crucial infrastructure are often overworked and underappreciated, leading to burnout and even the abandonment of critical projects. This is the linchpin problem in a nutshell: a small group of highly skilled individuals shoulder a disproportionate burden, putting the entire ecosystem at risk. But could AI be the answer?
Less Management, More Coding
Think about the typical open source software maintainer. They are often bombarded with requests to fix bugs, add features, and answer questions from users. These tasks, while essential, can be incredibly time-consuming and take them away from the actual coding they love. The researchers found that when developers were given free access to Copilot, they shifted their work patterns dramatically. Coding activity increased, while project management activities decreased. This suggests that Copilot is not just making developers more productive, but also freeing them from the managerial burden, allowing them to focus on what they do best.
Going Solo with AI
Another interesting finding was that Copilot led developers to work more autonomously and less collaboratively. This might seem counterintuitive, as open source software is all about collaboration, right? But think about it: if AI can help you solve problems and write code faster, you might not need to rely on others as much. This could reduce the friction and overhead often associated with collaboration, especially in the decentralised world of open source.
AI Encourages Experimentation
The study also provided evidence that AI could encourage developers to explore new technologies and programming languages. This is particularly interesting because it suggests that AI could help boost innovation in the open source world. Developers may feel more comfortable trying new things if they have an AI assistant to guide them.
Leveling the Playing Field
Perhaps the most encouraging finding was that the benefits of Copilot were strongest for developers with lower levels of experience and skill. This suggests that AI could help level the playing field in open source development, making it easier for newcomers to contribute and reducing the reliance on a small group of experts.
A Future for Open Source?
While this is just one study, the findings are certainly intriguing. It seems that AI has the potential to change the nature of open source software development in profound ways, addressing the linchpin problem and potentially creating a more sustainable and inclusive ecosystem.
Reshaping the Future of Work
The study's implications extend far beyond software development. As similar AI assistants emerge for other knowledge work domains – from legal research to financial analysis – we might expect similar patterns:
- Increased individual productivity
- Reduced administrative overhead
- More autonomous work patterns
- Greater emphasis on exploration and creativity
The key insight isn't that AI makes workers more productive (though it does), but that it fundamentally changes behavior in ways that ripple through entire organizations.
Looking Ahead
Organizations adopting AI assistants like Copilot need to actively address these changes. Some key considerations:
- Create structured opportunities for knowledge sharing
- Develop new quality control mechanisms that work with autonomous developers
- Invest in tools and practices that preserve institutional knowledge
- Build cultures that balance AI efficiency with human collaboration
The future of software development – and knowledge work more broadly – won't be about humans versus AI, but about mastering this new dance between human creativity and AI capability. The developers who thrive will be those who learn to leverage AI's strengths while preserving the human elements that make great software possible.
As one senior developer put it: "Copilot isn't replacing me – it's letting me focus on the parts of programming I actually enjoy. The trick is learning when to let the AI drive and when to take the wheel yourself."
However, the key insight isn't that AI makes developers more productive (though it does), but that it changes their behavior in ways that ripple through entire organizations. As similar AI assistants emerge for other knowledge work domains – from legal research to financial analysis – we might expect to see similar patterns of increased autonomy, more experimentation, and shifting collaboration models.
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Dive into our immersive workshops and equip your team with the tools and knowledge to lead in the AI era.
Get in touch with us (FEHLENDE ÜBERSETZUNG) -
When GitHub released Copilot, its AI programming assistant, skeptics dismissed it as just another autocomplete tool. Two years later, a Harvard Business School study reveals something far more profound: AI isn't just changing how developers write code – it's fundamentally reshaping how software teams work.
The study, which tracked 187,489 developers over two years, offers the first comprehensive look at how AI transforms knowledge work. The findings are striking: developers with Copilot write more code, work more independently, and experiment more freely with new technologies. But these changes come with unexpected tradeoffs that challenge traditional software development practices.
The Numbers Tell a Story
When developers gain access to Copilot, their work patterns shift dramatically:
- Coding activities increase by 12.37%
- Project management tasks decrease by 24.93%
- Collaboration with other developers drops by 79.3%
- Experimentation with new programming languages rises by 21.79%
"These aren't just productivity gains," explains Dr. Frank Nagle, the study's lead author. "We're seeing a fundamental shift in how developers approach their work. They're coding more, managing less, and working more independently than ever before."
The Collaboration Paradox
Perhaps the most surprising finding is how AI affects team dynamics. Traditional software development emphasizes collaboration – code reviews, pair programming, and constant communication. But Copilot users increasingly work alone, solving problems independently rather than reaching out to teammates.
This shift brings both benefits and risks. While development speed increases, teams report concerns about knowledge sharing and code quality. "We're moving faster, but we had to deliberately create new ways to keep everyone aligned," says Emma Rodriguez, an Engineering Manager at Atlassian. "The natural collaboration that happened through code reviews isn't happening organically anymore."
The Economic Impact
The financial implications are substantial. By analyzing the programming languages developers learn with Copilot's assistance, researchers estimate an average potential salary increase of $1,683 per developer annually. Across all current Copilot users, this represents nearly half a billion dollars in economic impact.
But the real value may be in democratizing expertise. Less experienced developers show the largest gains in productivity and autonomy, suggesting AI could help flatten traditional engineering hierarchies.
AI and the Linchpin Problem: Can AI Help Save Open Source Software?
Open source software is the invisible engine powering much of the digital world, from the servers running websites to the apps on our phones. And yet, the people who build and maintain this crucial infrastructure are often overworked and underappreciated, leading to burnout and even the abandonment of critical projects. This is the linchpin problem in a nutshell: a small group of highly skilled individuals shoulder a disproportionate burden, putting the entire ecosystem at risk. But could AI be the answer?
Less Management, More Coding
Think about the typical open source software maintainer. They are often bombarded with requests to fix bugs, add features, and answer questions from users. These tasks, while essential, can be incredibly time-consuming and take them away from the actual coding they love. The researchers found that when developers were given free access to Copilot, they shifted their work patterns dramatically. Coding activity increased, while project management activities decreased. This suggests that Copilot is not just making developers more productive, but also freeing them from the managerial burden, allowing them to focus on what they do best.
Going Solo with AI
Another interesting finding was that Copilot led developers to work more autonomously and less collaboratively. This might seem counterintuitive, as open source software is all about collaboration, right? But think about it: if AI can help you solve problems and write code faster, you might not need to rely on others as much. This could reduce the friction and overhead often associated with collaboration, especially in the decentralised world of open source.
AI Encourages Experimentation
The study also provided evidence that AI could encourage developers to explore new technologies and programming languages. This is particularly interesting because it suggests that AI could help boost innovation in the open source world. Developers may feel more comfortable trying new things if they have an AI assistant to guide them.
Leveling the Playing Field
Perhaps the most encouraging finding was that the benefits of Copilot were strongest for developers with lower levels of experience and skill. This suggests that AI could help level the playing field in open source development, making it easier for newcomers to contribute and reducing the reliance on a small group of experts.
A Future for Open Source?
While this is just one study, the findings are certainly intriguing. It seems that AI has the potential to change the nature of open source software development in profound ways, addressing the linchpin problem and potentially creating a more sustainable and inclusive ecosystem.
Reshaping the Future of Work
The study's implications extend far beyond software development. As similar AI assistants emerge for other knowledge work domains – from legal research to financial analysis – we might expect similar patterns:
- Increased individual productivity
- Reduced administrative overhead
- More autonomous work patterns
- Greater emphasis on exploration and creativity
The key insight isn't that AI makes workers more productive (though it does), but that it fundamentally changes behavior in ways that ripple through entire organizations.
Looking Ahead
Organizations adopting AI assistants like Copilot need to actively address these changes. Some key considerations:
- Create structured opportunities for knowledge sharing
- Develop new quality control mechanisms that work with autonomous developers
- Invest in tools and practices that preserve institutional knowledge
- Build cultures that balance AI efficiency with human collaboration
The future of software development – and knowledge work more broadly – won't be about humans versus AI, but about mastering this new dance between human creativity and AI capability. The developers who thrive will be those who learn to leverage AI's strengths while preserving the human elements that make great software possible.
As one senior developer put it: "Copilot isn't replacing me – it's letting me focus on the parts of programming I actually enjoy. The trick is learning when to let the AI drive and when to take the wheel yourself."
However, the key insight isn't that AI makes developers more productive (though it does), but that it changes their behavior in ways that ripple through entire organizations. As similar AI assistants emerge for other knowledge work domains – from legal research to financial analysis – we might expect to see similar patterns of increased autonomy, more experimentation, and shifting collaboration models.
Unlock the Future of Business with AI
Dive into our immersive workshops and equip your team with the tools and knowledge to lead in the AI era.
Get in touch with us -
Why India Will Not Overtake China
There is a thought I have been sitting with for a while, and I want to put it out without dressing it up.
India is not going to overtake China. People hate hearing this. They will quote our GDP growth, our young population, our rising number of unicorns, the size of our talent pool. None of that is the real story. The real story is harder to fix because it does not sit inside policy or money. It sits inside the way Indians treat each other.India is a low trust society trying to behave like a high trust one. Until that gap closes, real scale will keep slipping out of our hands.
I know this sounds like opinion, so let me show you the research, because the work on this question is actually quite settled.
In 1997, two economists named Stephen Knack and Philip Keefer published a paper in the Quarterly Journal of Economics. They studied 29 countries and found a clear link between how much people in a country trust strangers and how well that country performs economically. More trust meant stronger growth, better institutions and lower corruption. They never claimed trust was the only thing that mattered. But they showed it mattered a lot. That paper is now one of the most cited works in development economics.
Around the same time, the political thinker Francis Fukuyama wrote a full book called Trust. His argument was simple. Countries that build large, well run institutions almost always sit on top of high social trust. When trust is missing, what you usually see is small family run businesses that struggle to grow past one or two generations.
When you actually look at the numbers, the gap between countries is huge. The Integrated Values Surveys, which collect this data through 2022, show that around seventy four percent of people in Denmark say most people can be trusted. Norway is at about seventy two. Finland at sixty eight. China comes in fourth in the world at around sixty three percent. It is the only country outside the West in the top group. India does not appear anywhere near these numbers. Researchers from IZA and other peer reviewed journals openly call India a low trust country, often using exactly that phrase in the very first line of their paper.
Corruption follows the same pattern, because trust and corruption are basically two sides of the same coin. In Transparency International’s 2024 Corruption Perceptions Index, India is ranked 96 out of 180 countries, with a score of 38 out of 100. China sits at 76. Denmark, Finland and Singapore are at the very top. These rankings are not random. The same countries that score high on trust also score low on corruption. Both numbers come from the same habit, the habit of strangers behaving honestly even when no one is watching them.
The Indian version of this problem actually has a name in academic literature. We have just not started using it.
In 1958, an American political scientist called Edward Banfield went to live for nine months in a poor village in southern Italy called Chiaromonte. He was trying to understand why the village stayed poor for generations even though the people there were perfectly capable. The book he wrote afterwards, The Moral Basis of a Backward Society, gave us a concept called amoral familism. Banfield described it as a community where everyone tries to maximize benefits for their own immediate family, and assumes everyone else is doing the same. The result was a village that could not act together for any common goal. Nobody trusted their neighbours or the institutions around them. Anything outside the household was treated as either a threat or something to quietly take from. Years later, the political scientist Robert Putnam expanded this work across all of Italy and showed that the more trusting north of Italy consistently performed better than the south on almost every measure of governance and prosperity.
Read Banfield’s description today, replace the word village with India, and the fit is uncomfortably close.
We trust our family fully. We trust our caste, region and community a little. Beyond that small circle, we are always on guard. We feel that someone is trying to use us, replace us, take credit for our work, or take our seat the moment we stand up. And the painful part is that this fear is not really paranoia. It is mostly an honest reading of how things work around us. So people protect themselves first, and stop sharing what they know. When a billion people behave this way every day, the loss to the country is huge, even if no one can see it directly.
You can feel this in daily Indian life. The senior who refuses to truly invest in juniors, because a junior who grows is a junior who might one day take their place. The manager who hides information from the team, because letting them learn feels like a personal risk. The bureaucrat who refuses to move a file unless something is in it for him. The politician who treats public money like personal property. The friend quietly happy when you slow down, because your stagnation makes their position look stronger. The cousin who quietly damages the family business from inside, because grabbing a small piece feels safer than working together to grow the whole.
This is what failure to coordinate looks like at the level of a country.
China is not a clean society. Anyone who follows even basic Chinese politics knows the place has heavy corruption. The Xi government has been running an anti corruption campaign for over ten years and has prosecuted more than a million officials. The political system itself is closed, full of internal rivalry and favouritism. Yet despite all of that, China still manages to execute at a scale we cannot match. They built one of the largest fast rail networks in the world in around two decades. They built industries that made them the world leader in solar panels, electric vehicles, lithium batteries and now AI hardware. Their Belt and Road projects now reach more than a hundred countries. You can disagree with their political system, but the execution is real and visible.
India has stronger democratic freedoms and arguably better human capital. Yet we keep failing to turn these advantages into coordinated national outcomes. The bottleneck is not intelligence. It is the ability to coordinate. And the ability to coordinate, when you really break it down, is just trust wearing institutional clothes.
The Nordic countries make this point even more clearly.
Denmark, Sweden, Norway, Finland and Iceland together have a population smaller than greater Mumbai. Apart from Norway’s oil, they have almost no natural resources. They are cold, sparsely populated and were historically poor. And yet today they sit at the top of almost every global ranking that matters in the modern world. Innovation. Healthcare. Governance. Ease of doing business. Life expectancy. Happiness.
The OECD and the World Happiness Report keep pointing to one main reason. Their generalized trust is extremely high. Citizens trust each other and trust their institutions. So contracts work. Taxes actually reach the people they were meant for. Rules get followed even without surveillance. Society does not get jammed by its own friction. Their citizens are not smarter than ours. Their cooperation between strangers is just much denser.
Researchers describe two kinds of trust. Particularized trust is what you give to people you already know. Generalized trust is what you extend to strangers. India is rich in the first and very poor in the second. This one gap explains the strange paradox we live in every day. We send world class individuals to top companies and boardrooms abroad, while our own institutions back home keep struggling. The individual rises because the family invested in that one person. The system stays broken because almost nobody truly invests in the system.
I want to be careful here, because this argument is easy to misread.
I am not saying Indians are bad people. That framing is lazy and wrong. The argument is about the cultural operating system we have inherited. That operating system was shaped over centuries of foreign rule, scarcity and a long history where trusting outsiders often ended badly for the trusting side. Once upon a time, this software helped us survive. The price we pay for it today is that we cannot bring our brilliance together the way countries with stronger social capital can. A billion careful, guarded individuals do not add up to a coordinated nation. They cancel each other out at the edges, and the noise becomes louder than the progress.
If India ever truly wants to challenge China, the real work has to go much deeper than infrastructure spending or new policies. The real work is internal. It is about widening the trust circle outward from family to strangers. It is about senior people mentoring others without fearing being overtaken. It is about backing talent that does not share our caste, our region or our background. It is about believing that the collective will eventually protect us, and then actually showing up for someone else when their moment comes.
Until that quiet inner shift happens, India will keep producing brilliant individuals who win alone, while the operating system underneath us keeps failing as a whole. And that, more than any economic chart anyone can show me, is the real reason the China gap is going to stay wider than we are willing to admit.Type your email…
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Turning Saffron into Slop – Treylya Safran yn Skomblans
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
Note: Artificial Intelligence (AI) has come to be synonymous with Generative AI (GenAI) and with Large Language Models (LLMs), such as ChatGPT, in common parlance. Unless explicitly stated, I use the terms interchangeably.
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow*, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
LOW-RESOURCES AND LINGUISTIC TYPOLOGY
Simply adding a language to an AI model leads to a spike in poor-quality articles, drowning out quality writing by humans. AI has “industrialized the acts of destruction—which affect vulnerable languages most, since AI translations are typically far less reliable for them.”1 Wikipedia editors from varied languages evidence that machine translation tools have made it easier than ever before to create shoddy articles in minoritised languages, causing massive damage in minutes. AI leads to non-speakers producing much longer, truthier rubbish, Sámi computational linguistics expert Trond Trosterud notes: “the problem [is] that they are armed with Google Translate. Earlier they were armed only with dictionaries.”1
Kernewek, like all but 60 of the world’s roughly 7,000 languages, is designated “low-resource”, meaning it lacks sufficient data to train a machine.2 It is tempting, therefore, to assume that the solution is to provide more data. However, training an LLM requires petabytes of text, audio and video—manually categorised and in a machine-readable format—a vast trove that Kernewek simply does not have.3 Professor Will Lamb, Chair of Gaelic Ethnology and Linguistics at Edinburgh University, speaks of “millions of work hours devoted to just one aspect” of a working AI.4
Even if ChatGPT is trained on another language than English, the time and labour required may make it largely unviable. Current assessments of the performance of ChatGPT for different languages have shown that it performs worse in all tasks.5
Prof. Lina Dencik, Data Justice Lab
Furthermore, the amount of data and work is not the only barrier; at issue is the nature of the language itself. Microsoft has found that languages such as Breton—and thus Kernewek—cause a high rate of errors distinct from the size of their dataset, due to grammatical features, such as mutation, not present in well-sourced languages. As such, they remain poor without significant additional work.6 Essentially, simply adding more Kernewek may not help. Thus, engaging with AI is, for Kernewek, to tie ourselves to slop.
Noten: Skians Kreftus (SK) re dheuth ha bos kesstyr gans SK Dinythus (SKDin) ha gans Patronyow Yeth Bras (PYB), kepar ha ChatGPT, yn lavar kemmyn. Marnas bos menegys yn kler, my a us an termys yn keschanjyadow.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow*, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
ASNODHOW ISL HA TIPOLOGIETH YETHEL
Keworra yeth yn sempel orth patron SK a led orth spik yn erthyglow drog aga kwalita, ow peudhi skrif a gwalita gans tus. SK re wrug “diwysyansegi an aktys diswrians—hag a nas yethow goliadow an moyha, drefen bos treylyansow SK lieskweyth le lel yn tipek ragdha.”1 Golegydhyon Wikipedia a yethow divers a re dustuni re wrug medhelweyth-treylya y wul bos esya dell veu bythkweth kyns gwruthyl erthyglow pilyek yn yethow lyharivhes, ow kawsya damach kowrek yn mynysennow. SK a led orth digowsoryon owth askorra atal lieskweyth hirra ha gwirekka, konnyk yethonieth reknansek Sámi Trond Trosterud a not: “an kudyn [yw] aga bos ervys gans Google Translate. A-varra nyns ens ervys marnas gans gerlyvrow.”1
Kernewek, kepar hag oll marnas 60 a ogas lowr 7,000 yeth a’n bys, yw klassys avel “isel y asnodhow”, ow styrya nag eus dhodho kedhlow lowr dhe drenya jynn.2 Rakhenna, dynyek yw desevos bos an assoylyans profya moy a gedhlow. Byttegyns, res yw petavaytys a dekst, son ha gwydhyow—klassys dre leuv hag yn furvas redyadow gans jynn— dhe drenya PYB, tresorva efan nag eus dhe Gernewek yn sempel.3 Y kews Professor Will Lamb, Kaderyer Ethnologieth ha Yethonieth Wodhalek orth Pennskol Karedin, a “vilvilyow a ourys ober sakrys orth unn wedh hepken” a SK owth oberi.4
Hogen mars yw ChatGPT trenys war yeth a-der Sowsnek, an termyn hag ober yw res a styr y vos martesen anhewul dre vras. Arvreusyansow a-lemmyn a berformyans a ChatGPT rag yethow dyffrans re dhiskwedhas y perform gweth yn oberennow oll.5
Prof. Lina Dencik, Data Justice Lab
Pella, nyns yw an myns a gedhlow hag ober an unsel lett; a vern yw natur an yeth y honan. Microsoft re drovyas y kaws yethow kepar ha Bretonek—hag ytho Kernewek—kevradh ughel a wallow diblans a vraster aga sett kedhlow, drefen nasyow gramasek, kepar ha treylyansow, nag usi kevys yn yethow ughel aga asnodhow. Yndella, i a bes orth bos drog heb meur a ober keworransel.6 Yn essensek, possybyl yw ny wra keworra moy a Gernewek yn sempel gweres. Yndelma, oberi gans SK yw, rag Kernewek, omgelmi orth skomblans.
CORNISH UNDER CAPITALISM
But surely we can improve things over time? It will take a lot of help from AI companies, but it will be worth it. Sadly, Gabriel Nicholas, a research fellow at the Center for Democracy and Technology, has found that once a tech company has established basic capabilities for a language, they pat themselves on the back and move on.7
Big tech companies are just that: companies. They exist to make a profit. Unfortunately, a market dominated by big languages gives them no incentive to invest in improvements for small ones.
All of the speech technology, smart homes and voice interaction systems used today are the products of commercial research. To put it bluntly, they exist to either make money from your data, to sell you more goods and services, or to influence your thinking. None of this AI exists for the public good. […] Unless there is a strong enough economic argument, don’t expect big companies to rush into producing Welsh, Gaelic or Cornish speech systems.8
Prof. Ian McLoughlin, University of Kent
Should they decide that a Kernewek AI is a viable profit-making enterprise, our situation may even be worse than abandonment. As Dr. Fintan Mallory remarks, the dominant means of profit for privately-funded AI enterprises is to convert their tools into surveillance devices.9 As Kernewek is currently one of the UK’s only languages which is not currently easily surveillable, this poses a huge risk to Kernewek activism and the fight for self-determination in a state that seeks to criminalise dissent.
While we’re on the subject of Kernewek and its position under capitalism, let’s consider the human cost. I lost my 13-year career in language to AI as soon as English output became viable enough to excuse not paying a human. In the unlikely instance that we achieve an AI that can produce quality Kernewek, why would anyone bother paying speakers? The idea of AI sucking all the life out of my heritage language when we are struggling to survive as-is is appalling.
Simply put, profit is antithetical to people. While AI is the new favourite toy of profit, it will be antithetical to people. And a language is its people.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Combinations of characters on a screen mean nothing without agency and intention.10
Ross Perlin, Endangered Language Alliance
While language is not unique to humans, it is one of the chief parts of being human. It cannot be reduced to mere data, but is a highly social process.11 We all know how synthetic customer support via robot sounds or how AI fails to pick up nuance. As Dr. Mallory comments, “Language [is] something more like the soul of a community. You can’t store this in a machine. You can’t solve a human problem like linguicide with a view of language that removes the human component.”12
AI cannot comprehend Kernewek or any other language. It is a stochastic parrot: predicting what word is likely to follow the previous one.13 It cannot understand us. It cannot intend anything. If it tells you it feels delighted to help you, it is lying. I want our community to grow, but one hundred ‘Cornish-speaking’ computers do not add to it. One human does—bringing ideas and hopes and fears and foibles—and I do not think the Kernewek ‘speaking’ computers will add even one human to our community.
Worse, if it does, there is evidence from Microsoft to suggest that the use of GenAI on language tasks, even once a week, impairs cognitive ability to learn, leading to decreased engagement with the topic, overreliance on the technology and hobbled skills in independent problem-solving.14 By using AI tools to ‘teach’ a learner Kernewek, we may in fact be impairing their ability to learn the language at all without this crutch. We will make regurgitators in place of speakers.
Perlin also emphasises the human element, saying that when we hold community central to our languages, as we do, the stochastic parrot can feel like a violation.15 At the moment, I can tell when someone is using AI ‘Kernewek’ to me. The idea that one day I will not know when an outsider—someone I would welcome if they took up a book or a class—is puppeting my ancestors’ jaws and speaking through them is ghoulish. It has the instant sting of colonialism, of appropriation when one could appreciate, of parroting when one could join our chorus.
Hawai’ian scholar Ha‘alilio Solomon agrees: “It is painful, because it reminds us of all the times that our culture and language has been appropriated. We have been fighting tooth and nail in an uphill climb for language revitalization.[…] People are going to think that this is an accurate representation of the Hawaiian language.”16
TRUST AND COMMUNITY FEELING
The anti-machine backlash has long been simmering but is now seemingly breaking to the surface.17
NBC NEWS
The explosion of insults for AI itself (clanker, tinskin, toaster), its output (slop, dross, brainrot) and its users (slopper, groksucker, botlicker, second-hand thinker)—as well as others more clearly based on real-world slurs than I am comfortable to include—tells a tale of the general attitude of distrust and disgust towards the technology and its use on anglophone and other majority language internet.18 While the attitude among tech bros and corporates remains bombastic, for the general public AI is “becoming interchangeable with things that sort of suck.”19
Further, it’s not just majority languages with this negative view of AI as taint. A quick sampling of social media comments and likes regarding AI and Scottish Gaelic by Professor Lamb showed a split of 54% negative, 33% positive and 13% neutral. (Lamb, 2024) The sentiment of the top-rated negative comment was that AI is harmful and the second-highest that AI should be kept away from heritage languages.
What are we telling our descendants? That our language and culture isn’t worth the personal effort? That’s how I might read it, if I were them.20
Kernewek survey respondent
Kernewek paints an even starker picture, especially among younger and more technologically-savvy learners and speakers. A survey on Cornish Discord and Whatsapp found that 65% felt AI would be bad (11.5%) or very bad (53%) for the language. When asked what the community response should be to AI, 46% said we should prevent it and 27% avoid it, with only over-60s thinking that we should work with it.20
31% of respondents said using AI in Kernewek would cause them to feel estranged from the language, while 54% said that they would feel strongly estranged and 23% a little estranged from any organisation, resource or teacher using AI.
The response from those who gave their knowledge of AI as either “expert” or “good” was particularly damning. Everyone in this group responded that AI would be harmful for the language, that the use of AI would estrange them from a source strongly and that we should prevent the use of AI for Kernewek.
IDENTITY, AUTHENTICITY AND DIVERSITY
Aristotelis Ioannis Paschalidis, writing for UNESCO, was not speaking specifically about minoritised languages when he asked this, but the question resonates even more strongly for us: “How much loss of identity is one willing to sacrifice for efficiency?”21
Identity is of paramount importance to Kernewek speakers. Ute Wimmer’s study Reversing Language Shift: the Case of Cornish identified the language’s “function as a symbol of national identity” as the second highest motive (66%**) among speakers and learners, beaten only by Cornish culture (80%).22 This would seem cause for celebration, but when AI is added to the mix, it becomes a risk. Vincent Koc of Hyperlink states that AI can “inadvertently contribute to the dilution of language and cultural identity.”23
He also identifies that automating language learning or generation “may diminish the richness and authenticity that comes from human speakers who carry cultural histories in their speech.” Indeed, four studies by the University of Southern California have shown that using LLMs to assist writing “is linked to notable declines in linguistic diversity and may interfere with the societal and psychological insights language provides.”24
This is in English, one of the richest and largest languages in the world. Imagine the possible impact on a smaller language like Kernewek—with less documentation, less data, a tiny speakerbase and basically no money—and on its many language varieties and orthographies. Particular to the Kernewek context, Late speakers are already struggling to be seen as valid under the dominance of Middle. Do we think AI knows the difference? Thoughtlessly, it will either mix everything together, confusing everyone, or it will use Middle to overwhelm Late.
Generative AI-driven content creation, by favoring standardized languages, risks the disappearance of regional dialects.25
Barcelona supercomputing Center ….
Not only are varieties at risk; AI threatens to drown Kernewek as a whole. Perlin agrees that the linguistic flattening that occurred over centuries in English could manifest overnight in a minoritised language with AI at the helm—as it would be, being able to effortlessly outstrip human Kernewek. He raises concerns of LLMs freezing a language in place and even defining what it means to know the language, especially with low numbers of native speakers.26
Garbage translations multiply online like fake news. Native speakers of the languages in question are bypassed as being “too hard to find,” compared with automated methods of vetting that are completely disconnected from real-life communication. While larger and more powerful language communities may be able to hold the bots to account and even make strategic use of them, it is all too easy to imagine [a minority language] being overwhelmed.26
Ross Perlin, Endangered Language Alliance
Uncontrolled and in the hands of tech giants, synthetic Kernewek will outnumber and outmanoeuvre human Kernewek.
DATA SOVEREIGNTY AND COLONIALISM
Indigenous data sovereignty is the right of [an indigenous nation] to govern the collection, ownership, and application of its own data.27
Native Nations Institute
There are, however, indigenous cultures that are working on a more equitable relationship with AI. Tech without the giant requires resources, but it allows communities to retain data sovereignty over the cultural asset that is their language. Te Mana Raraunga, the Māori Data Sovereignty Network, has created a list of principles for the creation, use and sharing of Māori data, prioritising the need to enhance control for current and future Māori.
They raise a key point that should be considered carefully by stewards of linguistic and cultural knowledge: “Data from us, and about us and our resources, are valuable assets. Once control of it is lost, it is difficult to regain.”28 Decisions must not be taken lightly or hastily; we can always say “yes” if we have previously said “no” to a particular dataset’s use, but can never say “no” if we have already said “yes”.
The AI field, like any other space, is occupied by people who are set in their ways and unintentionally have a very colonial perspective.29
Michael Running Wolf, First Languages AI Reality
This is vital in the context of the potential control of Kernewek data by powerful external corporations. Capitalist extractivism has long been a bane on societies in the imperial periphery and our Cornish society is no different, having faced centuries of its wealth and natural resources being stripped and sold by and large for the profit of those outside Cornwall.
The book Indigenous Data Sovereignty and Policy notes that current data relations can be seen as “a continuation of the processes and underlying belief systems of extraction, exploitation, accumulation and dispossession that have been visited on Indigenous populations through historical colonialism.”30 This extractive understanding of information is, they note, not disrupted but rather replicated by paying people for their data.
Ultimately, our language must not lie in outside hands governed by proprietary principles that do not allow us sufficient sovereignty over one of our most valuable natural resources: our language. We must have open data principles, not bow to corporate control. We must steer and steward the use of our data, rather than expose it to use against our interests and for the pockets of big tech.
Rather than approaching language preservation as a technical problem, I think indigenous communities need to be politically empowered, whether that be funding from governments or legal protections to use their languages.31
Dr. Fintan Mallory, Durham University
We must prioritise language-as-community and seek open, equitable and ethical use of our language, heritage and other cultural assets. We must avoid thinking of AI as the magic that it promises and invest in basic research, driven by our own community. Corporations will not save us and, indeed, may do us great harm.
NO CORNISH ON A DEAD PLANET
Global capitalism and governments […] are addicted to ‘free’ market ideology over the wellbeing of communities, people and the planet.32
Cymdeithas yr Iaith Maniffesto 2022
Honestly, most takedowns of AI would have hit this point already. It’s one of the main arguments against Generative AI, but in case you’re not familiar with it, we will briefly look over the main points.
Water used in cooling AI data centers must be drinkable water. AI guzzles this water. The University of California has reported that “global water demand from AI could reach 4.2-6.6 billion cubic meters by 2027. That exceeds 50 percent of the UK’s annual water use in 2023.”33 All this while the Global Commission on the Economics of Water has declared “a rapidly accelerating water crisis” to which Kernewek should not be contributing.34
We have become utterly dependent on private technologies manufactured and controlled by a handful of opaque companies [who] appear mostly indifferent to the social consequences of their activities and only invest minimally if obliged by government regulations to enhance their public image.35
Iker Erdocia, Dublin City University
AI requires vast quantities of hardware at the cost of mining rare earth minerals. These are difficult to extract and purify and come with heavy environmental and social costs. They are often extracted from mines in countries with poorer environmental and labour protections. Reset states that “communities living near these mines, often indigenous or minority groups, regularly face land degradation, water contamination and human rights abuses. Much of this can be directly linked to the AI hardware.”36 When the hardware inevitably cooks and is useless, it is then thrown out as e-waste into poor communities. The potential advancement of Kernewek must not come at the expense of our sister indigenous and minority communities.
Training an also AI requires huge amounts of energy, soon perhaps as much as a small country37 and has an enormous carbon footprint.38 What is clear is that—through water usage, extractive industry, energy consumption and carbon footprint—AI is bad news for the struggling environment of the planet we live on and there is no Cornish on a dead planet.
MAKING AI AN EX-PARROT
Rather than making minority languages more accessible, AI is now creating an ever expanding minefield for students and speakers of those languages to navigate.39
mit technology review
We have heard of the vast improbability of getting AI to be able to mimic Kernewek in light of the costs in data, work, time and technology. We have considered the likely choice of cold negligence or surveillance product and the importance of data sovereignty. We have read about the effects on the livelihoods of Cornish speakers, as well as the the catastrophic costs to the environment and indigenous peoples.
We have learned that linguistic flattening by AI impoverishes its subjects and how AI may decide for us how our language must operate. We have seen the inescapability of language as human and the risks of creating ‘learners’ who cannot learn and ‘speakers’ who cannot speak. We have seen the dangers to reputation and trust for any organisation who would shovel what is seen as ‘slop’.
We have heard why giving in to the juggernaut of AI would be a mistake for Kernewek and how our community does not support our laying down of the shield. Instead, we must fight. We must make Kernewek a space as free of slop as possible, we must educate botlickers into ethical and effective language learning and use, we must avoid second-hand thinking.
We must make our language a no AI zone, a network of reliable humans and their human creations, built on authenticity, community, effort and trust: a Kernewek for the people, of the people and by the people.
KERNEWEK YN-DANN GEVALAV
Mes yn sur y hyllyn ni gwellhe taklow dres termyn? Y fydh res meur a weres a gompanis SK, mes y talvia dhyn. Yn trist, Gabriel Nicholas, kesvroder hwithrans orth an Center for Democracy and Technology, re drovyas pan wrug kompani tek fondya gallosow selyek rag unn yeth, i a omgeslowenha yn ughel hag ena movya yn-rag.7
Kompanis tek bras yw yndella poran: kompanis. Ymons i ena rag gwaynya budh. Y’n gwettha prys, ny wra marghas rewlys gans yethow bras ri kentryn dhe gevarghewi yn gwellhe rag an re byghan.
Oll a’n deknegieth kows, chiow konnyk ha systemow ynterweythres lev usys hedhyw yw an askorrasow a hwithrans kenwerthel. Dhe vos sogh, yth yns i po rag dendyl arghans a’th kedhlow, po gwertha gwara ha gonisyow, po delenwel dha dybyansow. Nyns yw tra vyth a’n SK ma rag an les kemmyn. […] Mar nag eus argyans erbysek krev lowr, na wra gwaytya kompanis bras dhe fyski dhe askorra systemow kows Kembrek, Godhalek po Kernewek.8
Prof. Ian McLoughlin, pennskol kint
Ha mars ervirons bos SK Kernewek aventur a yll gwaynya budh, possybyl yw bos agan studh gweth ages dell via gans forsakyans. Dell lever Dr. Fintan Mallor, an fordh vrassa a waynya budh rag kompanis SK arghesys yn privedh yw kedreylya aga thoulys yn devisyow aspians.9 Drefen bos Kernewek onan a’n yethow boghes y’n RU nag yw aspiadow yn es y’n eur ma, hemm yw peryl kowrek rag gweythresieth Kernewek ha’gan strif a-barth omdhetermyans yn stat a vynn galweythegi dissent.
Ha ni ow tochya Kernewek ha’y savla yn-dann gevalav, gwren ni mires orth an kost denel. My a gellis ow soodh 13 bloodh yn yethow dhe SK kettooth ha dell veu eskorrans Sowsnek hewul lowr dhe askusya sevel orth tyli den. Y’n kas diwirhaval may kevyn SK hag a yll askorra Kernewek da, prag y hwrussa nebonan omankombra ow pe kowser? An tybyans a SK ow tenna oll an bewnans a’m taves ertach ha ni ow kwynnel dhe dreusvewa dell on yw skruthus.
Yn sempel, budh yw gorthenebel orth tus. Hedre vo SK an degen nowydh flamm a vudh, y fydh gorthenebel orth tus. Ha yeth yw hy thus.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Nyns eus styr dhe gesunyansow a lytherennow war skrin heb dewis ha heb mynnas.10
Ross Perlin, Endangered Language Alliance
Kyn nag yw yeth dibarow dhe dhensys, onan a’n rannow chif a vos denel yw. Ny yll bos lehes dhe gedhlow hepken, mes yth yw argerdh sosyel dres eghen.11 Ni oll a wor py mar synthesek y sen skoodhyans prener der SK po fatel yll SK fyllel orth konvedhes arliwyow. Dell gampol Dr. Mallory, “Yeth [yw] neppyth moy kepar hag enev a gemeneth. Ny yllir gwitha hemma yn jynn. Ny yllir assoylya kudyn denel kepar ha yethladhans gans gwel a yeth hag a remov an gerann denel.”12
Ny yll SK konvedhes Kernewek po taves vyth aral. Papynjay chonsus yw: y targan py ger yw gwirhaval wosa an huni kyns.13 Ny yll agan konvedhes. Ny yll mynnes tra vyth. Mar kwra derivas orthis y vos pes da dha weres, gow yw. My a vynn agan kemeneth dhe devi, mes ny wra kans jynn-amontya a yll ‘kewsel Kernewek’ keworra orti. Y hwra unn den—ow tri tybyansow ha govenegow hag ownow ha gwanderyow—ha ny dybav y hwra an jynnys-amontya kernwegorek keworra unn den hogen orth agan kemeneth.
Gwettha, mar kwra, yma dustuni a-dhyworth Microsoft hag a brof y hwra an devnydh a SKDin war oberennow yeth, unweyth an seythen hogen, aperya gallos godhvosel a dhyski, ow ledya orth omworrans lehes gans an desten, gorfydhyans y’n deknegieth ha sleyneth sprallys a assoylya kudynnow yn anserghek.14 Der usya toulys SK dhe ‘dhyski’ Kernewek, possybyl yw ni dhe shyndya gallos dyski an yeth vytholl heb an kroch ma. Ni a wra gul mimyoryon yn le Kernewegoryon.
Ynwedh Perlin a boslev an elven dhenel, ow leverel pan wren ni synsi kemeneth avel kres agan yethow, dell wren, an papynjay chonsus a yll bos klewys kepar ha defolyans.15 Y’n eur ma, my a aswon pan eus nebonan owth usya ‘Kernewek’ SK dhymm. An tybyans ny wrav vy unn jydh godhvos pan eus estren—nebonan a wrussen vy dynerghi mar pe lyver po klass ganses—ow popettya diwawen ow hengerens ha kewsel dresta yw bedhrosus. Yma dhe’n dra an wan dhistowgh a drevesigeth, a berghenegyans pan yllir gwerthveurhe, a bapynjaya pan yllir junya agan kesgan.
Unver yw skolheyk Hawai’i henwys Noah Ha‘alilio Solomon: “Ankensi yw, drefen ni dhe vos kofhes a’n prysyow oll re beu agan gonisogeth ha yeth perghenegys. Ni re beu owth omladh dre dhens hag ewines yn batel gales a-barth dasvewheans yeth.[…] Y hwra pobel krysi bos hemma representyans ewn a’n yeth a Hawai’i.”16
TREST HAG OMGLEWANS AN GEMENETH
Hir re beu an kil-lash gorthjynn ow kovryjyon mes lemmyn yma va ow terri an arenep dell hevel.17
NBC NEWS
Tardh an arvedhennow rag SK y honan (clanker, tinskin, toaster), y askorras (slop, dross, brainrot) ha’y usyoryon (slopper, groksucker, botlicker, second-hand thinker)—keffrys hag erel selys moy yn kler war geryow kas gwir dell ov attes gans aga heworra—a re hwedhel a stons ollgemmyn a wogrys ha divlases war-tu hag an deknegieth ha’y devnydh war an kesrosweyth Sowsnek ha yethow bras erel.18 Kynth yw an stons yn-mysk gwesyon dek ha korforeth hwath gwresek, rag an boblek gemmyn y hwra SK “dos ha bos keschanjyadow gans taklow tamm kawgh.”19
Pella, nyns yw marnas yethow moyhariv gans an gwel negedhek ma a SK avel podrek. Sampel uskis a gampollow media sosyel ha meusi ow tochya SK ha Godhalek Alban gans Professor Lamb a dhiskwedhas fals a 54% negedhek, 33% posedhek ha 13% heptu. (Lamb, 2024) Sentiment an kampol negedhek an moyha talvesys o bos SK dregynnus hag an nessa y talvia dhyn lettya SK rag kestav gans tavosow ertach.
Pyth eson ni ow leverel orth agan diyskynysi? Ny dal agan yeth ha gonisogeth an strivyans personel? Hemm yw martesen fatel wrussen vy y redya, a pen vy i.20
Gorthebydh sondyans Kernewek
Kernewek a baynt aven moy serth, yn arbennik gans dyskoryon ha kowsoryon yowynka ha moy skentel gans tek. Sondyans war Discord ha Whatsapp Kernewek a drovyas bos 65% a grysis y fia SK drog (11.5%) po pur dhrog (53%) rag an yeth. Pan veu govynnys pyth a dal bos gorthyp an gemeneth orth SK, 46% a leveris y kodh y hedhi ha 27% y woheles, gans an dus moy ha 60 bloodh hepken ow tybi y kodh oberi ganso.20
31% a worthebydhyon an sondyans a leveris y hwrussa an devnydh a SK yn Kernewek aga fellhe a’n yeth, hag ynwedh 54% a leveris y fiens i pellhes yn krev ha 23% pellhes tamm a by kowethas, asnodh po dyskador pynag ow tevnydhya SK.
An gorthyp a’n re a leveris bos aga godhvos a SK po “konnyk” po “da” o dampnus yn arbennik. Pubonan y’n bagas ma a worthebis y fia SK dregynnus rag Kernewek, y hwrussa an devnydh a SK gans pennfenten aga fellhe a’n bennfenten na yn krev hag y kodh dhyn hedhi an devnydh a SK rag Kernewek.
HONANIETH, LELDER HA DIVERSETH
Nyns esa Aristotelis Ioannis Paschalidis, ow skrifa a-barth UNESCO, ow kewsel yn komparek a-dro dhe yethow lyharivhes pan wrug ev y wovyn, mes an govyn a dhassen yn kreffa ragon: “Pygemmys koll a honanieth a vynnir sakrifia rag effeythuster?”21
Honanieth yw a’n moyha bri rag Kernewegoryon. Studhyans Ute Wimmer Reversing Language Shift: the Case of Cornish a henow “gweythres [an yeth] avel arwodh a honanieth kenedhlek” avel an nessa ughella skila (66%**) yn-mysk kowsoryon ha dyskoryon, fethys gans gonisogeth Kernow (80%) hepken.22 Yth havalsa hemma bos acheson solempnyans, mes pan vo SK keworrys, y teu ha bos peryl. Vincent Koc a Hyperlink a lever y hyll SK “kevri dre wall orth an gwannheans a yeth ha honanieth wonisogethel”.23
Ev a aswon ynwedh y hallsa awtomategi dyski po dinythi yeth “lehe an rychedh ha lelder hag a dheu a gowsoryon dhenel neb a dheg istoriow gonisogethel y’ga hows”. Yn hwir, peswar studhyans gwrys gans Pennskol Kaliforni Soth re dhiskwedhas bos devnydhya PYB dhe weres gans skrifa “kelmys orth dyfygyansow nosedhek yn diverseth yethel hag y hyll mellya gans an konvedhes brysoniethel ha kowethasel yw proviys gans yeth.”24
Ha hemm yw yn Sowsnek, onan a’n yethow an ryccha ha brassa y’n bys. Dismyk an effeyth war yeth byghanna kepar ha Kernewek—gans le a dhogvennans, le a gedhlow, sel kowsoryon munys hag ogas hag arghans mann—ha war y lies orgraf hag eghen yeth. Yn arbennik yn gettesten Kernewek, seulabrys yma kowsoryon Diwedhes ow strivya dhe vos gwelys avel vas gans gwartheyvans Kres. A dybyn y hwor SK an dyffrans? Heb preder, y hwra po kemyska puptra warbarth, ow sowdheni pubonan, po devnydhya Kres dhe fetha Diwedhes.
An gwruthyl a dhalgh herdhys gans SK Dinythus, dre favera yethow savonegys, a argyl an vansyans a rannyethow ranndiryel.25
Kresen woramontyorieth Barcelona
Nyns yw eghennow hepken yn peryl; SK a wodros beudhi Kernewek yn tien. Akordys yw Perlin y hallsa an platheans yethel a hwarva dres kansbledhynnyow yn Sowsnek hwarvos dres nos yn yeth lyharivhes gans SK orth an fronnow—dell via, ow pos gallosek a bassya Kernewek denel heb assay. Ev a venek prederow yn kever PYB ow rewi yeth yn hy le ha hogen ow settya pyth yw an styr a wodhvos an yeth, yn arbennik gans niverow munys a gowsoryon deythyek.26
Treylyansow leun a atal a liesha warlinen kepar ha nowodhow fug. Kowsoryon deythyek a’n yethow ma yw passyes avel bos “re gales dhe drovya”, komparys orth fordhow awtomategys a surheans kwalita hag yw disjunys yn tien a geskomunyans y’n bys gwir. Kynth yw possybyl rag kemenethow yeth brassa ha moy gallosek synsi an bottys ma dhe akont ha’ga devnydhya yn stratejek hogen, re es yw dismygi [yeth lyhariv] ow pos reverthys.26
Ross Perlin, Endangered Language Alliance
Heb kontrol hag yn diwla an gewri deknegieth, Kernewek synthesek a wra gornivera ha gorthrabellhe Kernewek denel.
SOVRANEDH KEDHLOW HA KOLONEGIETH
Sovranedh kedhlow teythyek yw an gwir gans [kenedhel teythyek] a woverna an kuntel, perghenogeth ha gweytha a’y hedhlow hy honan.27
Native Nations Institute
Byttegyns, yma gonisogethow teythyek hag usi owth oberi war geskowethyans moy ewnhynsek gans SK. Tek heb an kowr a res asnodhow, mes y as kemenethow gwitha sovranedh kedhlow war an gerthen wonisogethel hag yw aga yeth. Te Mana Raraunga, Rosweyth Sovranedh Kedhlow Māori, re wrug rol a bennrewlys rag an gwruthyl, devnydhya ha kevrenna a gedhlow Māori, ow ragwirhe an edhom a grefhe maystri rag Māori a-lemmyn hag a dheu.
I a venek poynt posek hag a dalvia bos konsidrys gans rach gans stywards a skians yethel ha gonisogethel: “Kedhlow ahanan, a-dro dhyn ha’gan asnodhow, yw kerthennow a bris. Pan vo maystri kellys, kales yw y dhaskemeres.”28 Ny dal gul erviransow yn skav po yn uskis; y hyllyn pupprys leverel “ea” mar kwrussyn leverel “na” kyns orth us sett kedhlow, mes ny yllyn nevra leverel “na” mar kwrussyn leverel “ea” seulabrys.
An desten SK, kepar ha pub le aral, yw leun a dus hag yw settys y’ga maneryow ha gans gwel pur drevesigel yn tidowl.29
Michael Running Wolf, First Languages AI Reality
Hemm yw pur bosek y’n gettesten a’n kontrol possybyl a gedhlow Kernewek gans korforethow gallosek a-ves. Estenegieth jatelydhek re beu molleth war gowethasow y’n amal emperourethek ha nyns yw kowethas Kernewek dyffrans, wosa enebi kansvledhynnyow a’y rychys hag asnodhow naturek ow pos destryppys ha gwerthys dre vras gans budh tus yn-mes a Gernow.
An lyver henwys Indigenous Data Sovereignty and Policy a verk lemmyn y hyllir gweles perthynyansow kedhlow avel “pesyans a’n argerdhow ha systemow-krysi isworwedhek a estennans, drogusyans, kuntellyans ha diberghenogeth re beu gwrys war boblansow Teythyek dres trevesigeth istorek.”30 An konvedhes estennek ma a gedhlow yw, dell verkons, hevelebys a-der goderrys gans tyli pobel rag aga hedhlow.
Wostiwedh, res yw ma na vo agan yeth gorrys yn diwla a-ves routys gans pennrewlys perghenogel na as dhyn sovranedh lowr a onan a’gan asnodhow naturel an moyha posek: agan yeth. Res yw dhyn kavos pennrewlys kedhlow ygor, a-der plegya orth kontrol korforethel. Res yw dhyn lewya ha gidya an devnydh a’gan kedhlow, a-der y usya erbynn agan lesow ha rag pocketys tek bras.
A-der drehedhes an arwithans a davosow avel kudyn teknegiethel, my a dyb bos res dhe gemenethow teythyek bos reythhes yn politek, po der arghasans a wovernansow po dre dhifresyansow laghel dhe dhevnydhya aga yethow.31
Dr. Fintan Mallory, Pennskol Durham
Res yw dhyn ragwirhe yeth-avel-kemeneth ha hwilas devnydh ygor, ewnhynsek hag ethegel a’gan kerthennow yeth, ertach ha gonisogethel. Res yw dhyn goheles tybi a SK avel an hus mayth ambos ha kevarghewi yn hwithrans selyek, lewys gans agan kemeneth. Ny wra korforethow agan selwel ha, hogen, i a yll agan shyndya.
NYNS EUS KERNEWEK WAR BLANET MAROW
Governansow ha kevalav ollvysel […] yw omres dhe ideologieth marghas ‘rydh’ moy es dell yns omres dhe sewena kemenethow, pobel ha’n planet.32
Cymdeithas yr Iaith Maniffesto 2022
An brassa rann a vreusyansow a SK a wrussa meneges hemma seulabrys. Onan a’n argyansow brassa yw erbynn SK Dinythus, mes rag own bos ankoth dhis, ni a wra mires orth an chif boyntys.
Res yw bos evadow an dowr goyeynhe pub kresen kedhlow SK. Y kollenk an dowr ma. Pennskol Kaliforni re dherivas “y hallsa demond dowr ollvysel SK hedhes 4.2-6.6 bilvil metrow kubek erbynn 2027. Henn yw moy es 50 kansran a us dowr bledhynnyek an RU yn 2023.”33 Y kettermyn, an Desedhek Ollvysel Erbysieth Dowr a dheklaryas “barras dowr ow tardha yn uskis” ma na dal Kernewek kevri dhodho.34
Ni re dheuth ha bos yn hwir omres dhe deknegiethow privedh gwrys ha kontrolys gans dornas a gompanis diskler [hag] a hevel bos mygyl dre vras orth an sewyansow sosyel a’ga gwriansow ha kevri yn ispoyntel marnas mars yns i konstrinys gans rewlys an wovernans dhe wellhe aga imach poblek.35
Iker Erdocia, Pennskol Sita Dulyn
Yma edhom dhe SK a vynsow kowrek a galesweyth orth kost palas monyow tanow. Kales yw estenna ha purhe an re ma hag yma kostow kerghynedhel ha sosyel poos. Estennys yns i yn fenowgh a hwelyow yn powyow gans difresyansow lakka rag lavur ha’n kerghynnedh. Reset a lever “yn fenowgh y hwra kemenethow yw trigys yn ogas dhe’n hwelyow, yn fenowgh bagasow lyhariv po teythyek, enebi gwethheans an tir, defolyans an dowr hag abusyans gwiryow denel. Meur a hemma a yll bos kelmys yn tidro orth an galesweyth SK.”36 Pan yw an galesweyth kegys yn sertan hag euver, ena tewlys yw avel e-wast yn kemenethow boghosek. Res yw nyns yw an avonsyans possybyl a Gernewek orth kost agan kemenethow hwor lyhariv ha teythyek.
Ynwedh res yw myns hujes a nerth rag trenya SK, yn skon martesen an keth myns ha pow byghan37 hag yma ol troos karbon kowrek.38 Kler yw—der usadow dowr, diwysyans estennek, konsumyans nerth hag ol troos karbon—bos SK yeyn nowodhow rag kerghynnedh ow strivya a’n planet mayth on ni trigys warnodho ha nyns eus Kernewek war blanet marow.
GUL DHE SK BOS EKS-PAPYNJAY
A-der gul dhe yethow lyhariv bos moy hedhadow, lemmyn yma SK ow kwruthyl tardhek pupprys owth omlesa rag studhyoryon ha kowsoryon a’n yethow ma dhe wolya.39
mit technology review
Ni re glewas a’n anwirhevelepter efan a wul dhe SK gallos mimya Kernewek yn golow an kostys yn kedhlow, ober, termyn ha teknegieth. Ni re gonsidras lycklod an dewisynter dispresyans yeyn po askorras-aspia ha’n posekter a sovranedh kedhlow. Ni re redyas a-dro dhe’n effeythyow war vewnansow Kernewegoryon, keffrys ha’n kostys katastrofek rag an kerghynnedh ha poblow teythyek.
Ni re dhyskas y hwra platheans yethel gans SK boghosekhe y destennow ha fatel yll SK martesen ervira a’gan parth fatel godh dh’agan yeth oberi. Ni re welas an anwoheladewder a yeth avel denel ha’n peryllyow a wul ‘dyskoryon’ na yll dyski ha ‘kowsoryon’ na yll kewsel. Ni re welas an peryllyow orth bri ha fydhyans rag kowethasow a wrussa palas an pyth hag yw gwelys avel ‘skomblans’.
Ni re glewas prag y fia omblegya orth an jagganat a SK error rag Kernewek ha dell na vynn agan kemeneth skoodhya gorra an skoos a-dhyworthyn. Yn y le, res yw dhyn batalyas. Res yw dhyn gul dhe Gernewek bos spas mar rydh a skomblans dell yll bos, res yw adhyski orth botlapyoryon yn dyski ha devnydh yeth yn ethegel hag yn effeythus, res yw goheles tybi wortaswerth.
Res yw dhyn gul dh’agan yeth bos parth heb SK, rosweyth a dus fydhyadow ha’ga gwriansow denel, drehevys war lelder, kemeneth, assay ha trest: Kernewek hag yw a-barth an bobel, a’n bobel ha gans an bobel.
Niwlen Ster
Notennow
* A prime example is the laughably-unaffordable restaurant RenMor, which The Headland Hotel thinks is a version of “Re’n Mor”, which they believe means “by the sea” as in “next to the sea” but actually means “by the sea!” like saying “by Zeus!”. This is both hilarious and enraging.
** A figure perhaps lower than it should be if you consider that many of the “emotional motives” which were not counted in this category, such as “I’m Cornish, what better reason do you need?”, do also refer to identity.
FENTENNOW
1. Judah, J. (2025) How AI and Wikipedia have sent vulnerable languages into a doom spiral, MIT Technology Review.
2. Ackermann, A. (2023) When AI doesn’t speak your language, Coda.
3. Crichton, D. (2024) AI and the Death of Human Languages, Lux.
4. Lamb, W. (2024). Could Artificial Intelligence save Scottish Gaelic?, The University of Edinburgh.
5. Dencik, L. (/2025) AI Inequalities: Minority Languages, TUC Cymru.
6. Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Microsoft Research, India. (2020). The State and Fate of Linguistic Diversity and Inclusion in the NLP World. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
7. Ackermann, A. (op cit)
8. McLoughlin, I. (2018) How to teach AI to speak Welsh (and other minority languages), The Conversation.
9. Mallory, F. (2025) RISE UP Panel Discussion & Q&A: What AI Can and Cannot Do for Minoritised Languages, YouTube.
10. Perlin, R. (2024) AI Won’t Protect Endangered Languages, The Dial.
11. RISE UP (2025) #4 RISE UP Event Summary: What AI Can and Cannot Do For Minoritised Languages, RISE UP.
12. Mallory, F. (2024) European Day of Languages: Will lesser spoken languages soon only be kept alive by AI technology? Durham University.
13. Bender, E., Gebru, T., McMillan-Major, A., & Mitchell, M. (2021) On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
14. Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025) The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers. Microsoft.
15. Perlin, R. (op cit)
16. Judah, J. (op cit)
17. Abbruzzese, J., & Wile, R. (2025) Is an AI backlash brewing? What ‘clanker’ says about growing frustrations with emerging tech, NBC News.
18. Webster, K. (2025) Why Using ChatGPT at Work Could Hurt Your Reputation, Inc. Magazine.
19. Herrman, J. (2024) Is That AI? Or Does It Just Suck?, Intelligencer.
20. Wilson, L. (2025) Skians Kreftus ha Kernewek/Artificial Intelligence and Cornish
21. Paschalidis, A. I. (2025) AI and the great linguistic flattening, UNESCO.
22. Wimmer, U. (2010). Reversing Language Shift: the Case of Cornish. Cornish Language Board, p. 113
23. Koc, V. (2025) Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges, ResearchGate.
24. Sourati, Z., Karimi-Malekabadi, F., & Ozcan, M. (2025) The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Models, ResearchGate.
25. Melero, M. (2024) The Future of Language (and Cultural) Diversity in the Age of AI, CLARIN.
26. Perlin, R. (op cit)
27. Russo Carroll, S., Rodriguez Lonebear, D., & Martinez, A. (2017). Data Governance for Native Nation Rebuilding, Native Nations Institute.
28. Te Mana Raraunga. (2018). Frequently Asked Questions, Te Mana Raraunga.
29. Ackermann, A. (op cit)
30. Walter, M., Kukutai, T., Carroll, S. R., & Rodriguez-Lonebear, D. (Eds.). (2020). Indigenous Data Sovereignty and Policy. Taylor & Francis, p. 24
31. Mallory, F. (op cit)
32. Cymdeithas yr Iaith (2022) Cymru Rydd, Cymru Werdd, Cymru Gymraeg., p. 27
33. O’Sullivan, L. (2025). How AI’s Failure on Linguistic Diversity is Deepening Global Inequality, RESET – Digital for Good.
34. Harvey, F. (2024). Global water crisis leaves half of world food production at risk in next 25 years, The Guardian.
35. Erdocia, I., Migge, B., & Schneider, B. (2024). Language is not a data set—Why overcoming ideologies of dataism is more important than ever in the age of AI. Journal of Sociolinguistics, 28(5), p. 23
36. O’Sullivan, L. (op cit)
37. Erdenesanaa, D. (2023) A.I. Could Soon Need as Much Electricity as an Entire Country, The New York Times
38. Heikkilä, M. (2022) We’re getting a better idea of AI’s true carbon footprint, MIT Technology Review.
39. Judah, J. (op cit)#4 #AI #ArtificialIntelligence #Breus #Cornish #Cornwall #data #generativeAI #history #jynn #kedhlow #Kernewek #Kernow #Kernowek #LLM #machine #PYB #SK #SKDinythus #SkiansKreftus #Sordya
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Turning Saffron into Slop – Treylya Safran yn Skomblans
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
Note: Artificial Intelligence (AI) has come to be synonymous with Generative AI (GenAI) and with Large Language Models (LLMs), such as ChatGPT, in common parlance. Unless explicitly stated, I use the terms interchangeably.
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow*, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
LOW-RESOURCES AND LINGUISTIC TYPOLOGY
Simply adding a language to an AI model leads to a spike in poor-quality articles, drowning out quality writing by humans. AI has “industrialized the acts of destruction—which affect vulnerable languages most, since AI translations are typically far less reliable for them.”1 Wikipedia editors from varied languages evidence that machine translation tools have made it easier than ever before to create shoddy articles in minoritised languages, causing massive damage in minutes. AI leads to non-speakers producing much longer, truthier rubbish, Sámi computational linguistics expert Trond Trosterud notes: “the problem [is] that they are armed with Google Translate. Earlier they were armed only with dictionaries.”1
Kernewek, like all but 60 of the world’s roughly 7,000 languages, is designated “low-resource”, meaning it lacks sufficient data to train a machine.2 It is tempting, therefore, to assume that the solution is to provide more data. However, training an LLM requires petabytes of text, audio and video—manually categorised and in a machine-readable format—a vast trove that Kernewek simply does not have.3 Professor Will Lamb, Chair of Gaelic Ethnology and Linguistics at Edinburgh University, speaks of “millions of work hours devoted to just one aspect” of a working AI.4
Even if ChatGPT is trained on another language than English, the time and labour required may make it largely unviable. Current assessments of the performance of ChatGPT for different languages have shown that it performs worse in all tasks.5
Prof. Lina Dencik, Data Justice Lab
Furthermore, the amount of data and work is not the only barrier; at issue is the nature of the language itself. Microsoft has found that languages such as Breton—and thus Kernewek—cause a high rate of errors distinct from the size of their dataset, due to grammatical features, such as mutation, not present in well-sourced languages. As such, they remain poor without significant additional work.6 Essentially, simply adding more Kernewek may not help. Thus, engaging with AI is, for Kernewek, to tie ourselves to slop.
Noten: Skians Kreftus (SK) re dheuth ha bos kesstyr gans SK Dinythus (SKDin) ha gans Patronyow Yeth Bras (PYB), kepar ha ChatGPT, yn lavar kemmyn. Marnas bos menegys yn kler, my a us an termys yn keschanjyadow.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow*, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
ASNODHOW ISL HA TIPOLOGIETH YETHEL
Keworra yeth yn sempel orth patron SK a led orth spik yn erthyglow drog aga kwalita, ow peudhi skrif a gwalita gans tus. SK re wrug “diwysyansegi an aktys diswrians—hag a nas yethow goliadow an moyha, drefen bos treylyansow SK lieskweyth le lel yn tipek ragdha.”1 Golegydhyon Wikipedia a yethow divers a re dustuni re wrug medhelweyth-treylya y wul bos esya dell veu bythkweth kyns gwruthyl erthyglow pilyek yn yethow lyharivhes, ow kawsya damach kowrek yn mynysennow. SK a led orth digowsoryon owth askorra atal lieskweyth hirra ha gwirekka, konnyk yethonieth reknansek Sámi Trond Trosterud a not: “an kudyn [yw] aga bos ervys gans Google Translate. A-varra nyns ens ervys marnas gans gerlyvrow.”1
Kernewek, kepar hag oll marnas 60 a ogas lowr 7,000 yeth a’n bys, yw klassys avel “isel y asnodhow”, ow styrya nag eus dhodho kedhlow lowr dhe drenya jynn.2 Rakhenna, dynyek yw desevos bos an assoylyans profya moy a gedhlow. Byttegyns, res yw petavaytys a dekst, son ha gwydhyow—klassys dre leuv hag yn furvas redyadow gans jynn— dhe drenya PYB, tresorva efan nag eus dhe Gernewek yn sempel.3 Y kews Professor Will Lamb, Kaderyer Ethnologieth ha Yethonieth Wodhalek orth Pennskol Karedin, a “vilvilyow a ourys ober sakrys orth unn wedh hepken” a SK owth oberi.4
Hogen mars yw ChatGPT trenys war yeth a-der Sowsnek, an termyn hag ober yw res a styr y vos martesen anhewul dre vras. Arvreusyansow a-lemmyn a berformyans a ChatGPT rag yethow dyffrans re dhiskwedhas y perform gweth yn oberennow oll.5
Prof. Lina Dencik, Data Justice Lab
Pella, nyns yw an myns a gedhlow hag ober an unsel lett; a vern yw natur an yeth y honan. Microsoft re drovyas y kaws yethow kepar ha Bretonek—hag ytho Kernewek—kevradh ughel a wallow diblans a vraster aga sett kedhlow, drefen nasyow gramasek, kepar ha treylyansow, nag usi kevys yn yethow ughel aga asnodhow. Yndella, i a bes orth bos drog heb meur a ober keworransel.6 Yn essensek, possybyl yw ny wra keworra moy a Gernewek yn sempel gweres. Yndelma, oberi gans SK yw, rag Kernewek, omgelmi orth skomblans.
CORNISH UNDER CAPITALISM
But surely we can improve things over time? It will take a lot of help from AI companies, but it will be worth it. Sadly, Gabriel Nicholas, a research fellow at the Center for Democracy and Technology, has found that once a tech company has established basic capabilities for a language, they pat themselves on the back and move on.7
Big tech companies are just that: companies. They exist to make a profit. Unfortunately, a market dominated by big languages gives them no incentive to invest in improvements for small ones.
All of the speech technology, smart homes and voice interaction systems used today are the products of commercial research. To put it bluntly, they exist to either make money from your data, to sell you more goods and services, or to influence your thinking. None of this AI exists for the public good. […] Unless there is a strong enough economic argument, don’t expect big companies to rush into producing Welsh, Gaelic or Cornish speech systems.8
Prof. Ian McLoughlin, University of Kent
Should they decide that a Kernewek AI is a viable profit-making enterprise, our situation may even be worse than abandonment. As Dr. Fintan Mallory remarks, the dominant means of profit for privately-funded AI enterprises is to convert their tools into surveillance devices.9 As Kernewek is currently one of the UK’s only languages which is not currently easily surveillable, this poses a huge risk to Kernewek activism and the fight for self-determination in a state that seeks to criminalise dissent.
While we’re on the subject of Kernewek and its position under capitalism, let’s consider the human cost. I lost my 13-year career in language to AI as soon as English output became viable enough to excuse not paying a human. In the unlikely instance that we achieve an AI that can produce quality Kernewek, why would anyone bother paying speakers? The idea of AI sucking all the life out of my heritage language when we are struggling to survive as-is is appalling.
Simply put, profit is antithetical to people. While AI is the new favourite toy of profit, it will be antithetical to people. And a language is its people.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Combinations of characters on a screen mean nothing without agency and intention.10
Ross Perlin, Endangered Language Alliance
While language is not unique to humans, it is one of the chief parts of being human. It cannot be reduced to mere data, but is a highly social process.11 We all know how synthetic customer support via robot sounds or how AI fails to pick up nuance. As Dr. Mallory comments, “Language [is] something more like the soul of a community. You can’t store this in a machine. You can’t solve a human problem like linguicide with a view of language that removes the human component.”12
AI cannot comprehend Kernewek or any other language. It is a stochastic parrot: predicting what word is likely to follow the previous one.13 It cannot understand us. It cannot intend anything. If it tells you it feels delighted to help you, it is lying. I want our community to grow, but one hundred ‘Cornish-speaking’ computers do not add to it. One human does—bringing ideas and hopes and fears and foibles—and I do not think the Kernewek ‘speaking’ computers will add even one human to our community.
Worse, if it does, there is evidence from Microsoft to suggest that the use of GenAI on language tasks, even once a week, impairs cognitive ability to learn, leading to decreased engagement with the topic, overreliance on the technology and hobbled skills in independent problem-solving.14 By using AI tools to ‘teach’ a learner Kernewek, we may in fact be impairing their ability to learn the language at all without this crutch. We will make regurgitators in place of speakers.
Perlin also emphasises the human element, saying that when we hold community central to our languages, as we do, the stochastic parrot can feel like a violation.15 At the moment, I can tell when someone is using AI ‘Kernewek’ to me. The idea that one day I will not know when an outsider—someone I would welcome if they took up a book or a class—is puppeting my ancestors’ jaws and speaking through them is ghoulish. It has the instant sting of colonialism, of appropriation when one could appreciate, of parroting when one could join our chorus.
Hawai’ian scholar Ha‘alilio Solomon agrees: “It is painful, because it reminds us of all the times that our culture and language has been appropriated. We have been fighting tooth and nail in an uphill climb for language revitalization.[…] People are going to think that this is an accurate representation of the Hawaiian language.”16
TRUST AND COMMUNITY FEELING
The anti-machine backlash has long been simmering but is now seemingly breaking to the surface.17
NBC NEWS
The explosion of insults for AI itself (clanker, tinskin, toaster), its output (slop, dross, brainrot) and its users (slopper, groksucker, botlicker, second-hand thinker)—as well as others more clearly based on real-world slurs than I am comfortable to include—tells a tale of the general attitude of distrust and disgust towards the technology and its use on anglophone and other majority language internet.18 While the attitude among tech bros and corporates remains bombastic, for the general public AI is “becoming interchangeable with things that sort of suck.”19
Further, it’s not just majority languages with this negative view of AI as taint. A quick sampling of social media comments and likes regarding AI and Scottish Gaelic by Professor Lamb showed a split of 54% negative, 33% positive and 13% neutral. (Lamb, 2024) The sentiment of the top-rated negative comment was that AI is harmful and the second-highest that AI should be kept away from heritage languages.
What are we telling our descendants? That our language and culture isn’t worth the personal effort? That’s how I might read it, if I were them.20
Kernewek survey respondent
Kernewek paints an even starker picture, especially among younger and more technologically-savvy learners and speakers. A survey on Cornish Discord and Whatsapp found that 65% felt AI would be bad (11.5%) or very bad (53%) for the language. When asked what the community response should be to AI, 46% said we should prevent it and 27% avoid it, with only over-60s thinking that we should work with it.20
31% of respondents said using AI in Kernewek would cause them to feel estranged from the language, while 54% said that they would feel strongly estranged and 23% a little estranged from any organisation, resource or teacher using AI.
The response from those who gave their knowledge of AI as either “expert” or “good” was particularly damning. Everyone in this group responded that AI would be harmful for the language, that the use of AI would estrange them from a source strongly and that we should prevent the use of AI for Kernewek.
IDENTITY, AUTHENTICITY AND DIVERSITY
Aristotelis Ioannis Paschalidis, writing for UNESCO, was not speaking specifically about minoritised languages when he asked this, but the question resonates even more strongly for us: “How much loss of identity is one willing to sacrifice for efficiency?”21
Identity is of paramount importance to Kernewek speakers. Ute Wimmer’s study Reversing Language Shift: the Case of Cornish identified the language’s “function as a symbol of national identity” as the second highest motive (66%**) among speakers and learners, beaten only by Cornish culture (80%).22 This would seem cause for celebration, but when AI is added to the mix, it becomes a risk. Vincent Koc of Hyperlink states that AI can “inadvertently contribute to the dilution of language and cultural identity.”23
He also identifies that automating language learning or generation “may diminish the richness and authenticity that comes from human speakers who carry cultural histories in their speech.” Indeed, four studies by the University of Southern California have shown that using LLMs to assist writing “is linked to notable declines in linguistic diversity and may interfere with the societal and psychological insights language provides.”24
This is in English, one of the richest and largest languages in the world. Imagine the possible impact on a smaller language like Kernewek—with less documentation, less data, a tiny speakerbase and basically no money—and on its many language varieties and orthographies. Particular to the Kernewek context, Late speakers are already struggling to be seen as valid under the dominance of Middle. Do we think AI knows the difference? Thoughtlessly, it will either mix everything together, confusing everyone, or it will use Middle to overwhelm Late.
Generative AI-driven content creation, by favoring standardized languages, risks the disappearance of regional dialects.25
Barcelona supercomputing Center ….
Not only are varieties at risk; AI threatens to drown Kernewek as a whole. Perlin agrees that the linguistic flattening that occurred over centuries in English could manifest overnight in a minoritised language with AI at the helm—as it would be, being able to effortlessly outstrip human Kernewek. He raises concerns of LLMs freezing a language in place and even defining what it means to know the language, especially with low numbers of native speakers.26
Garbage translations multiply online like fake news. Native speakers of the languages in question are bypassed as being “too hard to find,” compared with automated methods of vetting that are completely disconnected from real-life communication. While larger and more powerful language communities may be able to hold the bots to account and even make strategic use of them, it is all too easy to imagine [a minority language] being overwhelmed.26
Ross Perlin, Endangered Language Alliance
Uncontrolled and in the hands of tech giants, synthetic Kernewek will outnumber and outmanoeuvre human Kernewek.
DATA SOVEREIGNTY AND COLONIALISM
Indigenous data sovereignty is the right of [an indigenous nation] to govern the collection, ownership, and application of its own data.27
Native Nations Institute
There are, however, indigenous cultures that are working on a more equitable relationship with AI. Tech without the giant requires resources, but it allows communities to retain data sovereignty over the cultural asset that is their language. Te Mana Raraunga, the Māori Data Sovereignty Network, has created a list of principles for the creation, use and sharing of Māori data, prioritising the need to enhance control for current and future Māori.
They raise a key point that should be considered carefully by stewards of linguistic and cultural knowledge: “Data from us, and about us and our resources, are valuable assets. Once control of it is lost, it is difficult to regain.”28 Decisions must not be taken lightly or hastily; we can always say “yes” if we have previously said “no” to a particular dataset’s use, but can never say “no” if we have already said “yes”.
The AI field, like any other space, is occupied by people who are set in their ways and unintentionally have a very colonial perspective.29
Michael Running Wolf, First Languages AI Reality
This is vital in the context of the potential control of Kernewek data by powerful external corporations. Capitalist extractivism has long been a bane on societies in the imperial periphery and our Cornish society is no different, having faced centuries of its wealth and natural resources being stripped and sold by and large for the profit of those outside Cornwall.
The book Indigenous Data Sovereignty and Policy notes that current data relations can be seen as “a continuation of the processes and underlying belief systems of extraction, exploitation, accumulation and dispossession that have been visited on Indigenous populations through historical colonialism.”30 This extractive understanding of information is, they note, not disrupted but rather replicated by paying people for their data.
Ultimately, our language must not lie in outside hands governed by proprietary principles that do not allow us sufficient sovereignty over one of our most valuable natural resources: our language. We must have open data principles, not bow to corporate control. We must steer and steward the use of our data, rather than expose it to use against our interests and for the pockets of big tech.
Rather than approaching language preservation as a technical problem, I think indigenous communities need to be politically empowered, whether that be funding from governments or legal protections to use their languages.31
Dr. Fintan Mallory, Durham University
We must prioritise language-as-community and seek open, equitable and ethical use of our language, heritage and other cultural assets. We must avoid thinking of AI as the magic that it promises and invest in basic research, driven by our own community. Corporations will not save us and, indeed, may do us great harm.
NO CORNISH ON A DEAD PLANET
Global capitalism and governments […] are addicted to ‘free’ market ideology over the wellbeing of communities, people and the planet.32
Cymdeithas yr Iaith Maniffesto 2022
Honestly, most takedowns of AI would have hit this point already. It’s one of the main arguments against Generative AI, but in case you’re not familiar with it, we will briefly look over the main points.
Water used in cooling AI data centers must be drinkable water. AI guzzles this water. The University of California has reported that “global water demand from AI could reach 4.2-6.6 billion cubic meters by 2027. That exceeds 50 percent of the UK’s annual water use in 2023.”33 All this while the Global Commission on the Economics of Water has declared “a rapidly accelerating water crisis” to which Kernewek should not be contributing.34
We have become utterly dependent on private technologies manufactured and controlled by a handful of opaque companies [who] appear mostly indifferent to the social consequences of their activities and only invest minimally if obliged by government regulations to enhance their public image.35
Iker Erdocia, Dublin City University
AI requires vast quantities of hardware at the cost of mining rare earth minerals. These are difficult to extract and purify and come with heavy environmental and social costs. They are often extracted from mines in countries with poorer environmental and labour protections. Reset states that “communities living near these mines, often indigenous or minority groups, regularly face land degradation, water contamination and human rights abuses. Much of this can be directly linked to the AI hardware.”36 When the hardware inevitably cooks and is useless, it is then thrown out as e-waste into poor communities. The potential advancement of Kernewek must not come at the expense of our sister indigenous and minority communities.
Training an also AI requires huge amounts of energy, soon perhaps as much as a small country37 and has an enormous carbon footprint.38 What is clear is that—through water usage, extractive industry, energy consumption and carbon footprint—AI is bad news for the struggling environment of the planet we live on and there is no Cornish on a dead planet.
MAKING AI AN EX-PARROT
Rather than making minority languages more accessible, AI is now creating an ever expanding minefield for students and speakers of those languages to navigate.39
mit technology review
We have heard of the vast improbability of getting AI to be able to mimic Kernewek in light of the costs in data, work, time and technology. We have considered the likely choice of cold negligence or surveillance product and the importance of data sovereignty. We have read about the effects on the livelihoods of Cornish speakers, as well as the the catastrophic costs to the environment and indigenous peoples.
We have learned that linguistic flattening by AI impoverishes its subjects and how AI may decide for us how our language must operate. We have seen the inescapability of language as human and the risks of creating ‘learners’ who cannot learn and ‘speakers’ who cannot speak. We have seen the dangers to reputation and trust for any organisation who would shovel what is seen as ‘slop’.
We have heard why giving in to the juggernaut of AI would be a mistake for Kernewek and how our community does not support our laying down of the shield. Instead, we must fight. We must make Kernewek a space as free of slop as possible, we must educate botlickers into ethical and effective language learning and use, we must avoid second-hand thinking.
We must make our language a no AI zone, a network of reliable humans and their human creations, built on authenticity, community, effort and trust: a Kernewek for the people, of the people and by the people.
KERNEWEK YN-DANN GEVALAV
Mes yn sur y hyllyn ni gwellhe taklow dres termyn? Y fydh res meur a weres a gompanis SK, mes y talvia dhyn. Yn trist, Gabriel Nicholas, kesvroder hwithrans orth an Center for Democracy and Technology, re drovyas pan wrug kompani tek fondya gallosow selyek rag unn yeth, i a omgeslowenha yn ughel hag ena movya yn-rag.7
Kompanis tek bras yw yndella poran: kompanis. Ymons i ena rag gwaynya budh. Y’n gwettha prys, ny wra marghas rewlys gans yethow bras ri kentryn dhe gevarghewi yn gwellhe rag an re byghan.
Oll a’n deknegieth kows, chiow konnyk ha systemow ynterweythres lev usys hedhyw yw an askorrasow a hwithrans kenwerthel. Dhe vos sogh, yth yns i po rag dendyl arghans a’th kedhlow, po gwertha gwara ha gonisyow, po delenwel dha dybyansow. Nyns yw tra vyth a’n SK ma rag an les kemmyn. […] Mar nag eus argyans erbysek krev lowr, na wra gwaytya kompanis bras dhe fyski dhe askorra systemow kows Kembrek, Godhalek po Kernewek.8
Prof. Ian McLoughlin, pennskol kint
Ha mars ervirons bos SK Kernewek aventur a yll gwaynya budh, possybyl yw bos agan studh gweth ages dell via gans forsakyans. Dell lever Dr. Fintan Mallor, an fordh vrassa a waynya budh rag kompanis SK arghesys yn privedh yw kedreylya aga thoulys yn devisyow aspians.9 Drefen bos Kernewek onan a’n yethow boghes y’n RU nag yw aspiadow yn es y’n eur ma, hemm yw peryl kowrek rag gweythresieth Kernewek ha’gan strif a-barth omdhetermyans yn stat a vynn galweythegi dissent.
Ha ni ow tochya Kernewek ha’y savla yn-dann gevalav, gwren ni mires orth an kost denel. My a gellis ow soodh 13 bloodh yn yethow dhe SK kettooth ha dell veu eskorrans Sowsnek hewul lowr dhe askusya sevel orth tyli den. Y’n kas diwirhaval may kevyn SK hag a yll askorra Kernewek da, prag y hwrussa nebonan omankombra ow pe kowser? An tybyans a SK ow tenna oll an bewnans a’m taves ertach ha ni ow kwynnel dhe dreusvewa dell on yw skruthus.
Yn sempel, budh yw gorthenebel orth tus. Hedre vo SK an degen nowydh flamm a vudh, y fydh gorthenebel orth tus. Ha yeth yw hy thus.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Nyns eus styr dhe gesunyansow a lytherennow war skrin heb dewis ha heb mynnas.10
Ross Perlin, Endangered Language Alliance
Kyn nag yw yeth dibarow dhe dhensys, onan a’n rannow chif a vos denel yw. Ny yll bos lehes dhe gedhlow hepken, mes yth yw argerdh sosyel dres eghen.11 Ni oll a wor py mar synthesek y sen skoodhyans prener der SK po fatel yll SK fyllel orth konvedhes arliwyow. Dell gampol Dr. Mallory, “Yeth [yw] neppyth moy kepar hag enev a gemeneth. Ny yllir gwitha hemma yn jynn. Ny yllir assoylya kudyn denel kepar ha yethladhans gans gwel a yeth hag a remov an gerann denel.”12
Ny yll SK konvedhes Kernewek po taves vyth aral. Papynjay chonsus yw: y targan py ger yw gwirhaval wosa an huni kyns.13 Ny yll agan konvedhes. Ny yll mynnes tra vyth. Mar kwra derivas orthis y vos pes da dha weres, gow yw. My a vynn agan kemeneth dhe devi, mes ny wra kans jynn-amontya a yll ‘kewsel Kernewek’ keworra orti. Y hwra unn den—ow tri tybyansow ha govenegow hag ownow ha gwanderyow—ha ny dybav y hwra an jynnys-amontya kernwegorek keworra unn den hogen orth agan kemeneth.
Gwettha, mar kwra, yma dustuni a-dhyworth Microsoft hag a brof y hwra an devnydh a SKDin war oberennow yeth, unweyth an seythen hogen, aperya gallos godhvosel a dhyski, ow ledya orth omworrans lehes gans an desten, gorfydhyans y’n deknegieth ha sleyneth sprallys a assoylya kudynnow yn anserghek.14 Der usya toulys SK dhe ‘dhyski’ Kernewek, possybyl yw ni dhe shyndya gallos dyski an yeth vytholl heb an kroch ma. Ni a wra gul mimyoryon yn le Kernewegoryon.
Ynwedh Perlin a boslev an elven dhenel, ow leverel pan wren ni synsi kemeneth avel kres agan yethow, dell wren, an papynjay chonsus a yll bos klewys kepar ha defolyans.15 Y’n eur ma, my a aswon pan eus nebonan owth usya ‘Kernewek’ SK dhymm. An tybyans ny wrav vy unn jydh godhvos pan eus estren—nebonan a wrussen vy dynerghi mar pe lyver po klass ganses—ow popettya diwawen ow hengerens ha kewsel dresta yw bedhrosus. Yma dhe’n dra an wan dhistowgh a drevesigeth, a berghenegyans pan yllir gwerthveurhe, a bapynjaya pan yllir junya agan kesgan.
Unver yw skolheyk Hawai’i henwys Noah Ha‘alilio Solomon: “Ankensi yw, drefen ni dhe vos kofhes a’n prysyow oll re beu agan gonisogeth ha yeth perghenegys. Ni re beu owth omladh dre dhens hag ewines yn batel gales a-barth dasvewheans yeth.[…] Y hwra pobel krysi bos hemma representyans ewn a’n yeth a Hawai’i.”16
TREST HAG OMGLEWANS AN GEMENETH
Hir re beu an kil-lash gorthjynn ow kovryjyon mes lemmyn yma va ow terri an arenep dell hevel.17
NBC NEWS
Tardh an arvedhennow rag SK y honan (clanker, tinskin, toaster), y askorras (slop, dross, brainrot) ha’y usyoryon (slopper, groksucker, botlicker, second-hand thinker)—keffrys hag erel selys moy yn kler war geryow kas gwir dell ov attes gans aga heworra—a re hwedhel a stons ollgemmyn a wogrys ha divlases war-tu hag an deknegieth ha’y devnydh war an kesrosweyth Sowsnek ha yethow bras erel.18 Kynth yw an stons yn-mysk gwesyon dek ha korforeth hwath gwresek, rag an boblek gemmyn y hwra SK “dos ha bos keschanjyadow gans taklow tamm kawgh.”19
Pella, nyns yw marnas yethow moyhariv gans an gwel negedhek ma a SK avel podrek. Sampel uskis a gampollow media sosyel ha meusi ow tochya SK ha Godhalek Alban gans Professor Lamb a dhiskwedhas fals a 54% negedhek, 33% posedhek ha 13% heptu. (Lamb, 2024) Sentiment an kampol negedhek an moyha talvesys o bos SK dregynnus hag an nessa y talvia dhyn lettya SK rag kestav gans tavosow ertach.
Pyth eson ni ow leverel orth agan diyskynysi? Ny dal agan yeth ha gonisogeth an strivyans personel? Hemm yw martesen fatel wrussen vy y redya, a pen vy i.20
Gorthebydh sondyans Kernewek
Kernewek a baynt aven moy serth, yn arbennik gans dyskoryon ha kowsoryon yowynka ha moy skentel gans tek. Sondyans war Discord ha Whatsapp Kernewek a drovyas bos 65% a grysis y fia SK drog (11.5%) po pur dhrog (53%) rag an yeth. Pan veu govynnys pyth a dal bos gorthyp an gemeneth orth SK, 46% a leveris y kodh y hedhi ha 27% y woheles, gans an dus moy ha 60 bloodh hepken ow tybi y kodh oberi ganso.20
31% a worthebydhyon an sondyans a leveris y hwrussa an devnydh a SK yn Kernewek aga fellhe a’n yeth, hag ynwedh 54% a leveris y fiens i pellhes yn krev ha 23% pellhes tamm a by kowethas, asnodh po dyskador pynag ow tevnydhya SK.
An gorthyp a’n re a leveris bos aga godhvos a SK po “konnyk” po “da” o dampnus yn arbennik. Pubonan y’n bagas ma a worthebis y fia SK dregynnus rag Kernewek, y hwrussa an devnydh a SK gans pennfenten aga fellhe a’n bennfenten na yn krev hag y kodh dhyn hedhi an devnydh a SK rag Kernewek.
HONANIETH, LELDER HA DIVERSETH
Nyns esa Aristotelis Ioannis Paschalidis, ow skrifa a-barth UNESCO, ow kewsel yn komparek a-dro dhe yethow lyharivhes pan wrug ev y wovyn, mes an govyn a dhassen yn kreffa ragon: “Pygemmys koll a honanieth a vynnir sakrifia rag effeythuster?”21
Honanieth yw a’n moyha bri rag Kernewegoryon. Studhyans Ute Wimmer Reversing Language Shift: the Case of Cornish a henow “gweythres [an yeth] avel arwodh a honanieth kenedhlek” avel an nessa ughella skila (66%**) yn-mysk kowsoryon ha dyskoryon, fethys gans gonisogeth Kernow (80%) hepken.22 Yth havalsa hemma bos acheson solempnyans, mes pan vo SK keworrys, y teu ha bos peryl. Vincent Koc a Hyperlink a lever y hyll SK “kevri dre wall orth an gwannheans a yeth ha honanieth wonisogethel”.23
Ev a aswon ynwedh y hallsa awtomategi dyski po dinythi yeth “lehe an rychedh ha lelder hag a dheu a gowsoryon dhenel neb a dheg istoriow gonisogethel y’ga hows”. Yn hwir, peswar studhyans gwrys gans Pennskol Kaliforni Soth re dhiskwedhas bos devnydhya PYB dhe weres gans skrifa “kelmys orth dyfygyansow nosedhek yn diverseth yethel hag y hyll mellya gans an konvedhes brysoniethel ha kowethasel yw proviys gans yeth.”24
Ha hemm yw yn Sowsnek, onan a’n yethow an ryccha ha brassa y’n bys. Dismyk an effeyth war yeth byghanna kepar ha Kernewek—gans le a dhogvennans, le a gedhlow, sel kowsoryon munys hag ogas hag arghans mann—ha war y lies orgraf hag eghen yeth. Yn arbennik yn gettesten Kernewek, seulabrys yma kowsoryon Diwedhes ow strivya dhe vos gwelys avel vas gans gwartheyvans Kres. A dybyn y hwor SK an dyffrans? Heb preder, y hwra po kemyska puptra warbarth, ow sowdheni pubonan, po devnydhya Kres dhe fetha Diwedhes.
An gwruthyl a dhalgh herdhys gans SK Dinythus, dre favera yethow savonegys, a argyl an vansyans a rannyethow ranndiryel.25
Kresen woramontyorieth Barcelona
Nyns yw eghennow hepken yn peryl; SK a wodros beudhi Kernewek yn tien. Akordys yw Perlin y hallsa an platheans yethel a hwarva dres kansbledhynnyow yn Sowsnek hwarvos dres nos yn yeth lyharivhes gans SK orth an fronnow—dell via, ow pos gallosek a bassya Kernewek denel heb assay. Ev a venek prederow yn kever PYB ow rewi yeth yn hy le ha hogen ow settya pyth yw an styr a wodhvos an yeth, yn arbennik gans niverow munys a gowsoryon deythyek.26
Treylyansow leun a atal a liesha warlinen kepar ha nowodhow fug. Kowsoryon deythyek a’n yethow ma yw passyes avel bos “re gales dhe drovya”, komparys orth fordhow awtomategys a surheans kwalita hag yw disjunys yn tien a geskomunyans y’n bys gwir. Kynth yw possybyl rag kemenethow yeth brassa ha moy gallosek synsi an bottys ma dhe akont ha’ga devnydhya yn stratejek hogen, re es yw dismygi [yeth lyhariv] ow pos reverthys.26
Ross Perlin, Endangered Language Alliance
Heb kontrol hag yn diwla an gewri deknegieth, Kernewek synthesek a wra gornivera ha gorthrabellhe Kernewek denel.
SOVRANEDH KEDHLOW HA KOLONEGIETH
Sovranedh kedhlow teythyek yw an gwir gans [kenedhel teythyek] a woverna an kuntel, perghenogeth ha gweytha a’y hedhlow hy honan.27
Native Nations Institute
Byttegyns, yma gonisogethow teythyek hag usi owth oberi war geskowethyans moy ewnhynsek gans SK. Tek heb an kowr a res asnodhow, mes y as kemenethow gwitha sovranedh kedhlow war an gerthen wonisogethel hag yw aga yeth. Te Mana Raraunga, Rosweyth Sovranedh Kedhlow Māori, re wrug rol a bennrewlys rag an gwruthyl, devnydhya ha kevrenna a gedhlow Māori, ow ragwirhe an edhom a grefhe maystri rag Māori a-lemmyn hag a dheu.
I a venek poynt posek hag a dalvia bos konsidrys gans rach gans stywards a skians yethel ha gonisogethel: “Kedhlow ahanan, a-dro dhyn ha’gan asnodhow, yw kerthennow a bris. Pan vo maystri kellys, kales yw y dhaskemeres.”28 Ny dal gul erviransow yn skav po yn uskis; y hyllyn pupprys leverel “ea” mar kwrussyn leverel “na” kyns orth us sett kedhlow, mes ny yllyn nevra leverel “na” mar kwrussyn leverel “ea” seulabrys.
An desten SK, kepar ha pub le aral, yw leun a dus hag yw settys y’ga maneryow ha gans gwel pur drevesigel yn tidowl.29
Michael Running Wolf, First Languages AI Reality
Hemm yw pur bosek y’n gettesten a’n kontrol possybyl a gedhlow Kernewek gans korforethow gallosek a-ves. Estenegieth jatelydhek re beu molleth war gowethasow y’n amal emperourethek ha nyns yw kowethas Kernewek dyffrans, wosa enebi kansvledhynnyow a’y rychys hag asnodhow naturek ow pos destryppys ha gwerthys dre vras gans budh tus yn-mes a Gernow.
An lyver henwys Indigenous Data Sovereignty and Policy a verk lemmyn y hyllir gweles perthynyansow kedhlow avel “pesyans a’n argerdhow ha systemow-krysi isworwedhek a estennans, drogusyans, kuntellyans ha diberghenogeth re beu gwrys war boblansow Teythyek dres trevesigeth istorek.”30 An konvedhes estennek ma a gedhlow yw, dell verkons, hevelebys a-der goderrys gans tyli pobel rag aga hedhlow.
Wostiwedh, res yw ma na vo agan yeth gorrys yn diwla a-ves routys gans pennrewlys perghenogel na as dhyn sovranedh lowr a onan a’gan asnodhow naturel an moyha posek: agan yeth. Res yw dhyn kavos pennrewlys kedhlow ygor, a-der plegya orth kontrol korforethel. Res yw dhyn lewya ha gidya an devnydh a’gan kedhlow, a-der y usya erbynn agan lesow ha rag pocketys tek bras.
A-der drehedhes an arwithans a davosow avel kudyn teknegiethel, my a dyb bos res dhe gemenethow teythyek bos reythhes yn politek, po der arghasans a wovernansow po dre dhifresyansow laghel dhe dhevnydhya aga yethow.31
Dr. Fintan Mallory, Pennskol Durham
Res yw dhyn ragwirhe yeth-avel-kemeneth ha hwilas devnydh ygor, ewnhynsek hag ethegel a’gan kerthennow yeth, ertach ha gonisogethel. Res yw dhyn goheles tybi a SK avel an hus mayth ambos ha kevarghewi yn hwithrans selyek, lewys gans agan kemeneth. Ny wra korforethow agan selwel ha, hogen, i a yll agan shyndya.
NYNS EUS KERNEWEK WAR BLANET MAROW
Governansow ha kevalav ollvysel […] yw omres dhe ideologieth marghas ‘rydh’ moy es dell yns omres dhe sewena kemenethow, pobel ha’n planet.32
Cymdeithas yr Iaith Maniffesto 2022
An brassa rann a vreusyansow a SK a wrussa meneges hemma seulabrys. Onan a’n argyansow brassa yw erbynn SK Dinythus, mes rag own bos ankoth dhis, ni a wra mires orth an chif boyntys.
Res yw bos evadow an dowr goyeynhe pub kresen kedhlow SK. Y kollenk an dowr ma. Pennskol Kaliforni re dherivas “y hallsa demond dowr ollvysel SK hedhes 4.2-6.6 bilvil metrow kubek erbynn 2027. Henn yw moy es 50 kansran a us dowr bledhynnyek an RU yn 2023.”33 Y kettermyn, an Desedhek Ollvysel Erbysieth Dowr a dheklaryas “barras dowr ow tardha yn uskis” ma na dal Kernewek kevri dhodho.34
Ni re dheuth ha bos yn hwir omres dhe deknegiethow privedh gwrys ha kontrolys gans dornas a gompanis diskler [hag] a hevel bos mygyl dre vras orth an sewyansow sosyel a’ga gwriansow ha kevri yn ispoyntel marnas mars yns i konstrinys gans rewlys an wovernans dhe wellhe aga imach poblek.35
Iker Erdocia, Pennskol Sita Dulyn
Yma edhom dhe SK a vynsow kowrek a galesweyth orth kost palas monyow tanow. Kales yw estenna ha purhe an re ma hag yma kostow kerghynedhel ha sosyel poos. Estennys yns i yn fenowgh a hwelyow yn powyow gans difresyansow lakka rag lavur ha’n kerghynnedh. Reset a lever “yn fenowgh y hwra kemenethow yw trigys yn ogas dhe’n hwelyow, yn fenowgh bagasow lyhariv po teythyek, enebi gwethheans an tir, defolyans an dowr hag abusyans gwiryow denel. Meur a hemma a yll bos kelmys yn tidro orth an galesweyth SK.”36 Pan yw an galesweyth kegys yn sertan hag euver, ena tewlys yw avel e-wast yn kemenethow boghosek. Res yw nyns yw an avonsyans possybyl a Gernewek orth kost agan kemenethow hwor lyhariv ha teythyek.
Ynwedh res yw myns hujes a nerth rag trenya SK, yn skon martesen an keth myns ha pow byghan37 hag yma ol troos karbon kowrek.38 Kler yw—der usadow dowr, diwysyans estennek, konsumyans nerth hag ol troos karbon—bos SK yeyn nowodhow rag kerghynnedh ow strivya a’n planet mayth on ni trigys warnodho ha nyns eus Kernewek war blanet marow.
GUL DHE SK BOS EKS-PAPYNJAY
A-der gul dhe yethow lyhariv bos moy hedhadow, lemmyn yma SK ow kwruthyl tardhek pupprys owth omlesa rag studhyoryon ha kowsoryon a’n yethow ma dhe wolya.39
mit technology review
Ni re glewas a’n anwirhevelepter efan a wul dhe SK gallos mimya Kernewek yn golow an kostys yn kedhlow, ober, termyn ha teknegieth. Ni re gonsidras lycklod an dewisynter dispresyans yeyn po askorras-aspia ha’n posekter a sovranedh kedhlow. Ni re redyas a-dro dhe’n effeythyow war vewnansow Kernewegoryon, keffrys ha’n kostys katastrofek rag an kerghynnedh ha poblow teythyek.
Ni re dhyskas y hwra platheans yethel gans SK boghosekhe y destennow ha fatel yll SK martesen ervira a’gan parth fatel godh dh’agan yeth oberi. Ni re welas an anwoheladewder a yeth avel denel ha’n peryllyow a wul ‘dyskoryon’ na yll dyski ha ‘kowsoryon’ na yll kewsel. Ni re welas an peryllyow orth bri ha fydhyans rag kowethasow a wrussa palas an pyth hag yw gwelys avel ‘skomblans’.
Ni re glewas prag y fia omblegya orth an jagganat a SK error rag Kernewek ha dell na vynn agan kemeneth skoodhya gorra an skoos a-dhyworthyn. Yn y le, res yw dhyn batalyas. Res yw dhyn gul dhe Gernewek bos spas mar rydh a skomblans dell yll bos, res yw adhyski orth botlapyoryon yn dyski ha devnydh yeth yn ethegel hag yn effeythus, res yw goheles tybi wortaswerth.
Res yw dhyn gul dh’agan yeth bos parth heb SK, rosweyth a dus fydhyadow ha’ga gwriansow denel, drehevys war lelder, kemeneth, assay ha trest: Kernewek hag yw a-barth an bobel, a’n bobel ha gans an bobel.
Niwlen Ster
Notennow
* A prime example is the laughably-unaffordable restaurant RenMor, which The Headland Hotel thinks is a version of “Re’n Mor”, which they believe means “by the sea” as in “next to the sea” but actually means “by the sea!” like saying “by Zeus!”. This is both hilarious and enraging.
** A figure perhaps lower than it should be if you consider that many of the “emotional motives” which were not counted in this category, such as “I’m Cornish, what better reason do you need?”, do also refer to identity.
FENTENNOW
1. Judah, J. (2025) How AI and Wikipedia have sent vulnerable languages into a doom spiral, MIT Technology Review.
2. Ackermann, A. (2023) When AI doesn’t speak your language, Coda.
3. Crichton, D. (2024) AI and the Death of Human Languages, Lux.
4. Lamb, W. (2024). Could Artificial Intelligence save Scottish Gaelic?, The University of Edinburgh.
5. Dencik, L. (/2025) AI Inequalities: Minority Languages, TUC Cymru.
6. Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Microsoft Research, India. (2020). The State and Fate of Linguistic Diversity and Inclusion in the NLP World. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
7. Ackermann, A. (op cit)
8. McLoughlin, I. (2018) How to teach AI to speak Welsh (and other minority languages), The Conversation.
9. Mallory, F. (2025) RISE UP Panel Discussion & Q&A: What AI Can and Cannot Do for Minoritised Languages, YouTube.
10. Perlin, R. (2024) AI Won’t Protect Endangered Languages, The Dial.
11. RISE UP (2025) #4 RISE UP Event Summary: What AI Can and Cannot Do For Minoritised Languages, RISE UP.
12. Mallory, F. (2024) European Day of Languages: Will lesser spoken languages soon only be kept alive by AI technology? Durham University.
13. Bender, E., Gebru, T., McMillan-Major, A., & Mitchell, M. (2021) On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
14. Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025) The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers. Microsoft.
15. Perlin, R. (op cit)
16. Judah, J. (op cit)
17. Abbruzzese, J., & Wile, R. (2025) Is an AI backlash brewing? What ‘clanker’ says about growing frustrations with emerging tech, NBC News.
18. Webster, K. (2025) Why Using ChatGPT at Work Could Hurt Your Reputation, Inc. Magazine.
19. Herrman, J. (2024) Is That AI? Or Does It Just Suck?, Intelligencer.
20. Wilson, L. (2025) Skians Kreftus ha Kernewek/Artificial Intelligence and Cornish
21. Paschalidis, A. I. (2025) AI and the great linguistic flattening, UNESCO.
22. Wimmer, U. (2010). Reversing Language Shift: the Case of Cornish. Cornish Language Board, p. 113
23. Koc, V. (2025) Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges, ResearchGate.
24. Sourati, Z., Karimi-Malekabadi, F., & Ozcan, M. (2025) The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Models, ResearchGate.
25. Melero, M. (2024) The Future of Language (and Cultural) Diversity in the Age of AI, CLARIN.
26. Perlin, R. (op cit)
27. Russo Carroll, S., Rodriguez Lonebear, D., & Martinez, A. (2017). Data Governance for Native Nation Rebuilding, Native Nations Institute.
28. Te Mana Raraunga. (2018). Frequently Asked Questions, Te Mana Raraunga.
29. Ackermann, A. (op cit)
30. Walter, M., Kukutai, T., Carroll, S. R., & Rodriguez-Lonebear, D. (Eds.). (2020). Indigenous Data Sovereignty and Policy. Taylor & Francis, p. 24
31. Mallory, F. (op cit)
32. Cymdeithas yr Iaith (2022) Cymru Rydd, Cymru Werdd, Cymru Gymraeg., p. 27
33. O’Sullivan, L. (2025). How AI’s Failure on Linguistic Diversity is Deepening Global Inequality, RESET – Digital for Good.
34. Harvey, F. (2024). Global water crisis leaves half of world food production at risk in next 25 years, The Guardian.
35. Erdocia, I., Migge, B., & Schneider, B. (2024). Language is not a data set—Why overcoming ideologies of dataism is more important than ever in the age of AI. Journal of Sociolinguistics, 28(5), p. 23
36. O’Sullivan, L. (op cit)
37. Erdenesanaa, D. (2023) A.I. Could Soon Need as Much Electricity as an Entire Country, The New York Times
38. Heikkilä, M. (2022) We’re getting a better idea of AI’s true carbon footprint, MIT Technology Review.
39. Judah, J. (op cit)#4 #AI #ArtificialIntelligence #Breus #Cornish #Cornwall #data #generativeAI #history #jynn #kedhlow #Kernewek #Kernow #Kernowek #LLM #machine #PYB #SK #SKDinythus #SkiansKreftus #Sordya
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Turning Saffron into Slop – Treylya Safran yn Skomblans
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
Note: Artificial Intelligence (AI) has come to be synonymous with Generative AI (GenAI) and with Large Language Models (LLMs), such as ChatGPT, in common parlance. Unless explicitly stated, I use the terms interchangeably.
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow*, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
LOW-RESOURCES AND LINGUISTIC TYPOLOGY
Simply adding a language to an AI model leads to a spike in poor-quality articles, drowning out quality writing by humans. AI has “industrialized the acts of destruction—which affect vulnerable languages most, since AI translations are typically far less reliable for them.”1 Wikipedia editors from varied languages evidence that machine translation tools have made it easier than ever before to create shoddy articles in minoritised languages, causing massive damage in minutes. AI leads to non-speakers producing much longer, truthier rubbish, Sámi computational linguistics expert Trond Trosterud notes: “the problem [is] that they are armed with Google Translate. Earlier they were armed only with dictionaries.”1
Kernewek, like all but 60 of the world’s roughly 7,000 languages, is designated “low-resource”, meaning it lacks sufficient data to train a machine.2 It is tempting, therefore, to assume that the solution is to provide more data. However, training an LLM requires petabytes of text, audio and video—manually categorised and in a machine-readable format—a vast trove that Kernewek simply does not have.3 Professor Will Lamb, Chair of Gaelic Ethnology and Linguistics at Edinburgh University, speaks of “millions of work hours devoted to just one aspect” of a working AI.4
Even if ChatGPT is trained on another language than English, the time and labour required may make it largely unviable. Current assessments of the performance of ChatGPT for different languages have shown that it performs worse in all tasks.5
Prof. Lina Dencik, Data Justice Lab
Furthermore, the amount of data and work is not the only barrier; at issue is the nature of the language itself. Microsoft has found that languages such as Breton—and thus Kernewek—cause a high rate of errors distinct from the size of their dataset, due to grammatical features, such as mutation, not present in well-sourced languages. As such, they remain poor without significant additional work.6 Essentially, simply adding more Kernewek may not help. Thus, engaging with AI is, for Kernewek, to tie ourselves to slop.
Noten: Skians Kreftus (SK) re dheuth ha bos kesstyr gans SK Dinythus (SKDin) ha gans Patronyow Yeth Bras (PYB), kepar ha ChatGPT, yn lavar kemmyn. Marnas bos menegys yn kler, my a us an termys yn keschanjyadow.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow*, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
ASNODHOW ISL HA TIPOLOGIETH YETHEL
Keworra yeth yn sempel orth patron SK a led orth spik yn erthyglow drog aga kwalita, ow peudhi skrif a gwalita gans tus. SK re wrug “diwysyansegi an aktys diswrians—hag a nas yethow goliadow an moyha, drefen bos treylyansow SK lieskweyth le lel yn tipek ragdha.”1 Golegydhyon Wikipedia a yethow divers a re dustuni re wrug medhelweyth-treylya y wul bos esya dell veu bythkweth kyns gwruthyl erthyglow pilyek yn yethow lyharivhes, ow kawsya damach kowrek yn mynysennow. SK a led orth digowsoryon owth askorra atal lieskweyth hirra ha gwirekka, konnyk yethonieth reknansek Sámi Trond Trosterud a not: “an kudyn [yw] aga bos ervys gans Google Translate. A-varra nyns ens ervys marnas gans gerlyvrow.”1
Kernewek, kepar hag oll marnas 60 a ogas lowr 7,000 yeth a’n bys, yw klassys avel “isel y asnodhow”, ow styrya nag eus dhodho kedhlow lowr dhe drenya jynn.2 Rakhenna, dynyek yw desevos bos an assoylyans profya moy a gedhlow. Byttegyns, res yw petavaytys a dekst, son ha gwydhyow—klassys dre leuv hag yn furvas redyadow gans jynn— dhe drenya PYB, tresorva efan nag eus dhe Gernewek yn sempel.3 Y kews Professor Will Lamb, Kaderyer Ethnologieth ha Yethonieth Wodhalek orth Pennskol Karedin, a “vilvilyow a ourys ober sakrys orth unn wedh hepken” a SK owth oberi.4
Hogen mars yw ChatGPT trenys war yeth a-der Sowsnek, an termyn hag ober yw res a styr y vos martesen anhewul dre vras. Arvreusyansow a-lemmyn a berformyans a ChatGPT rag yethow dyffrans re dhiskwedhas y perform gweth yn oberennow oll.5
Prof. Lina Dencik, Data Justice Lab
Pella, nyns yw an myns a gedhlow hag ober an unsel lett; a vern yw natur an yeth y honan. Microsoft re drovyas y kaws yethow kepar ha Bretonek—hag ytho Kernewek—kevradh ughel a wallow diblans a vraster aga sett kedhlow, drefen nasyow gramasek, kepar ha treylyansow, nag usi kevys yn yethow ughel aga asnodhow. Yndella, i a bes orth bos drog heb meur a ober keworransel.6 Yn essensek, possybyl yw ny wra keworra moy a Gernewek yn sempel gweres. Yndelma, oberi gans SK yw, rag Kernewek, omgelmi orth skomblans.
CORNISH UNDER CAPITALISM
But surely we can improve things over time? It will take a lot of help from AI companies, but it will be worth it. Sadly, Gabriel Nicholas, a research fellow at the Center for Democracy and Technology, has found that once a tech company has established basic capabilities for a language, they pat themselves on the back and move on.7
Big tech companies are just that: companies. They exist to make a profit. Unfortunately, a market dominated by big languages gives them no incentive to invest in improvements for small ones.
All of the speech technology, smart homes and voice interaction systems used today are the products of commercial research. To put it bluntly, they exist to either make money from your data, to sell you more goods and services, or to influence your thinking. None of this AI exists for the public good. […] Unless there is a strong enough economic argument, don’t expect big companies to rush into producing Welsh, Gaelic or Cornish speech systems.8
Prof. Ian McLoughlin, University of Kent
Should they decide that a Kernewek AI is a viable profit-making enterprise, our situation may even be worse than abandonment. As Dr. Fintan Mallory remarks, the dominant means of profit for privately-funded AI enterprises is to convert their tools into surveillance devices.9 As Kernewek is currently one of the UK’s only languages which is not currently easily surveillable, this poses a huge risk to Kernewek activism and the fight for self-determination in a state that seeks to criminalise dissent.
While we’re on the subject of Kernewek and its position under capitalism, let’s consider the human cost. I lost my 13-year career in language to AI as soon as English output became viable enough to excuse not paying a human. In the unlikely instance that we achieve an AI that can produce quality Kernewek, why would anyone bother paying speakers? The idea of AI sucking all the life out of my heritage language when we are struggling to survive as-is is appalling.
Simply put, profit is antithetical to people. While AI is the new favourite toy of profit, it will be antithetical to people. And a language is its people.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Combinations of characters on a screen mean nothing without agency and intention.10
Ross Perlin, Endangered Language Alliance
While language is not unique to humans, it is one of the chief parts of being human. It cannot be reduced to mere data, but is a highly social process.11 We all know how synthetic customer support via robot sounds or how AI fails to pick up nuance. As Dr. Mallory comments, “Language [is] something more like the soul of a community. You can’t store this in a machine. You can’t solve a human problem like linguicide with a view of language that removes the human component.”12
AI cannot comprehend Kernewek or any other language. It is a stochastic parrot: predicting what word is likely to follow the previous one.13 It cannot understand us. It cannot intend anything. If it tells you it feels delighted to help you, it is lying. I want our community to grow, but one hundred ‘Cornish-speaking’ computers do not add to it. One human does—bringing ideas and hopes and fears and foibles—and I do not think the Kernewek ‘speaking’ computers will add even one human to our community.
Worse, if it does, there is evidence from Microsoft to suggest that the use of GenAI on language tasks, even once a week, impairs cognitive ability to learn, leading to decreased engagement with the topic, overreliance on the technology and hobbled skills in independent problem-solving.14 By using AI tools to ‘teach’ a learner Kernewek, we may in fact be impairing their ability to learn the language at all without this crutch. We will make regurgitators in place of speakers.
Perlin also emphasises the human element, saying that when we hold community central to our languages, as we do, the stochastic parrot can feel like a violation.15 At the moment, I can tell when someone is using AI ‘Kernewek’ to me. The idea that one day I will not know when an outsider—someone I would welcome if they took up a book or a class—is puppeting my ancestors’ jaws and speaking through them is ghoulish. It has the instant sting of colonialism, of appropriation when one could appreciate, of parroting when one could join our chorus.
Hawai’ian scholar Ha‘alilio Solomon agrees: “It is painful, because it reminds us of all the times that our culture and language has been appropriated. We have been fighting tooth and nail in an uphill climb for language revitalization.[…] People are going to think that this is an accurate representation of the Hawaiian language.”16
TRUST AND COMMUNITY FEELING
The anti-machine backlash has long been simmering but is now seemingly breaking to the surface.17
NBC NEWS
The explosion of insults for AI itself (clanker, tinskin, toaster), its output (slop, dross, brainrot) and its users (slopper, groksucker, botlicker, second-hand thinker)—as well as others more clearly based on real-world slurs than I am comfortable to include—tells a tale of the general attitude of distrust and disgust towards the technology and its use on anglophone and other majority language internet.18 While the attitude among tech bros and corporates remains bombastic, for the general public AI is “becoming interchangeable with things that sort of suck.”19
Further, it’s not just majority languages with this negative view of AI as taint. A quick sampling of social media comments and likes regarding AI and Scottish Gaelic by Professor Lamb showed a split of 54% negative, 33% positive and 13% neutral. (Lamb, 2024) The sentiment of the top-rated negative comment was that AI is harmful and the second-highest that AI should be kept away from heritage languages.
What are we telling our descendants? That our language and culture isn’t worth the personal effort? That’s how I might read it, if I were them.20
Kernewek survey respondent
Kernewek paints an even starker picture, especially among younger and more technologically-savvy learners and speakers. A survey on Cornish Discord and Whatsapp found that 65% felt AI would be bad (11.5%) or very bad (53%) for the language. When asked what the community response should be to AI, 46% said we should prevent it and 27% avoid it, with only over-60s thinking that we should work with it.20
31% of respondents said using AI in Kernewek would cause them to feel estranged from the language, while 54% said that they would feel strongly estranged and 23% a little estranged from any organisation, resource or teacher using AI.
The response from those who gave their knowledge of AI as either “expert” or “good” was particularly damning. Everyone in this group responded that AI would be harmful for the language, that the use of AI would estrange them from a source strongly and that we should prevent the use of AI for Kernewek.
IDENTITY, AUTHENTICITY AND DIVERSITY
Aristotelis Ioannis Paschalidis, writing for UNESCO, was not speaking specifically about minoritised languages when he asked this, but the question resonates even more strongly for us: “How much loss of identity is one willing to sacrifice for efficiency?”21
Identity is of paramount importance to Kernewek speakers. Ute Wimmer’s study Reversing Language Shift: the Case of Cornish identified the language’s “function as a symbol of national identity” as the second highest motive (66%**) among speakers and learners, beaten only by Cornish culture (80%).22 This would seem cause for celebration, but when AI is added to the mix, it becomes a risk. Vincent Koc of Hyperlink states that AI can “inadvertently contribute to the dilution of language and cultural identity.”23
He also identifies that automating language learning or generation “may diminish the richness and authenticity that comes from human speakers who carry cultural histories in their speech.” Indeed, four studies by the University of Southern California have shown that using LLMs to assist writing “is linked to notable declines in linguistic diversity and may interfere with the societal and psychological insights language provides.”24
This is in English, one of the richest and largest languages in the world. Imagine the possible impact on a smaller language like Kernewek—with less documentation, less data, a tiny speakerbase and basically no money—and on its many language varieties and orthographies. Particular to the Kernewek context, Late speakers are already struggling to be seen as valid under the dominance of Middle. Do we think AI knows the difference? Thoughtlessly, it will either mix everything together, confusing everyone, or it will use Middle to overwhelm Late.
Generative AI-driven content creation, by favoring standardized languages, risks the disappearance of regional dialects.25
Barcelona supercomputing Center ….
Not only are varieties at risk; AI threatens to drown Kernewek as a whole. Perlin agrees that the linguistic flattening that occurred over centuries in English could manifest overnight in a minoritised language with AI at the helm—as it would be, being able to effortlessly outstrip human Kernewek. He raises concerns of LLMs freezing a language in place and even defining what it means to know the language, especially with low numbers of native speakers.26
Garbage translations multiply online like fake news. Native speakers of the languages in question are bypassed as being “too hard to find,” compared with automated methods of vetting that are completely disconnected from real-life communication. While larger and more powerful language communities may be able to hold the bots to account and even make strategic use of them, it is all too easy to imagine [a minority language] being overwhelmed.26
Ross Perlin, Endangered Language Alliance
Uncontrolled and in the hands of tech giants, synthetic Kernewek will outnumber and outmanoeuvre human Kernewek.
DATA SOVEREIGNTY AND COLONIALISM
Indigenous data sovereignty is the right of [an indigenous nation] to govern the collection, ownership, and application of its own data.27
Native Nations Institute
There are, however, indigenous cultures that are working on a more equitable relationship with AI. Tech without the giant requires resources, but it allows communities to retain data sovereignty over the cultural asset that is their language. Te Mana Raraunga, the Māori Data Sovereignty Network, has created a list of principles for the creation, use and sharing of Māori data, prioritising the need to enhance control for current and future Māori.
They raise a key point that should be considered carefully by stewards of linguistic and cultural knowledge: “Data from us, and about us and our resources, are valuable assets. Once control of it is lost, it is difficult to regain.”28 Decisions must not be taken lightly or hastily; we can always say “yes” if we have previously said “no” to a particular dataset’s use, but can never say “no” if we have already said “yes”.
The AI field, like any other space, is occupied by people who are set in their ways and unintentionally have a very colonial perspective.29
Michael Running Wolf, First Languages AI Reality
This is vital in the context of the potential control of Kernewek data by powerful external corporations. Capitalist extractivism has long been a bane on societies in the imperial periphery and our Cornish society is no different, having faced centuries of its wealth and natural resources being stripped and sold by and large for the profit of those outside Cornwall.
The book Indigenous Data Sovereignty and Policy notes that current data relations can be seen as “a continuation of the processes and underlying belief systems of extraction, exploitation, accumulation and dispossession that have been visited on Indigenous populations through historical colonialism.”30 This extractive understanding of information is, they note, not disrupted but rather replicated by paying people for their data.
Ultimately, our language must not lie in outside hands governed by proprietary principles that do not allow us sufficient sovereignty over one of our most valuable natural resources: our language. We must have open data principles, not bow to corporate control. We must steer and steward the use of our data, rather than expose it to use against our interests and for the pockets of big tech.
Rather than approaching language preservation as a technical problem, I think indigenous communities need to be politically empowered, whether that be funding from governments or legal protections to use their languages.31
Dr. Fintan Mallory, Durham University
We must prioritise language-as-community and seek open, equitable and ethical use of our language, heritage and other cultural assets. We must avoid thinking of AI as the magic that it promises and invest in basic research, driven by our own community. Corporations will not save us and, indeed, may do us great harm.
NO CORNISH ON A DEAD PLANET
Global capitalism and governments […] are addicted to ‘free’ market ideology over the wellbeing of communities, people and the planet.32
Cymdeithas yr Iaith Maniffesto 2022
Honestly, most takedowns of AI would have hit this point already. It’s one of the main arguments against Generative AI, but in case you’re not familiar with it, we will briefly look over the main points.
Water used in cooling AI data centers must be drinkable water. AI guzzles this water. The University of California has reported that “global water demand from AI could reach 4.2-6.6 billion cubic meters by 2027. That exceeds 50 percent of the UK’s annual water use in 2023.”33 All this while the Global Commission on the Economics of Water has declared “a rapidly accelerating water crisis” to which Kernewek should not be contributing.34
We have become utterly dependent on private technologies manufactured and controlled by a handful of opaque companies [who] appear mostly indifferent to the social consequences of their activities and only invest minimally if obliged by government regulations to enhance their public image.35
Iker Erdocia, Dublin City University
AI requires vast quantities of hardware at the cost of mining rare earth minerals. These are difficult to extract and purify and come with heavy environmental and social costs. They are often extracted from mines in countries with poorer environmental and labour protections. Reset states that “communities living near these mines, often indigenous or minority groups, regularly face land degradation, water contamination and human rights abuses. Much of this can be directly linked to the AI hardware.”36 When the hardware inevitably cooks and is useless, it is then thrown out as e-waste into poor communities. The potential advancement of Kernewek must not come at the expense of our sister indigenous and minority communities.
Training an also AI requires huge amounts of energy, soon perhaps as much as a small country37 and has an enormous carbon footprint.38 What is clear is that—through water usage, extractive industry, energy consumption and carbon footprint—AI is bad news for the struggling environment of the planet we live on and there is no Cornish on a dead planet.
MAKING AI AN EX-PARROT
Rather than making minority languages more accessible, AI is now creating an ever expanding minefield for students and speakers of those languages to navigate.39
mit technology review
We have heard of the vast improbability of getting AI to be able to mimic Kernewek in light of the costs in data, work, time and technology. We have considered the likely choice of cold negligence or surveillance product and the importance of data sovereignty. We have read about the effects on the livelihoods of Cornish speakers, as well as the the catastrophic costs to the environment and indigenous peoples.
We have learned that linguistic flattening by AI impoverishes its subjects and how AI may decide for us how our language must operate. We have seen the inescapability of language as human and the risks of creating ‘learners’ who cannot learn and ‘speakers’ who cannot speak. We have seen the dangers to reputation and trust for any organisation who would shovel what is seen as ‘slop’.
We have heard why giving in to the juggernaut of AI would be a mistake for Kernewek and how our community does not support our laying down of the shield. Instead, we must fight. We must make Kernewek a space as free of slop as possible, we must educate botlickers into ethical and effective language learning and use, we must avoid second-hand thinking.
We must make our language a no AI zone, a network of reliable humans and their human creations, built on authenticity, community, effort and trust: a Kernewek for the people, of the people and by the people.
KERNEWEK YN-DANN GEVALAV
Mes yn sur y hyllyn ni gwellhe taklow dres termyn? Y fydh res meur a weres a gompanis SK, mes y talvia dhyn. Yn trist, Gabriel Nicholas, kesvroder hwithrans orth an Center for Democracy and Technology, re drovyas pan wrug kompani tek fondya gallosow selyek rag unn yeth, i a omgeslowenha yn ughel hag ena movya yn-rag.7
Kompanis tek bras yw yndella poran: kompanis. Ymons i ena rag gwaynya budh. Y’n gwettha prys, ny wra marghas rewlys gans yethow bras ri kentryn dhe gevarghewi yn gwellhe rag an re byghan.
Oll a’n deknegieth kows, chiow konnyk ha systemow ynterweythres lev usys hedhyw yw an askorrasow a hwithrans kenwerthel. Dhe vos sogh, yth yns i po rag dendyl arghans a’th kedhlow, po gwertha gwara ha gonisyow, po delenwel dha dybyansow. Nyns yw tra vyth a’n SK ma rag an les kemmyn. […] Mar nag eus argyans erbysek krev lowr, na wra gwaytya kompanis bras dhe fyski dhe askorra systemow kows Kembrek, Godhalek po Kernewek.8
Prof. Ian McLoughlin, pennskol kint
Ha mars ervirons bos SK Kernewek aventur a yll gwaynya budh, possybyl yw bos agan studh gweth ages dell via gans forsakyans. Dell lever Dr. Fintan Mallor, an fordh vrassa a waynya budh rag kompanis SK arghesys yn privedh yw kedreylya aga thoulys yn devisyow aspians.9 Drefen bos Kernewek onan a’n yethow boghes y’n RU nag yw aspiadow yn es y’n eur ma, hemm yw peryl kowrek rag gweythresieth Kernewek ha’gan strif a-barth omdhetermyans yn stat a vynn galweythegi dissent.
Ha ni ow tochya Kernewek ha’y savla yn-dann gevalav, gwren ni mires orth an kost denel. My a gellis ow soodh 13 bloodh yn yethow dhe SK kettooth ha dell veu eskorrans Sowsnek hewul lowr dhe askusya sevel orth tyli den. Y’n kas diwirhaval may kevyn SK hag a yll askorra Kernewek da, prag y hwrussa nebonan omankombra ow pe kowser? An tybyans a SK ow tenna oll an bewnans a’m taves ertach ha ni ow kwynnel dhe dreusvewa dell on yw skruthus.
Yn sempel, budh yw gorthenebel orth tus. Hedre vo SK an degen nowydh flamm a vudh, y fydh gorthenebel orth tus. Ha yeth yw hy thus.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Nyns eus styr dhe gesunyansow a lytherennow war skrin heb dewis ha heb mynnas.10
Ross Perlin, Endangered Language Alliance
Kyn nag yw yeth dibarow dhe dhensys, onan a’n rannow chif a vos denel yw. Ny yll bos lehes dhe gedhlow hepken, mes yth yw argerdh sosyel dres eghen.11 Ni oll a wor py mar synthesek y sen skoodhyans prener der SK po fatel yll SK fyllel orth konvedhes arliwyow. Dell gampol Dr. Mallory, “Yeth [yw] neppyth moy kepar hag enev a gemeneth. Ny yllir gwitha hemma yn jynn. Ny yllir assoylya kudyn denel kepar ha yethladhans gans gwel a yeth hag a remov an gerann denel.”12
Ny yll SK konvedhes Kernewek po taves vyth aral. Papynjay chonsus yw: y targan py ger yw gwirhaval wosa an huni kyns.13 Ny yll agan konvedhes. Ny yll mynnes tra vyth. Mar kwra derivas orthis y vos pes da dha weres, gow yw. My a vynn agan kemeneth dhe devi, mes ny wra kans jynn-amontya a yll ‘kewsel Kernewek’ keworra orti. Y hwra unn den—ow tri tybyansow ha govenegow hag ownow ha gwanderyow—ha ny dybav y hwra an jynnys-amontya kernwegorek keworra unn den hogen orth agan kemeneth.
Gwettha, mar kwra, yma dustuni a-dhyworth Microsoft hag a brof y hwra an devnydh a SKDin war oberennow yeth, unweyth an seythen hogen, aperya gallos godhvosel a dhyski, ow ledya orth omworrans lehes gans an desten, gorfydhyans y’n deknegieth ha sleyneth sprallys a assoylya kudynnow yn anserghek.14 Der usya toulys SK dhe ‘dhyski’ Kernewek, possybyl yw ni dhe shyndya gallos dyski an yeth vytholl heb an kroch ma. Ni a wra gul mimyoryon yn le Kernewegoryon.
Ynwedh Perlin a boslev an elven dhenel, ow leverel pan wren ni synsi kemeneth avel kres agan yethow, dell wren, an papynjay chonsus a yll bos klewys kepar ha defolyans.15 Y’n eur ma, my a aswon pan eus nebonan owth usya ‘Kernewek’ SK dhymm. An tybyans ny wrav vy unn jydh godhvos pan eus estren—nebonan a wrussen vy dynerghi mar pe lyver po klass ganses—ow popettya diwawen ow hengerens ha kewsel dresta yw bedhrosus. Yma dhe’n dra an wan dhistowgh a drevesigeth, a berghenegyans pan yllir gwerthveurhe, a bapynjaya pan yllir junya agan kesgan.
Unver yw skolheyk Hawai’i henwys Noah Ha‘alilio Solomon: “Ankensi yw, drefen ni dhe vos kofhes a’n prysyow oll re beu agan gonisogeth ha yeth perghenegys. Ni re beu owth omladh dre dhens hag ewines yn batel gales a-barth dasvewheans yeth.[…] Y hwra pobel krysi bos hemma representyans ewn a’n yeth a Hawai’i.”16
TREST HAG OMGLEWANS AN GEMENETH
Hir re beu an kil-lash gorthjynn ow kovryjyon mes lemmyn yma va ow terri an arenep dell hevel.17
NBC NEWS
Tardh an arvedhennow rag SK y honan (clanker, tinskin, toaster), y askorras (slop, dross, brainrot) ha’y usyoryon (slopper, groksucker, botlicker, second-hand thinker)—keffrys hag erel selys moy yn kler war geryow kas gwir dell ov attes gans aga heworra—a re hwedhel a stons ollgemmyn a wogrys ha divlases war-tu hag an deknegieth ha’y devnydh war an kesrosweyth Sowsnek ha yethow bras erel.18 Kynth yw an stons yn-mysk gwesyon dek ha korforeth hwath gwresek, rag an boblek gemmyn y hwra SK “dos ha bos keschanjyadow gans taklow tamm kawgh.”19
Pella, nyns yw marnas yethow moyhariv gans an gwel negedhek ma a SK avel podrek. Sampel uskis a gampollow media sosyel ha meusi ow tochya SK ha Godhalek Alban gans Professor Lamb a dhiskwedhas fals a 54% negedhek, 33% posedhek ha 13% heptu. (Lamb, 2024) Sentiment an kampol negedhek an moyha talvesys o bos SK dregynnus hag an nessa y talvia dhyn lettya SK rag kestav gans tavosow ertach.
Pyth eson ni ow leverel orth agan diyskynysi? Ny dal agan yeth ha gonisogeth an strivyans personel? Hemm yw martesen fatel wrussen vy y redya, a pen vy i.20
Gorthebydh sondyans Kernewek
Kernewek a baynt aven moy serth, yn arbennik gans dyskoryon ha kowsoryon yowynka ha moy skentel gans tek. Sondyans war Discord ha Whatsapp Kernewek a drovyas bos 65% a grysis y fia SK drog (11.5%) po pur dhrog (53%) rag an yeth. Pan veu govynnys pyth a dal bos gorthyp an gemeneth orth SK, 46% a leveris y kodh y hedhi ha 27% y woheles, gans an dus moy ha 60 bloodh hepken ow tybi y kodh oberi ganso.20
31% a worthebydhyon an sondyans a leveris y hwrussa an devnydh a SK yn Kernewek aga fellhe a’n yeth, hag ynwedh 54% a leveris y fiens i pellhes yn krev ha 23% pellhes tamm a by kowethas, asnodh po dyskador pynag ow tevnydhya SK.
An gorthyp a’n re a leveris bos aga godhvos a SK po “konnyk” po “da” o dampnus yn arbennik. Pubonan y’n bagas ma a worthebis y fia SK dregynnus rag Kernewek, y hwrussa an devnydh a SK gans pennfenten aga fellhe a’n bennfenten na yn krev hag y kodh dhyn hedhi an devnydh a SK rag Kernewek.
HONANIETH, LELDER HA DIVERSETH
Nyns esa Aristotelis Ioannis Paschalidis, ow skrifa a-barth UNESCO, ow kewsel yn komparek a-dro dhe yethow lyharivhes pan wrug ev y wovyn, mes an govyn a dhassen yn kreffa ragon: “Pygemmys koll a honanieth a vynnir sakrifia rag effeythuster?”21
Honanieth yw a’n moyha bri rag Kernewegoryon. Studhyans Ute Wimmer Reversing Language Shift: the Case of Cornish a henow “gweythres [an yeth] avel arwodh a honanieth kenedhlek” avel an nessa ughella skila (66%**) yn-mysk kowsoryon ha dyskoryon, fethys gans gonisogeth Kernow (80%) hepken.22 Yth havalsa hemma bos acheson solempnyans, mes pan vo SK keworrys, y teu ha bos peryl. Vincent Koc a Hyperlink a lever y hyll SK “kevri dre wall orth an gwannheans a yeth ha honanieth wonisogethel”.23
Ev a aswon ynwedh y hallsa awtomategi dyski po dinythi yeth “lehe an rychedh ha lelder hag a dheu a gowsoryon dhenel neb a dheg istoriow gonisogethel y’ga hows”. Yn hwir, peswar studhyans gwrys gans Pennskol Kaliforni Soth re dhiskwedhas bos devnydhya PYB dhe weres gans skrifa “kelmys orth dyfygyansow nosedhek yn diverseth yethel hag y hyll mellya gans an konvedhes brysoniethel ha kowethasel yw proviys gans yeth.”24
Ha hemm yw yn Sowsnek, onan a’n yethow an ryccha ha brassa y’n bys. Dismyk an effeyth war yeth byghanna kepar ha Kernewek—gans le a dhogvennans, le a gedhlow, sel kowsoryon munys hag ogas hag arghans mann—ha war y lies orgraf hag eghen yeth. Yn arbennik yn gettesten Kernewek, seulabrys yma kowsoryon Diwedhes ow strivya dhe vos gwelys avel vas gans gwartheyvans Kres. A dybyn y hwor SK an dyffrans? Heb preder, y hwra po kemyska puptra warbarth, ow sowdheni pubonan, po devnydhya Kres dhe fetha Diwedhes.
An gwruthyl a dhalgh herdhys gans SK Dinythus, dre favera yethow savonegys, a argyl an vansyans a rannyethow ranndiryel.25
Kresen woramontyorieth Barcelona
Nyns yw eghennow hepken yn peryl; SK a wodros beudhi Kernewek yn tien. Akordys yw Perlin y hallsa an platheans yethel a hwarva dres kansbledhynnyow yn Sowsnek hwarvos dres nos yn yeth lyharivhes gans SK orth an fronnow—dell via, ow pos gallosek a bassya Kernewek denel heb assay. Ev a venek prederow yn kever PYB ow rewi yeth yn hy le ha hogen ow settya pyth yw an styr a wodhvos an yeth, yn arbennik gans niverow munys a gowsoryon deythyek.26
Treylyansow leun a atal a liesha warlinen kepar ha nowodhow fug. Kowsoryon deythyek a’n yethow ma yw passyes avel bos “re gales dhe drovya”, komparys orth fordhow awtomategys a surheans kwalita hag yw disjunys yn tien a geskomunyans y’n bys gwir. Kynth yw possybyl rag kemenethow yeth brassa ha moy gallosek synsi an bottys ma dhe akont ha’ga devnydhya yn stratejek hogen, re es yw dismygi [yeth lyhariv] ow pos reverthys.26
Ross Perlin, Endangered Language Alliance
Heb kontrol hag yn diwla an gewri deknegieth, Kernewek synthesek a wra gornivera ha gorthrabellhe Kernewek denel.
SOVRANEDH KEDHLOW HA KOLONEGIETH
Sovranedh kedhlow teythyek yw an gwir gans [kenedhel teythyek] a woverna an kuntel, perghenogeth ha gweytha a’y hedhlow hy honan.27
Native Nations Institute
Byttegyns, yma gonisogethow teythyek hag usi owth oberi war geskowethyans moy ewnhynsek gans SK. Tek heb an kowr a res asnodhow, mes y as kemenethow gwitha sovranedh kedhlow war an gerthen wonisogethel hag yw aga yeth. Te Mana Raraunga, Rosweyth Sovranedh Kedhlow Māori, re wrug rol a bennrewlys rag an gwruthyl, devnydhya ha kevrenna a gedhlow Māori, ow ragwirhe an edhom a grefhe maystri rag Māori a-lemmyn hag a dheu.
I a venek poynt posek hag a dalvia bos konsidrys gans rach gans stywards a skians yethel ha gonisogethel: “Kedhlow ahanan, a-dro dhyn ha’gan asnodhow, yw kerthennow a bris. Pan vo maystri kellys, kales yw y dhaskemeres.”28 Ny dal gul erviransow yn skav po yn uskis; y hyllyn pupprys leverel “ea” mar kwrussyn leverel “na” kyns orth us sett kedhlow, mes ny yllyn nevra leverel “na” mar kwrussyn leverel “ea” seulabrys.
An desten SK, kepar ha pub le aral, yw leun a dus hag yw settys y’ga maneryow ha gans gwel pur drevesigel yn tidowl.29
Michael Running Wolf, First Languages AI Reality
Hemm yw pur bosek y’n gettesten a’n kontrol possybyl a gedhlow Kernewek gans korforethow gallosek a-ves. Estenegieth jatelydhek re beu molleth war gowethasow y’n amal emperourethek ha nyns yw kowethas Kernewek dyffrans, wosa enebi kansvledhynnyow a’y rychys hag asnodhow naturek ow pos destryppys ha gwerthys dre vras gans budh tus yn-mes a Gernow.
An lyver henwys Indigenous Data Sovereignty and Policy a verk lemmyn y hyllir gweles perthynyansow kedhlow avel “pesyans a’n argerdhow ha systemow-krysi isworwedhek a estennans, drogusyans, kuntellyans ha diberghenogeth re beu gwrys war boblansow Teythyek dres trevesigeth istorek.”30 An konvedhes estennek ma a gedhlow yw, dell verkons, hevelebys a-der goderrys gans tyli pobel rag aga hedhlow.
Wostiwedh, res yw ma na vo agan yeth gorrys yn diwla a-ves routys gans pennrewlys perghenogel na as dhyn sovranedh lowr a onan a’gan asnodhow naturel an moyha posek: agan yeth. Res yw dhyn kavos pennrewlys kedhlow ygor, a-der plegya orth kontrol korforethel. Res yw dhyn lewya ha gidya an devnydh a’gan kedhlow, a-der y usya erbynn agan lesow ha rag pocketys tek bras.
A-der drehedhes an arwithans a davosow avel kudyn teknegiethel, my a dyb bos res dhe gemenethow teythyek bos reythhes yn politek, po der arghasans a wovernansow po dre dhifresyansow laghel dhe dhevnydhya aga yethow.31
Dr. Fintan Mallory, Pennskol Durham
Res yw dhyn ragwirhe yeth-avel-kemeneth ha hwilas devnydh ygor, ewnhynsek hag ethegel a’gan kerthennow yeth, ertach ha gonisogethel. Res yw dhyn goheles tybi a SK avel an hus mayth ambos ha kevarghewi yn hwithrans selyek, lewys gans agan kemeneth. Ny wra korforethow agan selwel ha, hogen, i a yll agan shyndya.
NYNS EUS KERNEWEK WAR BLANET MAROW
Governansow ha kevalav ollvysel […] yw omres dhe ideologieth marghas ‘rydh’ moy es dell yns omres dhe sewena kemenethow, pobel ha’n planet.32
Cymdeithas yr Iaith Maniffesto 2022
An brassa rann a vreusyansow a SK a wrussa meneges hemma seulabrys. Onan a’n argyansow brassa yw erbynn SK Dinythus, mes rag own bos ankoth dhis, ni a wra mires orth an chif boyntys.
Res yw bos evadow an dowr goyeynhe pub kresen kedhlow SK. Y kollenk an dowr ma. Pennskol Kaliforni re dherivas “y hallsa demond dowr ollvysel SK hedhes 4.2-6.6 bilvil metrow kubek erbynn 2027. Henn yw moy es 50 kansran a us dowr bledhynnyek an RU yn 2023.”33 Y kettermyn, an Desedhek Ollvysel Erbysieth Dowr a dheklaryas “barras dowr ow tardha yn uskis” ma na dal Kernewek kevri dhodho.34
Ni re dheuth ha bos yn hwir omres dhe deknegiethow privedh gwrys ha kontrolys gans dornas a gompanis diskler [hag] a hevel bos mygyl dre vras orth an sewyansow sosyel a’ga gwriansow ha kevri yn ispoyntel marnas mars yns i konstrinys gans rewlys an wovernans dhe wellhe aga imach poblek.35
Iker Erdocia, Pennskol Sita Dulyn
Yma edhom dhe SK a vynsow kowrek a galesweyth orth kost palas monyow tanow. Kales yw estenna ha purhe an re ma hag yma kostow kerghynedhel ha sosyel poos. Estennys yns i yn fenowgh a hwelyow yn powyow gans difresyansow lakka rag lavur ha’n kerghynnedh. Reset a lever “yn fenowgh y hwra kemenethow yw trigys yn ogas dhe’n hwelyow, yn fenowgh bagasow lyhariv po teythyek, enebi gwethheans an tir, defolyans an dowr hag abusyans gwiryow denel. Meur a hemma a yll bos kelmys yn tidro orth an galesweyth SK.”36 Pan yw an galesweyth kegys yn sertan hag euver, ena tewlys yw avel e-wast yn kemenethow boghosek. Res yw nyns yw an avonsyans possybyl a Gernewek orth kost agan kemenethow hwor lyhariv ha teythyek.
Ynwedh res yw myns hujes a nerth rag trenya SK, yn skon martesen an keth myns ha pow byghan37 hag yma ol troos karbon kowrek.38 Kler yw—der usadow dowr, diwysyans estennek, konsumyans nerth hag ol troos karbon—bos SK yeyn nowodhow rag kerghynnedh ow strivya a’n planet mayth on ni trigys warnodho ha nyns eus Kernewek war blanet marow.
GUL DHE SK BOS EKS-PAPYNJAY
A-der gul dhe yethow lyhariv bos moy hedhadow, lemmyn yma SK ow kwruthyl tardhek pupprys owth omlesa rag studhyoryon ha kowsoryon a’n yethow ma dhe wolya.39
mit technology review
Ni re glewas a’n anwirhevelepter efan a wul dhe SK gallos mimya Kernewek yn golow an kostys yn kedhlow, ober, termyn ha teknegieth. Ni re gonsidras lycklod an dewisynter dispresyans yeyn po askorras-aspia ha’n posekter a sovranedh kedhlow. Ni re redyas a-dro dhe’n effeythyow war vewnansow Kernewegoryon, keffrys ha’n kostys katastrofek rag an kerghynnedh ha poblow teythyek.
Ni re dhyskas y hwra platheans yethel gans SK boghosekhe y destennow ha fatel yll SK martesen ervira a’gan parth fatel godh dh’agan yeth oberi. Ni re welas an anwoheladewder a yeth avel denel ha’n peryllyow a wul ‘dyskoryon’ na yll dyski ha ‘kowsoryon’ na yll kewsel. Ni re welas an peryllyow orth bri ha fydhyans rag kowethasow a wrussa palas an pyth hag yw gwelys avel ‘skomblans’.
Ni re glewas prag y fia omblegya orth an jagganat a SK error rag Kernewek ha dell na vynn agan kemeneth skoodhya gorra an skoos a-dhyworthyn. Yn y le, res yw dhyn batalyas. Res yw dhyn gul dhe Gernewek bos spas mar rydh a skomblans dell yll bos, res yw adhyski orth botlapyoryon yn dyski ha devnydh yeth yn ethegel hag yn effeythus, res yw goheles tybi wortaswerth.
Res yw dhyn gul dh’agan yeth bos parth heb SK, rosweyth a dus fydhyadow ha’ga gwriansow denel, drehevys war lelder, kemeneth, assay ha trest: Kernewek hag yw a-barth an bobel, a’n bobel ha gans an bobel.
Niwlen Ster
Notennow
* A prime example is the laughably-unaffordable restaurant RenMor, which The Headland Hotel thinks is a version of “Re’n Mor”, which they believe means “by the sea” as in “next to the sea” but actually means “by the sea!” like saying “by Zeus!”. This is both hilarious and enraging.
** A figure perhaps lower than it should be if you consider that many of the “emotional motives” which were not counted in this category, such as “I’m Cornish, what better reason do you need?”, do also refer to identity.
FENTENNOW
1. Judah, J. (2025) How AI and Wikipedia have sent vulnerable languages into a doom spiral, MIT Technology Review.
2. Ackermann, A. (2023) When AI doesn’t speak your language, Coda.
3. Crichton, D. (2024) AI and the Death of Human Languages, Lux.
4. Lamb, W. (2024). Could Artificial Intelligence save Scottish Gaelic?, The University of Edinburgh.
5. Dencik, L. (/2025) AI Inequalities: Minority Languages, TUC Cymru.
6. Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Microsoft Research, India. (2020). The State and Fate of Linguistic Diversity and Inclusion in the NLP World. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
7. Ackermann, A. (op cit)
8. McLoughlin, I. (2018) How to teach AI to speak Welsh (and other minority languages), The Conversation.
9. Mallory, F. (2025) RISE UP Panel Discussion & Q&A: What AI Can and Cannot Do for Minoritised Languages, YouTube.
10. Perlin, R. (2024) AI Won’t Protect Endangered Languages, The Dial.
11. RISE UP (2025) #4 RISE UP Event Summary: What AI Can and Cannot Do For Minoritised Languages, RISE UP.
12. Mallory, F. (2024) European Day of Languages: Will lesser spoken languages soon only be kept alive by AI technology? Durham University.
13. Bender, E., Gebru, T., McMillan-Major, A., & Mitchell, M. (2021) On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
14. Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025) The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers. Microsoft.
15. Perlin, R. (op cit)
16. Judah, J. (op cit)
17. Abbruzzese, J., & Wile, R. (2025) Is an AI backlash brewing? What ‘clanker’ says about growing frustrations with emerging tech, NBC News.
18. Webster, K. (2025) Why Using ChatGPT at Work Could Hurt Your Reputation, Inc. Magazine.
19. Herrman, J. (2024) Is That AI? Or Does It Just Suck?, Intelligencer.
20. Wilson, L. (2025) Skians Kreftus ha Kernewek/Artificial Intelligence and Cornish
21. Paschalidis, A. I. (2025) AI and the great linguistic flattening, UNESCO.
22. Wimmer, U. (2010). Reversing Language Shift: the Case of Cornish. Cornish Language Board, p. 113
23. Koc, V. (2025) Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges, ResearchGate.
24. Sourati, Z., Karimi-Malekabadi, F., & Ozcan, M. (2025) The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Models, ResearchGate.
25. Melero, M. (2024) The Future of Language (and Cultural) Diversity in the Age of AI, CLARIN.
26. Perlin, R. (op cit)
27. Russo Carroll, S., Rodriguez Lonebear, D., & Martinez, A. (2017). Data Governance for Native Nation Rebuilding, Native Nations Institute.
28. Te Mana Raraunga. (2018). Frequently Asked Questions, Te Mana Raraunga.
29. Ackermann, A. (op cit)
30. Walter, M., Kukutai, T., Carroll, S. R., & Rodriguez-Lonebear, D. (Eds.). (2020). Indigenous Data Sovereignty and Policy. Taylor & Francis, p. 24
31. Mallory, F. (op cit)
32. Cymdeithas yr Iaith (2022) Cymru Rydd, Cymru Werdd, Cymru Gymraeg., p. 27
33. O’Sullivan, L. (2025). How AI’s Failure on Linguistic Diversity is Deepening Global Inequality, RESET – Digital for Good.
34. Harvey, F. (2024). Global water crisis leaves half of world food production at risk in next 25 years, The Guardian.
35. Erdocia, I., Migge, B., & Schneider, B. (2024). Language is not a data set—Why overcoming ideologies of dataism is more important than ever in the age of AI. Journal of Sociolinguistics, 28(5), p. 23
36. O’Sullivan, L. (op cit)
37. Erdenesanaa, D. (2023) A.I. Could Soon Need as Much Electricity as an Entire Country, The New York Times
38. Heikkilä, M. (2022) We’re getting a better idea of AI’s true carbon footprint, MIT Technology Review.
39. Judah, J. (op cit)#4 #AI #ArtificialIntelligence #Breus #Cornish #Cornwall #data #generativeAI #history #jynn #kedhlow #Kernewek #Kernow #Kernowek #LLM #machine #PYB #SK #SKDinythus #SkiansKreftus #Sordya
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Turning Saffron into Slop – Treylya Safran yn Skomblans
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
Note: Artificial Intelligence (AI) has come to be synonymous with Generative AI (GenAI) and with Large Language Models (LLMs), such as ChatGPT, in common parlance. Unless explicitly stated, I use the terms interchangeably.
Kernewek is under attack. The attacker? Machine-made rubbish. Fresh from companies dictionary-bashing to make terrible ‘translations’ for their black-and-gold-washing brandification of Kernow*, the shoddiness has spiralled.
Error-riddled AI ‘Kernewek textbooks’ have appeared on Amazon, by ‘authors’ who are at best well-meaning but harmful and at worst out to exploit us. Worse, a prominent crackpot is ‘translating’ conspiracy theories into ‘Cornish’ en masse. It’s not just nonsensical; it ties our language to fascism faster than we, making content by hand, can work to untie it.
There are those who believe that the best defence is to put down our shield and join the opposing forces: to ‘buy in’ to AI in the hope of coming out the other side with a useful tool for the language and a stronger community. Such hopes must be abandoned. What follows is a look why this approach is wrong-headed, as evidenced by universities, activists and indigenous groups.
LOW-RESOURCES AND LINGUISTIC TYPOLOGY
Simply adding a language to an AI model leads to a spike in poor-quality articles, drowning out quality writing by humans. AI has “industrialized the acts of destruction—which affect vulnerable languages most, since AI translations are typically far less reliable for them.”1 Wikipedia editors from varied languages evidence that machine translation tools have made it easier than ever before to create shoddy articles in minoritised languages, causing massive damage in minutes. AI leads to non-speakers producing much longer, truthier rubbish, Sámi computational linguistics expert Trond Trosterud notes: “the problem [is] that they are armed with Google Translate. Earlier they were armed only with dictionaries.”1
Kernewek, like all but 60 of the world’s roughly 7,000 languages, is designated “low-resource”, meaning it lacks sufficient data to train a machine.2 It is tempting, therefore, to assume that the solution is to provide more data. However, training an LLM requires petabytes of text, audio and video—manually categorised and in a machine-readable format—a vast trove that Kernewek simply does not have.3 Professor Will Lamb, Chair of Gaelic Ethnology and Linguistics at Edinburgh University, speaks of “millions of work hours devoted to just one aspect” of a working AI.4
Even if ChatGPT is trained on another language than English, the time and labour required may make it largely unviable. Current assessments of the performance of ChatGPT for different languages have shown that it performs worse in all tasks.5
Prof. Lina Dencik, Data Justice Lab
Furthermore, the amount of data and work is not the only barrier; at issue is the nature of the language itself. Microsoft has found that languages such as Breton—and thus Kernewek—cause a high rate of errors distinct from the size of their dataset, due to grammatical features, such as mutation, not present in well-sourced languages. As such, they remain poor without significant additional work.6 Essentially, simply adding more Kernewek may not help. Thus, engaging with AI is, for Kernewek, to tie ourselves to slop.
Noten: Skians Kreftus (SK) re dheuth ha bos kesstyr gans SK Dinythus (SKDin) ha gans Patronyow Yeth Bras (PYB), kepar ha ChatGPT, yn lavar kemmyn. Marnas bos menegys yn kler, my a us an termys yn keschanjyadow.
Kernewek yw yn-dann omsettyans. An omsettyer? Atal gwrys dre jynn. Nowydh devedhys a gompanis ow pylla gerlyvrow rag gul ‘treylyansow’ euthyk rag aga merkegyans yethwolghi a Gernow*, an pilyekter re wrug pesya.
‘Dysklyvrow’ ‘Kernewek’ gwallblagys re apperyas war Amazon, gans ‘awtours’ neb yw teg aga thowl dhe’n gwella ha drogusus aga hwans dhe’n gwettha. Lakka, yma koyntwas a vri ow ‘treylya’ tybiethow kesplottyans dhe ‘Gernewek’ yn routh. Nyns yw gocki hepken; y kelm agan yeth orth faskorieth uskissa es dell yllyn, dre wul dalgh dre leuv, oberi dh’y digelmi.
Yma nebes a grys bos agan gwella difres gorra an skoos dhyworthyn ha junya an ostys er agan pynn: dhe ‘unverhe’ gans SK gans govenek dos yn-mes gans toul dhe les rag an yeth ha kemeneth kreffa. Res yw hepkor govenegow a’n par na. An pyth hag a sew a vir orth prag yth yw an devedhyans ma penn-gam, dell yw dustunys gans pennskolyow, gweythresoryon ha bagasow teythyek.
ASNODHOW ISL HA TIPOLOGIETH YETHEL
Keworra yeth yn sempel orth patron SK a led orth spik yn erthyglow drog aga kwalita, ow peudhi skrif a gwalita gans tus. SK re wrug “diwysyansegi an aktys diswrians—hag a nas yethow goliadow an moyha, drefen bos treylyansow SK lieskweyth le lel yn tipek ragdha.”1 Golegydhyon Wikipedia a yethow divers a re dustuni re wrug medhelweyth-treylya y wul bos esya dell veu bythkweth kyns gwruthyl erthyglow pilyek yn yethow lyharivhes, ow kawsya damach kowrek yn mynysennow. SK a led orth digowsoryon owth askorra atal lieskweyth hirra ha gwirekka, konnyk yethonieth reknansek Sámi Trond Trosterud a not: “an kudyn [yw] aga bos ervys gans Google Translate. A-varra nyns ens ervys marnas gans gerlyvrow.”1
Kernewek, kepar hag oll marnas 60 a ogas lowr 7,000 yeth a’n bys, yw klassys avel “isel y asnodhow”, ow styrya nag eus dhodho kedhlow lowr dhe drenya jynn.2 Rakhenna, dynyek yw desevos bos an assoylyans profya moy a gedhlow. Byttegyns, res yw petavaytys a dekst, son ha gwydhyow—klassys dre leuv hag yn furvas redyadow gans jynn— dhe drenya PYB, tresorva efan nag eus dhe Gernewek yn sempel.3 Y kews Professor Will Lamb, Kaderyer Ethnologieth ha Yethonieth Wodhalek orth Pennskol Karedin, a “vilvilyow a ourys ober sakrys orth unn wedh hepken” a SK owth oberi.4
Hogen mars yw ChatGPT trenys war yeth a-der Sowsnek, an termyn hag ober yw res a styr y vos martesen anhewul dre vras. Arvreusyansow a-lemmyn a berformyans a ChatGPT rag yethow dyffrans re dhiskwedhas y perform gweth yn oberennow oll.5
Prof. Lina Dencik, Data Justice Lab
Pella, nyns yw an myns a gedhlow hag ober an unsel lett; a vern yw natur an yeth y honan. Microsoft re drovyas y kaws yethow kepar ha Bretonek—hag ytho Kernewek—kevradh ughel a wallow diblans a vraster aga sett kedhlow, drefen nasyow gramasek, kepar ha treylyansow, nag usi kevys yn yethow ughel aga asnodhow. Yndella, i a bes orth bos drog heb meur a ober keworransel.6 Yn essensek, possybyl yw ny wra keworra moy a Gernewek yn sempel gweres. Yndelma, oberi gans SK yw, rag Kernewek, omgelmi orth skomblans.
CORNISH UNDER CAPITALISM
But surely we can improve things over time? It will take a lot of help from AI companies, but it will be worth it. Sadly, Gabriel Nicholas, a research fellow at the Center for Democracy and Technology, has found that once a tech company has established basic capabilities for a language, they pat themselves on the back and move on.7
Big tech companies are just that: companies. They exist to make a profit. Unfortunately, a market dominated by big languages gives them no incentive to invest in improvements for small ones.
All of the speech technology, smart homes and voice interaction systems used today are the products of commercial research. To put it bluntly, they exist to either make money from your data, to sell you more goods and services, or to influence your thinking. None of this AI exists for the public good. […] Unless there is a strong enough economic argument, don’t expect big companies to rush into producing Welsh, Gaelic or Cornish speech systems.8
Prof. Ian McLoughlin, University of Kent
Should they decide that a Kernewek AI is a viable profit-making enterprise, our situation may even be worse than abandonment. As Dr. Fintan Mallory remarks, the dominant means of profit for privately-funded AI enterprises is to convert their tools into surveillance devices.9 As Kernewek is currently one of the UK’s only languages which is not currently easily surveillable, this poses a huge risk to Kernewek activism and the fight for self-determination in a state that seeks to criminalise dissent.
While we’re on the subject of Kernewek and its position under capitalism, let’s consider the human cost. I lost my 13-year career in language to AI as soon as English output became viable enough to excuse not paying a human. In the unlikely instance that we achieve an AI that can produce quality Kernewek, why would anyone bother paying speakers? The idea of AI sucking all the life out of my heritage language when we are struggling to survive as-is is appalling.
Simply put, profit is antithetical to people. While AI is the new favourite toy of profit, it will be antithetical to people. And a language is its people.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Combinations of characters on a screen mean nothing without agency and intention.10
Ross Perlin, Endangered Language Alliance
While language is not unique to humans, it is one of the chief parts of being human. It cannot be reduced to mere data, but is a highly social process.11 We all know how synthetic customer support via robot sounds or how AI fails to pick up nuance. As Dr. Mallory comments, “Language [is] something more like the soul of a community. You can’t store this in a machine. You can’t solve a human problem like linguicide with a view of language that removes the human component.”12
AI cannot comprehend Kernewek or any other language. It is a stochastic parrot: predicting what word is likely to follow the previous one.13 It cannot understand us. It cannot intend anything. If it tells you it feels delighted to help you, it is lying. I want our community to grow, but one hundred ‘Cornish-speaking’ computers do not add to it. One human does—bringing ideas and hopes and fears and foibles—and I do not think the Kernewek ‘speaking’ computers will add even one human to our community.
Worse, if it does, there is evidence from Microsoft to suggest that the use of GenAI on language tasks, even once a week, impairs cognitive ability to learn, leading to decreased engagement with the topic, overreliance on the technology and hobbled skills in independent problem-solving.14 By using AI tools to ‘teach’ a learner Kernewek, we may in fact be impairing their ability to learn the language at all without this crutch. We will make regurgitators in place of speakers.
Perlin also emphasises the human element, saying that when we hold community central to our languages, as we do, the stochastic parrot can feel like a violation.15 At the moment, I can tell when someone is using AI ‘Kernewek’ to me. The idea that one day I will not know when an outsider—someone I would welcome if they took up a book or a class—is puppeting my ancestors’ jaws and speaking through them is ghoulish. It has the instant sting of colonialism, of appropriation when one could appreciate, of parroting when one could join our chorus.
Hawai’ian scholar Ha‘alilio Solomon agrees: “It is painful, because it reminds us of all the times that our culture and language has been appropriated. We have been fighting tooth and nail in an uphill climb for language revitalization.[…] People are going to think that this is an accurate representation of the Hawaiian language.”16
TRUST AND COMMUNITY FEELING
The anti-machine backlash has long been simmering but is now seemingly breaking to the surface.17
NBC NEWS
The explosion of insults for AI itself (clanker, tinskin, toaster), its output (slop, dross, brainrot) and its users (slopper, groksucker, botlicker, second-hand thinker)—as well as others more clearly based on real-world slurs than I am comfortable to include—tells a tale of the general attitude of distrust and disgust towards the technology and its use on anglophone and other majority language internet.18 While the attitude among tech bros and corporates remains bombastic, for the general public AI is “becoming interchangeable with things that sort of suck.”19
Further, it’s not just majority languages with this negative view of AI as taint. A quick sampling of social media comments and likes regarding AI and Scottish Gaelic by Professor Lamb showed a split of 54% negative, 33% positive and 13% neutral. (Lamb, 2024) The sentiment of the top-rated negative comment was that AI is harmful and the second-highest that AI should be kept away from heritage languages.
What are we telling our descendants? That our language and culture isn’t worth the personal effort? That’s how I might read it, if I were them.20
Kernewek survey respondent
Kernewek paints an even starker picture, especially among younger and more technologically-savvy learners and speakers. A survey on Cornish Discord and Whatsapp found that 65% felt AI would be bad (11.5%) or very bad (53%) for the language. When asked what the community response should be to AI, 46% said we should prevent it and 27% avoid it, with only over-60s thinking that we should work with it.20
31% of respondents said using AI in Kernewek would cause them to feel estranged from the language, while 54% said that they would feel strongly estranged and 23% a little estranged from any organisation, resource or teacher using AI.
The response from those who gave their knowledge of AI as either “expert” or “good” was particularly damning. Everyone in this group responded that AI would be harmful for the language, that the use of AI would estrange them from a source strongly and that we should prevent the use of AI for Kernewek.
IDENTITY, AUTHENTICITY AND DIVERSITY
Aristotelis Ioannis Paschalidis, writing for UNESCO, was not speaking specifically about minoritised languages when he asked this, but the question resonates even more strongly for us: “How much loss of identity is one willing to sacrifice for efficiency?”21
Identity is of paramount importance to Kernewek speakers. Ute Wimmer’s study Reversing Language Shift: the Case of Cornish identified the language’s “function as a symbol of national identity” as the second highest motive (66%**) among speakers and learners, beaten only by Cornish culture (80%).22 This would seem cause for celebration, but when AI is added to the mix, it becomes a risk. Vincent Koc of Hyperlink states that AI can “inadvertently contribute to the dilution of language and cultural identity.”23
He also identifies that automating language learning or generation “may diminish the richness and authenticity that comes from human speakers who carry cultural histories in their speech.” Indeed, four studies by the University of Southern California have shown that using LLMs to assist writing “is linked to notable declines in linguistic diversity and may interfere with the societal and psychological insights language provides.”24
This is in English, one of the richest and largest languages in the world. Imagine the possible impact on a smaller language like Kernewek—with less documentation, less data, a tiny speakerbase and basically no money—and on its many language varieties and orthographies. Particular to the Kernewek context, Late speakers are already struggling to be seen as valid under the dominance of Middle. Do we think AI knows the difference? Thoughtlessly, it will either mix everything together, confusing everyone, or it will use Middle to overwhelm Late.
Generative AI-driven content creation, by favoring standardized languages, risks the disappearance of regional dialects.25
Barcelona supercomputing Center ….
Not only are varieties at risk; AI threatens to drown Kernewek as a whole. Perlin agrees that the linguistic flattening that occurred over centuries in English could manifest overnight in a minoritised language with AI at the helm—as it would be, being able to effortlessly outstrip human Kernewek. He raises concerns of LLMs freezing a language in place and even defining what it means to know the language, especially with low numbers of native speakers.26
Garbage translations multiply online like fake news. Native speakers of the languages in question are bypassed as being “too hard to find,” compared with automated methods of vetting that are completely disconnected from real-life communication. While larger and more powerful language communities may be able to hold the bots to account and even make strategic use of them, it is all too easy to imagine [a minority language] being overwhelmed.26
Ross Perlin, Endangered Language Alliance
Uncontrolled and in the hands of tech giants, synthetic Kernewek will outnumber and outmanoeuvre human Kernewek.
DATA SOVEREIGNTY AND COLONIALISM
Indigenous data sovereignty is the right of [an indigenous nation] to govern the collection, ownership, and application of its own data.27
Native Nations Institute
There are, however, indigenous cultures that are working on a more equitable relationship with AI. Tech without the giant requires resources, but it allows communities to retain data sovereignty over the cultural asset that is their language. Te Mana Raraunga, the Māori Data Sovereignty Network, has created a list of principles for the creation, use and sharing of Māori data, prioritising the need to enhance control for current and future Māori.
They raise a key point that should be considered carefully by stewards of linguistic and cultural knowledge: “Data from us, and about us and our resources, are valuable assets. Once control of it is lost, it is difficult to regain.”28 Decisions must not be taken lightly or hastily; we can always say “yes” if we have previously said “no” to a particular dataset’s use, but can never say “no” if we have already said “yes”.
The AI field, like any other space, is occupied by people who are set in their ways and unintentionally have a very colonial perspective.29
Michael Running Wolf, First Languages AI Reality
This is vital in the context of the potential control of Kernewek data by powerful external corporations. Capitalist extractivism has long been a bane on societies in the imperial periphery and our Cornish society is no different, having faced centuries of its wealth and natural resources being stripped and sold by and large for the profit of those outside Cornwall.
The book Indigenous Data Sovereignty and Policy notes that current data relations can be seen as “a continuation of the processes and underlying belief systems of extraction, exploitation, accumulation and dispossession that have been visited on Indigenous populations through historical colonialism.”30 This extractive understanding of information is, they note, not disrupted but rather replicated by paying people for their data.
Ultimately, our language must not lie in outside hands governed by proprietary principles that do not allow us sufficient sovereignty over one of our most valuable natural resources: our language. We must have open data principles, not bow to corporate control. We must steer and steward the use of our data, rather than expose it to use against our interests and for the pockets of big tech.
Rather than approaching language preservation as a technical problem, I think indigenous communities need to be politically empowered, whether that be funding from governments or legal protections to use their languages.31
Dr. Fintan Mallory, Durham University
We must prioritise language-as-community and seek open, equitable and ethical use of our language, heritage and other cultural assets. We must avoid thinking of AI as the magic that it promises and invest in basic research, driven by our own community. Corporations will not save us and, indeed, may do us great harm.
NO CORNISH ON A DEAD PLANET
Global capitalism and governments […] are addicted to ‘free’ market ideology over the wellbeing of communities, people and the planet.32
Cymdeithas yr Iaith Maniffesto 2022
Honestly, most takedowns of AI would have hit this point already. It’s one of the main arguments against Generative AI, but in case you’re not familiar with it, we will briefly look over the main points.
Water used in cooling AI data centers must be drinkable water. AI guzzles this water. The University of California has reported that “global water demand from AI could reach 4.2-6.6 billion cubic meters by 2027. That exceeds 50 percent of the UK’s annual water use in 2023.”33 All this while the Global Commission on the Economics of Water has declared “a rapidly accelerating water crisis” to which Kernewek should not be contributing.34
We have become utterly dependent on private technologies manufactured and controlled by a handful of opaque companies [who] appear mostly indifferent to the social consequences of their activities and only invest minimally if obliged by government regulations to enhance their public image.35
Iker Erdocia, Dublin City University
AI requires vast quantities of hardware at the cost of mining rare earth minerals. These are difficult to extract and purify and come with heavy environmental and social costs. They are often extracted from mines in countries with poorer environmental and labour protections. Reset states that “communities living near these mines, often indigenous or minority groups, regularly face land degradation, water contamination and human rights abuses. Much of this can be directly linked to the AI hardware.”36 When the hardware inevitably cooks and is useless, it is then thrown out as e-waste into poor communities. The potential advancement of Kernewek must not come at the expense of our sister indigenous and minority communities.
Training an also AI requires huge amounts of energy, soon perhaps as much as a small country37 and has an enormous carbon footprint.38 What is clear is that—through water usage, extractive industry, energy consumption and carbon footprint—AI is bad news for the struggling environment of the planet we live on and there is no Cornish on a dead planet.
MAKING AI AN EX-PARROT
Rather than making minority languages more accessible, AI is now creating an ever expanding minefield for students and speakers of those languages to navigate.39
mit technology review
We have heard of the vast improbability of getting AI to be able to mimic Kernewek in light of the costs in data, work, time and technology. We have considered the likely choice of cold negligence or surveillance product and the importance of data sovereignty. We have read about the effects on the livelihoods of Cornish speakers, as well as the the catastrophic costs to the environment and indigenous peoples.
We have learned that linguistic flattening by AI impoverishes its subjects and how AI may decide for us how our language must operate. We have seen the inescapability of language as human and the risks of creating ‘learners’ who cannot learn and ‘speakers’ who cannot speak. We have seen the dangers to reputation and trust for any organisation who would shovel what is seen as ‘slop’.
We have heard why giving in to the juggernaut of AI would be a mistake for Kernewek and how our community does not support our laying down of the shield. Instead, we must fight. We must make Kernewek a space as free of slop as possible, we must educate botlickers into ethical and effective language learning and use, we must avoid second-hand thinking.
We must make our language a no AI zone, a network of reliable humans and their human creations, built on authenticity, community, effort and trust: a Kernewek for the people, of the people and by the people.
KERNEWEK YN-DANN GEVALAV
Mes yn sur y hyllyn ni gwellhe taklow dres termyn? Y fydh res meur a weres a gompanis SK, mes y talvia dhyn. Yn trist, Gabriel Nicholas, kesvroder hwithrans orth an Center for Democracy and Technology, re drovyas pan wrug kompani tek fondya gallosow selyek rag unn yeth, i a omgeslowenha yn ughel hag ena movya yn-rag.7
Kompanis tek bras yw yndella poran: kompanis. Ymons i ena rag gwaynya budh. Y’n gwettha prys, ny wra marghas rewlys gans yethow bras ri kentryn dhe gevarghewi yn gwellhe rag an re byghan.
Oll a’n deknegieth kows, chiow konnyk ha systemow ynterweythres lev usys hedhyw yw an askorrasow a hwithrans kenwerthel. Dhe vos sogh, yth yns i po rag dendyl arghans a’th kedhlow, po gwertha gwara ha gonisyow, po delenwel dha dybyansow. Nyns yw tra vyth a’n SK ma rag an les kemmyn. […] Mar nag eus argyans erbysek krev lowr, na wra gwaytya kompanis bras dhe fyski dhe askorra systemow kows Kembrek, Godhalek po Kernewek.8
Prof. Ian McLoughlin, pennskol kint
Ha mars ervirons bos SK Kernewek aventur a yll gwaynya budh, possybyl yw bos agan studh gweth ages dell via gans forsakyans. Dell lever Dr. Fintan Mallor, an fordh vrassa a waynya budh rag kompanis SK arghesys yn privedh yw kedreylya aga thoulys yn devisyow aspians.9 Drefen bos Kernewek onan a’n yethow boghes y’n RU nag yw aspiadow yn es y’n eur ma, hemm yw peryl kowrek rag gweythresieth Kernewek ha’gan strif a-barth omdhetermyans yn stat a vynn galweythegi dissent.
Ha ni ow tochya Kernewek ha’y savla yn-dann gevalav, gwren ni mires orth an kost denel. My a gellis ow soodh 13 bloodh yn yethow dhe SK kettooth ha dell veu eskorrans Sowsnek hewul lowr dhe askusya sevel orth tyli den. Y’n kas diwirhaval may kevyn SK hag a yll askorra Kernewek da, prag y hwrussa nebonan omankombra ow pe kowser? An tybyans a SK ow tenna oll an bewnans a’m taves ertach ha ni ow kwynnel dhe dreusvewa dell on yw skruthus.
Yn sempel, budh yw gorthenebel orth tus. Hedre vo SK an degen nowydh flamm a vudh, y fydh gorthenebel orth tus. Ha yeth yw hy thus.
KENEDHEL HEB YETH, KENEDHEL HEB KOLON
Nyns eus styr dhe gesunyansow a lytherennow war skrin heb dewis ha heb mynnas.10
Ross Perlin, Endangered Language Alliance
Kyn nag yw yeth dibarow dhe dhensys, onan a’n rannow chif a vos denel yw. Ny yll bos lehes dhe gedhlow hepken, mes yth yw argerdh sosyel dres eghen.11 Ni oll a wor py mar synthesek y sen skoodhyans prener der SK po fatel yll SK fyllel orth konvedhes arliwyow. Dell gampol Dr. Mallory, “Yeth [yw] neppyth moy kepar hag enev a gemeneth. Ny yllir gwitha hemma yn jynn. Ny yllir assoylya kudyn denel kepar ha yethladhans gans gwel a yeth hag a remov an gerann denel.”12
Ny yll SK konvedhes Kernewek po taves vyth aral. Papynjay chonsus yw: y targan py ger yw gwirhaval wosa an huni kyns.13 Ny yll agan konvedhes. Ny yll mynnes tra vyth. Mar kwra derivas orthis y vos pes da dha weres, gow yw. My a vynn agan kemeneth dhe devi, mes ny wra kans jynn-amontya a yll ‘kewsel Kernewek’ keworra orti. Y hwra unn den—ow tri tybyansow ha govenegow hag ownow ha gwanderyow—ha ny dybav y hwra an jynnys-amontya kernwegorek keworra unn den hogen orth agan kemeneth.
Gwettha, mar kwra, yma dustuni a-dhyworth Microsoft hag a brof y hwra an devnydh a SKDin war oberennow yeth, unweyth an seythen hogen, aperya gallos godhvosel a dhyski, ow ledya orth omworrans lehes gans an desten, gorfydhyans y’n deknegieth ha sleyneth sprallys a assoylya kudynnow yn anserghek.14 Der usya toulys SK dhe ‘dhyski’ Kernewek, possybyl yw ni dhe shyndya gallos dyski an yeth vytholl heb an kroch ma. Ni a wra gul mimyoryon yn le Kernewegoryon.
Ynwedh Perlin a boslev an elven dhenel, ow leverel pan wren ni synsi kemeneth avel kres agan yethow, dell wren, an papynjay chonsus a yll bos klewys kepar ha defolyans.15 Y’n eur ma, my a aswon pan eus nebonan owth usya ‘Kernewek’ SK dhymm. An tybyans ny wrav vy unn jydh godhvos pan eus estren—nebonan a wrussen vy dynerghi mar pe lyver po klass ganses—ow popettya diwawen ow hengerens ha kewsel dresta yw bedhrosus. Yma dhe’n dra an wan dhistowgh a drevesigeth, a berghenegyans pan yllir gwerthveurhe, a bapynjaya pan yllir junya agan kesgan.
Unver yw skolheyk Hawai’i henwys Noah Ha‘alilio Solomon: “Ankensi yw, drefen ni dhe vos kofhes a’n prysyow oll re beu agan gonisogeth ha yeth perghenegys. Ni re beu owth omladh dre dhens hag ewines yn batel gales a-barth dasvewheans yeth.[…] Y hwra pobel krysi bos hemma representyans ewn a’n yeth a Hawai’i.”16
TREST HAG OMGLEWANS AN GEMENETH
Hir re beu an kil-lash gorthjynn ow kovryjyon mes lemmyn yma va ow terri an arenep dell hevel.17
NBC NEWS
Tardh an arvedhennow rag SK y honan (clanker, tinskin, toaster), y askorras (slop, dross, brainrot) ha’y usyoryon (slopper, groksucker, botlicker, second-hand thinker)—keffrys hag erel selys moy yn kler war geryow kas gwir dell ov attes gans aga heworra—a re hwedhel a stons ollgemmyn a wogrys ha divlases war-tu hag an deknegieth ha’y devnydh war an kesrosweyth Sowsnek ha yethow bras erel.18 Kynth yw an stons yn-mysk gwesyon dek ha korforeth hwath gwresek, rag an boblek gemmyn y hwra SK “dos ha bos keschanjyadow gans taklow tamm kawgh.”19
Pella, nyns yw marnas yethow moyhariv gans an gwel negedhek ma a SK avel podrek. Sampel uskis a gampollow media sosyel ha meusi ow tochya SK ha Godhalek Alban gans Professor Lamb a dhiskwedhas fals a 54% negedhek, 33% posedhek ha 13% heptu. (Lamb, 2024) Sentiment an kampol negedhek an moyha talvesys o bos SK dregynnus hag an nessa y talvia dhyn lettya SK rag kestav gans tavosow ertach.
Pyth eson ni ow leverel orth agan diyskynysi? Ny dal agan yeth ha gonisogeth an strivyans personel? Hemm yw martesen fatel wrussen vy y redya, a pen vy i.20
Gorthebydh sondyans Kernewek
Kernewek a baynt aven moy serth, yn arbennik gans dyskoryon ha kowsoryon yowynka ha moy skentel gans tek. Sondyans war Discord ha Whatsapp Kernewek a drovyas bos 65% a grysis y fia SK drog (11.5%) po pur dhrog (53%) rag an yeth. Pan veu govynnys pyth a dal bos gorthyp an gemeneth orth SK, 46% a leveris y kodh y hedhi ha 27% y woheles, gans an dus moy ha 60 bloodh hepken ow tybi y kodh oberi ganso.20
31% a worthebydhyon an sondyans a leveris y hwrussa an devnydh a SK yn Kernewek aga fellhe a’n yeth, hag ynwedh 54% a leveris y fiens i pellhes yn krev ha 23% pellhes tamm a by kowethas, asnodh po dyskador pynag ow tevnydhya SK.
An gorthyp a’n re a leveris bos aga godhvos a SK po “konnyk” po “da” o dampnus yn arbennik. Pubonan y’n bagas ma a worthebis y fia SK dregynnus rag Kernewek, y hwrussa an devnydh a SK gans pennfenten aga fellhe a’n bennfenten na yn krev hag y kodh dhyn hedhi an devnydh a SK rag Kernewek.
HONANIETH, LELDER HA DIVERSETH
Nyns esa Aristotelis Ioannis Paschalidis, ow skrifa a-barth UNESCO, ow kewsel yn komparek a-dro dhe yethow lyharivhes pan wrug ev y wovyn, mes an govyn a dhassen yn kreffa ragon: “Pygemmys koll a honanieth a vynnir sakrifia rag effeythuster?”21
Honanieth yw a’n moyha bri rag Kernewegoryon. Studhyans Ute Wimmer Reversing Language Shift: the Case of Cornish a henow “gweythres [an yeth] avel arwodh a honanieth kenedhlek” avel an nessa ughella skila (66%**) yn-mysk kowsoryon ha dyskoryon, fethys gans gonisogeth Kernow (80%) hepken.22 Yth havalsa hemma bos acheson solempnyans, mes pan vo SK keworrys, y teu ha bos peryl. Vincent Koc a Hyperlink a lever y hyll SK “kevri dre wall orth an gwannheans a yeth ha honanieth wonisogethel”.23
Ev a aswon ynwedh y hallsa awtomategi dyski po dinythi yeth “lehe an rychedh ha lelder hag a dheu a gowsoryon dhenel neb a dheg istoriow gonisogethel y’ga hows”. Yn hwir, peswar studhyans gwrys gans Pennskol Kaliforni Soth re dhiskwedhas bos devnydhya PYB dhe weres gans skrifa “kelmys orth dyfygyansow nosedhek yn diverseth yethel hag y hyll mellya gans an konvedhes brysoniethel ha kowethasel yw proviys gans yeth.”24
Ha hemm yw yn Sowsnek, onan a’n yethow an ryccha ha brassa y’n bys. Dismyk an effeyth war yeth byghanna kepar ha Kernewek—gans le a dhogvennans, le a gedhlow, sel kowsoryon munys hag ogas hag arghans mann—ha war y lies orgraf hag eghen yeth. Yn arbennik yn gettesten Kernewek, seulabrys yma kowsoryon Diwedhes ow strivya dhe vos gwelys avel vas gans gwartheyvans Kres. A dybyn y hwor SK an dyffrans? Heb preder, y hwra po kemyska puptra warbarth, ow sowdheni pubonan, po devnydhya Kres dhe fetha Diwedhes.
An gwruthyl a dhalgh herdhys gans SK Dinythus, dre favera yethow savonegys, a argyl an vansyans a rannyethow ranndiryel.25
Kresen woramontyorieth Barcelona
Nyns yw eghennow hepken yn peryl; SK a wodros beudhi Kernewek yn tien. Akordys yw Perlin y hallsa an platheans yethel a hwarva dres kansbledhynnyow yn Sowsnek hwarvos dres nos yn yeth lyharivhes gans SK orth an fronnow—dell via, ow pos gallosek a bassya Kernewek denel heb assay. Ev a venek prederow yn kever PYB ow rewi yeth yn hy le ha hogen ow settya pyth yw an styr a wodhvos an yeth, yn arbennik gans niverow munys a gowsoryon deythyek.26
Treylyansow leun a atal a liesha warlinen kepar ha nowodhow fug. Kowsoryon deythyek a’n yethow ma yw passyes avel bos “re gales dhe drovya”, komparys orth fordhow awtomategys a surheans kwalita hag yw disjunys yn tien a geskomunyans y’n bys gwir. Kynth yw possybyl rag kemenethow yeth brassa ha moy gallosek synsi an bottys ma dhe akont ha’ga devnydhya yn stratejek hogen, re es yw dismygi [yeth lyhariv] ow pos reverthys.26
Ross Perlin, Endangered Language Alliance
Heb kontrol hag yn diwla an gewri deknegieth, Kernewek synthesek a wra gornivera ha gorthrabellhe Kernewek denel.
SOVRANEDH KEDHLOW HA KOLONEGIETH
Sovranedh kedhlow teythyek yw an gwir gans [kenedhel teythyek] a woverna an kuntel, perghenogeth ha gweytha a’y hedhlow hy honan.27
Native Nations Institute
Byttegyns, yma gonisogethow teythyek hag usi owth oberi war geskowethyans moy ewnhynsek gans SK. Tek heb an kowr a res asnodhow, mes y as kemenethow gwitha sovranedh kedhlow war an gerthen wonisogethel hag yw aga yeth. Te Mana Raraunga, Rosweyth Sovranedh Kedhlow Māori, re wrug rol a bennrewlys rag an gwruthyl, devnydhya ha kevrenna a gedhlow Māori, ow ragwirhe an edhom a grefhe maystri rag Māori a-lemmyn hag a dheu.
I a venek poynt posek hag a dalvia bos konsidrys gans rach gans stywards a skians yethel ha gonisogethel: “Kedhlow ahanan, a-dro dhyn ha’gan asnodhow, yw kerthennow a bris. Pan vo maystri kellys, kales yw y dhaskemeres.”28 Ny dal gul erviransow yn skav po yn uskis; y hyllyn pupprys leverel “ea” mar kwrussyn leverel “na” kyns orth us sett kedhlow, mes ny yllyn nevra leverel “na” mar kwrussyn leverel “ea” seulabrys.
An desten SK, kepar ha pub le aral, yw leun a dus hag yw settys y’ga maneryow ha gans gwel pur drevesigel yn tidowl.29
Michael Running Wolf, First Languages AI Reality
Hemm yw pur bosek y’n gettesten a’n kontrol possybyl a gedhlow Kernewek gans korforethow gallosek a-ves. Estenegieth jatelydhek re beu molleth war gowethasow y’n amal emperourethek ha nyns yw kowethas Kernewek dyffrans, wosa enebi kansvledhynnyow a’y rychys hag asnodhow naturek ow pos destryppys ha gwerthys dre vras gans budh tus yn-mes a Gernow.
An lyver henwys Indigenous Data Sovereignty and Policy a verk lemmyn y hyllir gweles perthynyansow kedhlow avel “pesyans a’n argerdhow ha systemow-krysi isworwedhek a estennans, drogusyans, kuntellyans ha diberghenogeth re beu gwrys war boblansow Teythyek dres trevesigeth istorek.”30 An konvedhes estennek ma a gedhlow yw, dell verkons, hevelebys a-der goderrys gans tyli pobel rag aga hedhlow.
Wostiwedh, res yw ma na vo agan yeth gorrys yn diwla a-ves routys gans pennrewlys perghenogel na as dhyn sovranedh lowr a onan a’gan asnodhow naturel an moyha posek: agan yeth. Res yw dhyn kavos pennrewlys kedhlow ygor, a-der plegya orth kontrol korforethel. Res yw dhyn lewya ha gidya an devnydh a’gan kedhlow, a-der y usya erbynn agan lesow ha rag pocketys tek bras.
A-der drehedhes an arwithans a davosow avel kudyn teknegiethel, my a dyb bos res dhe gemenethow teythyek bos reythhes yn politek, po der arghasans a wovernansow po dre dhifresyansow laghel dhe dhevnydhya aga yethow.31
Dr. Fintan Mallory, Pennskol Durham
Res yw dhyn ragwirhe yeth-avel-kemeneth ha hwilas devnydh ygor, ewnhynsek hag ethegel a’gan kerthennow yeth, ertach ha gonisogethel. Res yw dhyn goheles tybi a SK avel an hus mayth ambos ha kevarghewi yn hwithrans selyek, lewys gans agan kemeneth. Ny wra korforethow agan selwel ha, hogen, i a yll agan shyndya.
NYNS EUS KERNEWEK WAR BLANET MAROW
Governansow ha kevalav ollvysel […] yw omres dhe ideologieth marghas ‘rydh’ moy es dell yns omres dhe sewena kemenethow, pobel ha’n planet.32
Cymdeithas yr Iaith Maniffesto 2022
An brassa rann a vreusyansow a SK a wrussa meneges hemma seulabrys. Onan a’n argyansow brassa yw erbynn SK Dinythus, mes rag own bos ankoth dhis, ni a wra mires orth an chif boyntys.
Res yw bos evadow an dowr goyeynhe pub kresen kedhlow SK. Y kollenk an dowr ma. Pennskol Kaliforni re dherivas “y hallsa demond dowr ollvysel SK hedhes 4.2-6.6 bilvil metrow kubek erbynn 2027. Henn yw moy es 50 kansran a us dowr bledhynnyek an RU yn 2023.”33 Y kettermyn, an Desedhek Ollvysel Erbysieth Dowr a dheklaryas “barras dowr ow tardha yn uskis” ma na dal Kernewek kevri dhodho.34
Ni re dheuth ha bos yn hwir omres dhe deknegiethow privedh gwrys ha kontrolys gans dornas a gompanis diskler [hag] a hevel bos mygyl dre vras orth an sewyansow sosyel a’ga gwriansow ha kevri yn ispoyntel marnas mars yns i konstrinys gans rewlys an wovernans dhe wellhe aga imach poblek.35
Iker Erdocia, Pennskol Sita Dulyn
Yma edhom dhe SK a vynsow kowrek a galesweyth orth kost palas monyow tanow. Kales yw estenna ha purhe an re ma hag yma kostow kerghynedhel ha sosyel poos. Estennys yns i yn fenowgh a hwelyow yn powyow gans difresyansow lakka rag lavur ha’n kerghynnedh. Reset a lever “yn fenowgh y hwra kemenethow yw trigys yn ogas dhe’n hwelyow, yn fenowgh bagasow lyhariv po teythyek, enebi gwethheans an tir, defolyans an dowr hag abusyans gwiryow denel. Meur a hemma a yll bos kelmys yn tidro orth an galesweyth SK.”36 Pan yw an galesweyth kegys yn sertan hag euver, ena tewlys yw avel e-wast yn kemenethow boghosek. Res yw nyns yw an avonsyans possybyl a Gernewek orth kost agan kemenethow hwor lyhariv ha teythyek.
Ynwedh res yw myns hujes a nerth rag trenya SK, yn skon martesen an keth myns ha pow byghan37 hag yma ol troos karbon kowrek.38 Kler yw—der usadow dowr, diwysyans estennek, konsumyans nerth hag ol troos karbon—bos SK yeyn nowodhow rag kerghynnedh ow strivya a’n planet mayth on ni trigys warnodho ha nyns eus Kernewek war blanet marow.
GUL DHE SK BOS EKS-PAPYNJAY
A-der gul dhe yethow lyhariv bos moy hedhadow, lemmyn yma SK ow kwruthyl tardhek pupprys owth omlesa rag studhyoryon ha kowsoryon a’n yethow ma dhe wolya.39
mit technology review
Ni re glewas a’n anwirhevelepter efan a wul dhe SK gallos mimya Kernewek yn golow an kostys yn kedhlow, ober, termyn ha teknegieth. Ni re gonsidras lycklod an dewisynter dispresyans yeyn po askorras-aspia ha’n posekter a sovranedh kedhlow. Ni re redyas a-dro dhe’n effeythyow war vewnansow Kernewegoryon, keffrys ha’n kostys katastrofek rag an kerghynnedh ha poblow teythyek.
Ni re dhyskas y hwra platheans yethel gans SK boghosekhe y destennow ha fatel yll SK martesen ervira a’gan parth fatel godh dh’agan yeth oberi. Ni re welas an anwoheladewder a yeth avel denel ha’n peryllyow a wul ‘dyskoryon’ na yll dyski ha ‘kowsoryon’ na yll kewsel. Ni re welas an peryllyow orth bri ha fydhyans rag kowethasow a wrussa palas an pyth hag yw gwelys avel ‘skomblans’.
Ni re glewas prag y fia omblegya orth an jagganat a SK error rag Kernewek ha dell na vynn agan kemeneth skoodhya gorra an skoos a-dhyworthyn. Yn y le, res yw dhyn batalyas. Res yw dhyn gul dhe Gernewek bos spas mar rydh a skomblans dell yll bos, res yw adhyski orth botlapyoryon yn dyski ha devnydh yeth yn ethegel hag yn effeythus, res yw goheles tybi wortaswerth.
Res yw dhyn gul dh’agan yeth bos parth heb SK, rosweyth a dus fydhyadow ha’ga gwriansow denel, drehevys war lelder, kemeneth, assay ha trest: Kernewek hag yw a-barth an bobel, a’n bobel ha gans an bobel.
Niwlen Ster
Notennow
* A prime example is the laughably-unaffordable restaurant RenMor, which The Headland Hotel thinks is a version of “Re’n Mor”, which they believe means “by the sea” as in “next to the sea” but actually means “by the sea!” like saying “by Zeus!”. This is both hilarious and enraging.
** A figure perhaps lower than it should be if you consider that many of the “emotional motives” which were not counted in this category, such as “I’m Cornish, what better reason do you need?”, do also refer to identity.
FENTENNOW
1. Judah, J. (2025) How AI and Wikipedia have sent vulnerable languages into a doom spiral, MIT Technology Review.
2. Ackermann, A. (2023) When AI doesn’t speak your language, Coda.
3. Crichton, D. (2024) AI and the Death of Human Languages, Lux.
4. Lamb, W. (2024). Could Artificial Intelligence save Scottish Gaelic?, The University of Edinburgh.
5. Dencik, L. (/2025) AI Inequalities: Minority Languages, TUC Cymru.
6. Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Microsoft Research, India. (2020). The State and Fate of Linguistic Diversity and Inclusion in the NLP World. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
7. Ackermann, A. (op cit)
8. McLoughlin, I. (2018) How to teach AI to speak Welsh (and other minority languages), The Conversation.
9. Mallory, F. (2025) RISE UP Panel Discussion & Q&A: What AI Can and Cannot Do for Minoritised Languages, YouTube.
10. Perlin, R. (2024) AI Won’t Protect Endangered Languages, The Dial.
11. RISE UP (2025) #4 RISE UP Event Summary: What AI Can and Cannot Do For Minoritised Languages, RISE UP.
12. Mallory, F. (2024) European Day of Languages: Will lesser spoken languages soon only be kept alive by AI technology? Durham University.
13. Bender, E., Gebru, T., McMillan-Major, A., & Mitchell, M. (2021) On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
14. Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025) The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers. Microsoft.
15. Perlin, R. (op cit)
16. Judah, J. (op cit)
17. Abbruzzese, J., & Wile, R. (2025) Is an AI backlash brewing? What ‘clanker’ says about growing frustrations with emerging tech, NBC News.
18. Webster, K. (2025) Why Using ChatGPT at Work Could Hurt Your Reputation, Inc. Magazine.
19. Herrman, J. (2024) Is That AI? Or Does It Just Suck?, Intelligencer.
20. Wilson, L. (2025) Skians Kreftus ha Kernewek/Artificial Intelligence and Cornish
21. Paschalidis, A. I. (2025) AI and the great linguistic flattening, UNESCO.
22. Wimmer, U. (2010). Reversing Language Shift: the Case of Cornish. Cornish Language Board, p. 113
23. Koc, V. (2025) Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges, ResearchGate.
24. Sourati, Z., Karimi-Malekabadi, F., & Ozcan, M. (2025) The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Models, ResearchGate.
25. Melero, M. (2024) The Future of Language (and Cultural) Diversity in the Age of AI, CLARIN.
26. Perlin, R. (op cit)
27. Russo Carroll, S., Rodriguez Lonebear, D., & Martinez, A. (2017). Data Governance for Native Nation Rebuilding, Native Nations Institute.
28. Te Mana Raraunga. (2018). Frequently Asked Questions, Te Mana Raraunga.
29. Ackermann, A. (op cit)
30. Walter, M., Kukutai, T., Carroll, S. R., & Rodriguez-Lonebear, D. (Eds.). (2020). Indigenous Data Sovereignty and Policy. Taylor & Francis, p. 24
31. Mallory, F. (op cit)
32. Cymdeithas yr Iaith (2022) Cymru Rydd, Cymru Werdd, Cymru Gymraeg., p. 27
33. O’Sullivan, L. (2025). How AI’s Failure on Linguistic Diversity is Deepening Global Inequality, RESET – Digital for Good.
34. Harvey, F. (2024). Global water crisis leaves half of world food production at risk in next 25 years, The Guardian.
35. Erdocia, I., Migge, B., & Schneider, B. (2024). Language is not a data set—Why overcoming ideologies of dataism is more important than ever in the age of AI. Journal of Sociolinguistics, 28(5), p. 23
36. O’Sullivan, L. (op cit)
37. Erdenesanaa, D. (2023) A.I. Could Soon Need as Much Electricity as an Entire Country, The New York Times
38. Heikkilä, M. (2022) We’re getting a better idea of AI’s true carbon footprint, MIT Technology Review.
39. Judah, J. (op cit)#4 #AI #ArtificialIntelligence #Breus #Cornish #Cornwall #data #generativeAI #history #jynn #kedhlow #Kernewek #Kernow #Kernowek #LLM #machine #PYB #SK #SKDinythus #SkiansKreftus #Sordya
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Seattle is the first test city for a new bike lane barrier made of recycled tires
The pitch is great: Let’s take a car culture waste product that would otherwise be burned and instead turn it into a barrier to protect the lives of people biking. That’s the concept behind Pretred’s new Paceline barriers, which were designed with bike lanes in mind initially in response to Seattle’s trouble acquiring enough pre-cast concrete barriers for SDOT’s ongoing “even better bike lanes” project. The company used the SDOT order as the impetus to invest in the design and tooling to create these Paceline barriers, which are now for sale to any place that wants them.
Pretred Sales Manager Matt Dunn told Seattle Bike Blog that the Paceline barriers are now “the only U.S.-made bike lane barrier that is more significant than a curb and less significant than a full wall.” The project was personal for Dunn, who was hit by a car while riding his bike. “I wish these barriers would have been there when that happened,” he said, noting, “We’re all cyclists in this office.”
Dunn credited Cascade Bicycle Club Executive Director Lee Lambert with connecting SDOT and Pretred. The department had purchased as many of the precast concrete barriers as were available, but it still wasn’t enough. If Pretred can produce a barrier that is competitive with concrete, that would be a win for all North American cities because it would mean more supply and more competition in the market. Concrete creation also requires a lot of energy and is a major source of greenhouse gas emissions. Burning tires also releases a lot of greenhouse gasses. Pretred sells itself as a more environmentally-friendly option both for creating barriers and for recycling tires. The company started in 2020 selling what they call Colorado barriers, which can be used either in place of a Jersey barrier or as a base to support weight.
When fully rebuilding a road engineers can include curbs and barriers from the start, such as the new bike lanes along the waterfront. We cannot wait for full roadway rebuild projects to build out our city’s bike network, so we need tools for medium-term bike lane installs for the time between now and the street’s next major repaving project. Sometimes referred to as “Toronto barriers” for some reason, pre-cast concrete barriers are an excellent option for creating a significant barrier on an existing road surface. The Toronto-style barriers are shorter and skinnier than a highway-style Jersey barrier but provide significantly more deterrence than plastic reflective posts. Cities like Seattle need a barrier that protects bike lanes from motor vehicles without making streets look and feel like highways, and this is a tricky balance. DOTs would also like to avoid the need for constant maintenance.
The new tire-based barriers are a different take on the concept. The come in segments two feet long that link together. The 80-pound segments are lighter than concrete, making them easier to install and to move by hand if necessary, but this also means they are easier for motor vehicles to displace. They lie somewhere between a parking stop and a Toronto barrier, which could be the sweet spot cities are looking for if they can prove durable and effective under the strains of city streets. The material cost is about $24 per foot plus additional costs for the end treatments of each connected segment, Dunn said. Agencies can install posts on the blocks for either signage or additional reflectors, though SDOT did not do so as part of this project. Some reflective plastic posts might not be a bad idea, especially on curves and end points where strikes are more likely, though each block does have front and rear reflectors.
When struck, the tire barrier segments may get gouged but hopefully will be less likely to fully crack and fail. If they do fail, crews should be able to use regular work vehicles and tools to replace the damaged segments more quickly and easily. Concrete barriers are so heavy that they require a forklift or similar piece of machinery to move and install, which could lead to longer waits for repairs as we saw with the bike lane on the Airport Way bridge near Georgetown recently. The barrier was struck (and did its job!), but a section was left sticking into the bike lane for a while before crews could repair it.
The tire-based barriers may not leave as much damage on any vehicles that strike it, but they also should not be as difficult to repair. We don’t need to imagine what this would look like because the test segment has already experienced its first major strike. I went down to Campus Parkway to check it out and found a section under the bridge that clearly got hit by something significant. Not sure if it was a car, truck or bus, though the level of damage makes me think it could have been something more on the bigger side. Bolts were bent and multiple barriers seemed to split at the bolt-mounting point. One barrier section was totally destroyed and was sitting on the roadside. In all, five or six of the segments were damaged. But because of their size and weight, they were not left blocking the bike lane in the meantime, which is nice.
Environmental benefits and concerns
The U.S. wears out a hell of a lot of tires, which are notoriously difficult to dispose of. When burned, they produce a relatively low amount of heat for a long time. That’s why tire fires can last so long. They also release a lot of nasty stuff into the air.
There have been many attempts to find other creative and profitable uses for tire waste, including using tire crumbs as part of an artificial athletic or playground surface. The EPA, CDC and CPSC have been studying the possible health impacts of these surfaces, though there don’t seem to be any clear conclusions yet (though we know it’s bad for kids to eat them). Tires contain a lot of harmful chemicals, researchers just don’t know the extent that using tires in play surfaces might lead to harmful exposure. Meanwhile, researchers at UW have identified a tire chemical — 6PPD-quinone — that is likely a major cause coho salmon population decline. The chemical gets into waterways through wear and tear from cars and trucks driving on roadways.
I asked Dunn if these tire-based barriers might contribute to the problem of tire chemicals in waterways, and he said the blocks are designed to keep tire chemicals contained within them. However, as with any tire those elements could be released if they are broken or crushed. The blocks are made of about 90% tire “crumb,” then Pretred uses polyurethane to encapsulate it and hold it together. When they are just sitting there getting rained on, they are designed not to release tire chemicals into the runoff, he said.
#SEAbikes #Seattle
-
Seattle is the first test city for a new bike lane barrier made of recycled tires
The pitch is great: Let’s take a car culture waste product that would otherwise be burned and instead turn it into a barrier to protect the lives of people biking. That’s the concept behind Pretred’s new Paceline barriers, which were designed with bike lanes in mind initially in response to Seattle’s trouble acquiring enough pre-cast concrete barriers for SDOT’s ongoing “even better bike lanes” project. The company used the SDOT order as the impetus to invest in the design and tooling to create these Paceline barriers, which are now for sale to any place that wants them.
Pretred Sales Manager Matt Dunn told Seattle Bike Blog that the Paceline barriers are now “the only U.S.-made bike lane barrier that is more significant than a curb and less significant than a full wall.” The project was personal for Dunn, who was hit by a car while riding his bike. “I wish these barriers would have been there when that happened,” he said, noting, “We’re all cyclists in this office.”
Dunn credited Cascade Bicycle Club Executive Director Lee Lambert with connecting SDOT and Pretred. The department had purchased as many of the precast concrete barriers as were available, but it still wasn’t enough. If Pretred can produce a barrier that is competitive with concrete, that would be a win for all North American cities because it would mean more supply and more competition in the market. Concrete creation also requires a lot of energy and is a major source of greenhouse gas emissions. Burning tires also releases a lot of greenhouse gasses. Pretred sells itself as a more environmentally-friendly option both for creating barriers and for recycling tires. The company started in 2020 selling what they call Colorado barriers, which can be used either in place of a Jersey barrier or as a base to support weight.
When fully rebuilding a road engineers can include curbs and barriers from the start, such as the new bike lanes along the waterfront. We cannot wait for full roadway rebuild projects to build out our city’s bike network, so we need tools for medium-term bike lane installs for the time between now and the street’s next major repaving project. Sometimes referred to as “Toronto barriers” for some reason, pre-cast concrete barriers are an excellent option for creating a significant barrier on an existing road surface. The Toronto-style barriers are shorter and skinnier than a highway-style Jersey barrier but provide significantly more deterrence than plastic reflective posts. Cities like Seattle need a barrier that protects bike lanes from motor vehicles without making streets look and feel like highways, and this is a tricky balance. DOTs would also like to avoid the need for constant maintenance.
The new tire-based barriers are a different take on the concept. The come in segments two feet long that link together. The 80-pound segments are lighter than concrete, making them easier to install and to move by hand if necessary, but this also means they are easier for motor vehicles to displace. They lie somewhere between a parking stop and a Toronto barrier, which could be the sweet spot cities are looking for if they can prove durable and effective under the strains of city streets. The material cost is about $24 per foot plus additional costs for the end treatments of each connected segment, Dunn said. Agencies can install posts on the blocks for either signage or additional reflectors, though SDOT did not do so as part of this project. Some reflective plastic posts might not be a bad idea, especially on curves and end points where strikes are more likely, though each block does have front and rear reflectors.
When struck, the tire barrier segments may get gouged but hopefully will be less likely to fully crack and fail. If they do fail, crews should be able to use regular work vehicles and tools to replace the damaged segments more quickly and easily. Concrete barriers are so heavy that they require a forklift or similar piece of machinery to move and install, which could lead to longer waits for repairs as we saw with the bike lane on the Airport Way bridge near Georgetown recently. The barrier was struck (and did its job!), but a section was left sticking into the bike lane for a while before crews could repair it.
The tire-based barriers may not leave as much damage on any vehicles that strike it, but they also should not be as difficult to repair. We don’t need to imagine what this would look like because the test segment has already experienced its first major strike. I went down to Campus Parkway to check it out and found a section under the bridge that clearly got hit by something significant. Not sure if it was a car, truck or bus, though the level of damage makes me think it could have been something more on the bigger side. Bolts were bent and multiple barriers seemed to split at the bolt-mounting point. One barrier section was totally destroyed and was sitting on the roadside. In all, five or six of the segments were damaged. But because of their size and weight, they were not left blocking the bike lane in the meantime, which is nice.
Environmental benefits and concerns
The U.S. wears out a hell of a lot of tires, which are notoriously difficult to dispose of. When burned, they produce a relatively low amount of heat for a long time. That’s why tire fires can last so long. They also release a lot of nasty stuff into the air.
There have been many attempts to find other creative and profitable uses for tire waste, including using tire crumbs as part of an artificial athletic or playground surface. The EPA, CDC and CPSC have been studying the possible health impacts of these surfaces, though there don’t seem to be any clear conclusions yet (though we know it’s bad for kids to eat them). Tires contain a lot of harmful chemicals, researchers just don’t know the extent that using tires in play surfaces might lead to harmful exposure. Meanwhile, researchers at UW have identified a tire chemical — 6PPD-quinone — that is likely a major cause coho salmon population decline. The chemical gets into waterways through wear and tear from cars and trucks driving on roadways.
I asked Dunn if these tire-based barriers might contribute to the problem of tire chemicals in waterways, and he said the blocks are designed to keep tire chemicals contained within them. However, as with any tire those elements could be released if they are broken or crushed. The blocks are made of about 90% tire “crumb,” then Pretred uses polyurethane to encapsulate it and hold it together. When they are just sitting there getting rained on, they are designed not to release tire chemicals into the runoff, he said.
#SEAbikes #Seattle
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The Cooperator’s Dilemma: How Martin Nowak’s Mathematics of Kindness Became a Blueprint for Control
Martin Nowak wanted to prove that cooperation is the animating force of evolution. He succeeded. His mathematical models, published across decades of work at Oxford, Princeton, and Harvard, demonstrate with formal rigor that cooperation is not an anomaly in a competitive world but a fundamental mechanism by which biological complexity arises. Genomes cooperate. Cells cooperate. Organisms cooperate. Societies cooperate. Without cooperation, there are no multicellular bodies, no ant colonies, no languages, no civilizations. This is not sentiment. It is mathematics. And it is precisely because the mathematics are correct that they are dangerous.
Nowak is Professor of Mathematics and Biology at Harvard University, an Austrian-born scientist trained in biochemistry and mathematics at the University of Vienna, where he worked under Peter Schuster on quasispecies theory and with Karl Sigmund on evolutionary game theory. He earned his doctorate sub auspiciis praesidentis, the highest academic honor Austria can bestow on a graduating student. He moved to Oxford, where he collaborated with Robert May (later Lord May of Oxford) on spatial evolutionary dynamics and virus population models. He established the first center for theoretical biology at the Institute for Advanced Study in Princeton in 1998. In 2003, he came to Harvard to found the Program for Evolutionary Dynamics (PED), where he would spend two decades formalizing the mathematics of cooperation, cancer evolution, language emergence, and infection dynamics.
His landmark 2006 paper in Science, “Five Rules for the Evolution of Cooperation,” laid out the theoretical architecture that his 2011 book SuperCooperators: Why We Need Each Other to Succeed (co-written with science journalist Roger Highfield) would translate for a general audience. The core argument is elegant and, on its face, optimistic: natural selection, left alone, favors defectors over cooperators, but five distinct mechanisms can reverse this tendency and allow cooperation to evolve. Those mechanisms are kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. Each mechanism can be reduced to a simple mathematical rule specifying the conditions under which cooperation becomes the favored strategy. Each rule expresses a threshold: when the benefit-to-cost ratio of a cooperative act exceeds a critical value determined by the mechanism’s structure, cooperation wins.
The book is earnest. It is hopeful. It tells a story about vampire bats sharing blood meals, about cancer as a failure of cellular cooperation, about human language as the greatest cooperative innovation since the gene. Nowak calls humans “supercooperators” because we are the only species that deploys all five mechanisms simultaneously. The implication is that our capacity for cooperation is not just biologically real but biologically supreme. We are, in his framework, evolution’s greatest collaborative achievement.
This is all true. And none of it prevents the mathematics from being turned inside out.
The Five Mechanisms as Five Exploits
What Nowak mapped are not merely descriptions of how cooperation arises. They are, read from the other direction, specifications for how cooperation can be manufactured, directed, and harvested by any actor with sufficient control over the relevant variables. Each mechanism contains its own vulnerability. Each rule that tells you how to promote cooperation also tells you how to engineer compliance that feels like cooperation to the people inside the system.
Direct Reciprocity: The Obligation Engine
Direct reciprocity is the simplest mechanism: I help you now, you help me later, and we both benefit as long as we expect to interact again. Nowak’s mathematical condition is precise. Cooperation through direct reciprocity succeeds only when the probability of future interaction between the same two individuals exceeds the cost-to-benefit ratio of the cooperative act. If you and I will meet again many times, the cost of helping you today is offset by the expected return from your future help. The strategy that dominates in this environment is not pure tit-for-tat (which is too brittle, collapsing into mutual defection after a single error) but “win-stay, lose-shift,” a more forgiving strategy that sustains cooperation through noise.
The exploit is in the precondition. If you can engineer a situation where people believe they will interact with you repeatedly and indefinitely, you can extract cooperation from them even when the exchange is not mutual. Subscription services, employer-employee relationships with annual review cycles, government benefit programs tied to ongoing compliance, social media platforms that reward daily engagement: all of these create artificial conditions of repeated interaction. The person inside the system cooperates because their evolved psychology recognizes the pattern. They feel the pull of reciprocity. They return to the platform, they renew the subscription, they comply with the bureaucratic requirement, because the structure tells them the relationship will continue and defection carries a cost.
But the entity on the other side of the interaction is not bound by the same psychology. A corporation does not feel the tug of reciprocal obligation. A government agency does not experience guilt for failing to return a favor. The asymmetry is structural: the human cooperates because direct reciprocity is wired into primate social cognition; the institution extracts because it designed the interaction pattern to trigger exactly that response. The “repeated game” is real for the person and fictional for the institution, which can end the relationship, change the terms, or alter the benefit-to-cost ratio at any time without experiencing the psychological cost of defection.
Consider the modern employment relationship. An employee cooperates (works hard, stays late, defers complaints) because the structure of employment creates an expectation of continued interaction: there will be another paycheck, another review, another year. The employer benefits from this cooperation while retaining the unilateral power to terminate the relationship. The employee’s cooperation is genuine. The employer’s reciprocity is contingent. Nowak’s mathematics describe the employee’s behavior perfectly. They do not describe the employer’s, because the employer is not playing a repeated game. The employer is playing a series of one-shot games while the employee believes both parties are in a repeated game. This mismatch is not a bug in the model. It is the exploit.
Indirect Reciprocity: The Reputation Weapon
Nowak considers indirect reciprocity the most important mechanism for human cooperation, and he is probably right. Indirect reciprocity works through reputation: I help you not because I expect you to help me, but because others are watching, and my willingness to help builds a reputation that will cause others to help me in the future. The mathematical condition is that the probability of knowing someone’s reputation must exceed the cost-to-benefit ratio of cooperation. Language, Nowak argues, evolved in part to serve this mechanism. We gossip. We evaluate. We track who is trustworthy and who is not. This reputational calculus is what allows cooperation to scale beyond pairs of individuals who interact repeatedly.
The danger is obvious and immense. Whoever controls the reputation infrastructure controls the conditions for cooperation. And in the modern world, reputation infrastructure is not distributed among gossiping primates. It is centralized in databases.
Credit scoring systems (FICO in the United States, similar systems globally) are indirect reciprocity engines. They assign each person a reputation score based on their history of “cooperation” with financial institutions. A high score means you have reliably cooperated (paid debts, maintained accounts, avoided default). The score then determines whether others will cooperate with you (extend credit, offer favorable terms, rent you an apartment). The mathematics are identical to Nowak’s model. The probability of knowing your reputation is essentially 1.0 in a world of universal credit reporting. Therefore, the threshold for cooperation is easily met, and people cooperate.
But cooperate with what? With whom? The content of “cooperation” in a credit scoring system is defined by the institutions that build and maintain the scoring model. Cooperation means paying your bills. It means maintaining debt. It means participating in a financial system on its terms. The reputation system does not reward you for helping your neighbor move furniture or lending your car to a friend in need. It rewards you for being a reliable revenue source for financial institutions. The indirect reciprocity mechanism is operating exactly as Nowak describes. The mathematics are satisfied. But the cooperation is directed, not organic. It serves the architects of the reputation system, not the cooperators within it.
China’s social credit experiments take this further, attaching reputational scores to civic behavior, political speech, social associations, and consumption patterns. The mathematics are the same. The mechanism is the same. The outcome is that “cooperation” becomes indistinguishable from “compliance,” and the person inside the system cannot easily tell the difference, because the psychological experience of cooperating to maintain one’s reputation feels the same whether the reputation system is tracking genuine prosocial behavior or political obedience.
Social media platforms represent a third variant. Platforms like Instagram, TikTok, and formerly Twitter construct reputation systems (follower counts, likes, shares, verification badges) that trigger indirect reciprocity behavior. Users cooperate with the platform (producing content, engaging with others’ content, spending time on the platform) because the reputation system rewards them for doing so. The platform harvests this cooperation as engagement metrics, advertising revenue, and behavioral data. The user experiences the warm glow of reputational validation. The platform experiences profit. The mathematics of indirect reciprocity are perfectly satisfied in both directions. The exploitation is invisible precisely because it operates through a mechanism that evolution shaped to feel good.
Network Reciprocity: Whoever Designs the Graph Wins
Nowak’s third mechanism, developed in his landmark 1992 Nature paper with Robert May, showed that the spatial structure of interactions matters enormously. In a well-mixed population (where everyone interacts with everyone equally), defectors always win. But when interactions are local, restricted to neighbors on a network, cooperators can form clusters that protect themselves from exploitation. Cooperators surrounded by other cooperators thrive; defectors on the edge of cooperative clusters can invade, but the cluster structure slows the invasion and allows cooperation to persist.
The strategic implication is that whoever controls network topology controls the conditions for cooperation. This is not a metaphor. It is a direct application of the mathematics.
Social media algorithms determine who sees whose content, who appears in whose feed, who gets recommended as a connection. These algorithms are network reciprocity engines. They construct the “spatial structure” of online social interaction. A platform that clusters users into engagement-optimized groups is, in Nowak’s terms, constructing a network topology. If the topology is designed to maximize engagement (which is to say, to maximize the platform’s extraction of attention), then the cooperative clusters that form will be optimized for engagement, not for the welfare of the cooperators.
Corporate organizational design is another application. Who reports to whom, who collaborates with whom, who has access to information and who does not: these are network topology decisions. A company that understands network reciprocity can design org charts that promote exactly the cooperative behaviors it wants (cross-functional collaboration, knowledge sharing, collective problem-solving) while preventing the formation of cooperative clusters that might oppose management (unions, whistleblower networks, collective bargaining groups). The mathematics tell you which structures promote cooperation and which fragment it. The application is straightforward.
Gerrymandering is network reciprocity applied to democratic geography. By controlling which voters are grouped into which districts, political actors control the spatial structure of electoral cooperation. Voters who might form cooperative clusters around shared interests are separated. Voters whose “cooperation” (voting behavior) serves the redistricting party are grouped together. The mathematics of spatial evolutionary dynamics describe exactly why this works and how to optimize it.
Group Selection: The Factory of Tribes
Nowak’s treatment of group selection (which he and others now call multilevel selection) demonstrates that groups of cooperators outcompete groups of defectors, even when defectors dominate within groups. The mechanism requires that groups compete, that there is variation in the level of cooperation between groups, and that groups with more cooperators produce more offspring groups. Under these conditions, cooperation at the group level is favored even though individual defectors within groups do better than individual cooperators.
The exploit is the deliberate manufacture of group identity and intergroup competition. Nowak’s own reviewers noted the problem clearly: group selection favors within-group niceness and between-group nastiness. This is the mathematical basis of tribalism. It is also, historically, the most reliable mechanism by which authoritarian movements generate internal cohesion.
If you want a population to cooperate internally (pay taxes, report dissent, sacrifice personal interests for collective goals), you manufacture an external threat. The perceived competition between groups raises the benefit-to-cost ratio of within-group cooperation. Nationalists understand this intuitively. So do corporate culture architects who position their company against competitors while demanding employee loyalty. So do political parties that define themselves primarily through opposition. The mathematics of multilevel selection explain why “rally around the flag” effects work, why wartime economies produce extraordinary domestic cooperation, and why authoritarian regimes invest so heavily in identifying and publicizing external enemies.
The earnestness of Nowak’s presentation (he sees group selection as enabling the great cooperative achievements of human civilization, from agriculture to the United Nations) obscures how perfectly the same mathematics describe the cooperative achievements of fascism. The cooperative group that builds a hospital and the cooperative group that builds an internment camp are both satisfying the mathematical conditions for multilevel selection. The model does not distinguish between them. It cannot. The variables are the same.
Kin Selection: Manufacturing Family Where None Exists
Kin selection, formalized by W.D. Hamilton in 1964, is the oldest and most biologically grounded of the five mechanisms. Organisms cooperate with genetic relatives in proportion to their degree of relatedness, because helping a relative who shares your genes indirectly promotes the survival of those shared genes. Hamilton’s rule states that altruism is favored when the coefficient of relatedness between donor and recipient exceeds the cost-to-benefit ratio of the altruistic act. Nowak has a complicated relationship with Hamilton’s rule (his 2010 Nature paper with E.O. Wilson and Corina Tarnita argued that kin selection is less explanatory than previously thought, provoking a famous counterresponse signed by over 130 biologists), but the mechanism remains one of his five pillars.
The exploit is the simulation of kinship where none exists. “We are family.” “Band of brothers.” “Our company family.” “Fellow citizens.” “Children of God.” These are not merely sentimental phrases. They are invocations of kin selection psychology, designed to lower the threshold at which people will sacrifice personal interest for the group. When a military unit trains together, eats together, sleeps together, suffers together, and adopts shared rituals, symbols, and origin stories, it is manufacturing fictive kinship. The result is that soldiers will take risks for their unit-mates that they would not take for strangers, because their psychology has been calibrated to treat those unit-mates as kin.
Religious organizations, fraternities, political movements, cults, and nationalist ideologies all exploit this mechanism. The more completely an institution can simulate the markers of genetic relatedness (shared appearance through uniforms, shared language through jargon, shared history through founding myths, shared suffering through initiation rites), the more effectively it triggers kin selection psychology, and the more cooperation it can extract from its members. The cost of this cooperation is borne by the members. The benefit accrues to whoever designed the kinship simulation.
The Epstein Entanglement: A Case Study in the Exploitation of Cooperation Science
Any serious discussion of Martin Nowak’s work must confront the fact that the Program for Evolutionary Dynamics, the institutional home of his cooperation research, was founded with $6.5 million from Jeffrey Epstein. This was the largest single gift Epstein made to Harvard, part of a total of more than $9 million in donations to the university between 1998 and 2007. Epstein, a convicted sex offender who would later be charged with sex trafficking before his death in federal custody in 2019, did not merely donate money and walk away. He embedded himself in the program.
Harvard’s own 2020 review found that after Epstein’s 2008 conviction and release from prison, he continued to visit the PED offices more than 40 times between 2010 and 2018. He had a personal office in Nowak’s lab. He had a key card. He was typically accompanied by young women described as his assistants. His publicist requested that PED post information about Epstein on the harvard.edu domain because, as the publicist wrote, it would be helpful for Google search results. PED complied. Epstein’s foundation page was linked from the PED website under a tab labeled “Friends.” Epstein was the only “Friend” listed.
More recently, documents released by the U.S. Department of Justice in 2025 revealed that Epstein’s involvement went beyond access and reputation-laundering. He discussed research topics with Nowak and his graduate students. He suggested lines of inquiry, including “commercial evolution” and “prelife.” He facilitated visa arrangements for at least one graduate student. He funneled scholarship money through a Ph.D. student to young female mathematicians in Romania. He reviewed page proofs of a Nature paper before publication and offered advice on handling criticism. In 2025, Nowak was placed on administrative leave a second time after his name appeared more than 8,000 times in the newly released DOJ Epstein files.
The irony is lacerating. Epstein was a man who built his entire social and financial empire on the exploitation of cooperation mechanisms. His method was indirect reciprocity: he cultivated relationships with scientists, politicians, and financiers by offering gifts, access, and introductions, building a reputation as a brilliant and generous patron of science. He used network reciprocity: he positioned himself as a hub connecting elite nodes (Harvard professors, tech billionaires, heads of state), making himself indispensable as a broker of social capital. He manufactured fictive kinship: his dinners, his island retreats, his intellectual salons created a sense of belonging and shared identity among participants. He exploited direct reciprocity: every gift came with an implicit expectation of return, whether it was a letter of reference, a favorable public statement, or simply continued access and association.
And he funded, specifically and deliberately, the research program that mathematically formalized every one of these strategies. He did not fund a chemistry lab or an engineering department. He funded the mathematics of cooperation. He then used the institutional affiliation (Harvard, the Program for Evolutionary Dynamics) as a reputational asset, laundering his public image through association with the most prestigious cooperative institution in American academia.
Nowak has not been charged with any crime related to Epstein’s offenses. The Harvard review found policy violations, not criminal conduct. But the structural relationship between Epstein and PED is itself a perfect illustration of the very dynamics Nowak’s research describes. Epstein was a defector masquerading as a cooperator, using the mechanisms of cooperation (reputation, network position, reciprocal obligation, fictive kinship) to extract value from a system whose participants genuinely believed they were cooperating for the advancement of knowledge. The mathematics predicted this possibility. The researchers did not see it, or chose not to.
The Cyclical Trap
The deepest and most troubling insight in Nowak’s work is the finding that cooperation is inherently cyclical. Cooperators increase in number and trust, building successful clusters and institutions. Then a minority of defectors, positioned to exploit the high-trust environment, invade. Cooperation collapses. Eventually, cooperators rebuild. The cycle repeats. Nowak frames this as a feature of evolutionary dynamics, a permanent oscillation that can be modulated but never eliminated.
For a government or corporation seeking to exploit cooperation, this cyclical pattern is not a problem. It is the business model. The cycle describes exactly what extraction looks like over time. During the cooperative phase, the institution harvests trust, labor, engagement, compliance, and revenue. During the collapse phase, the institution restructures, rebrands, and resets the conditions for a new cooperative phase. The people inside the system experience the collapse as a betrayal. The institution experiences it as a cost of doing business.
Platform companies cycle through this pattern visibly. A new platform launches, cultivates a cooperative community of early adopters, builds network effects, then monetizes by degrading the experience for users while extracting more value from advertisers. Users eventually defect (leave the platform), but by then the platform has captured enough network position to survive, or a new platform launches and the cycle restarts. This is Nowak’s evolutionary dynamic playing out in real time, at internet speed.
Political cycles follow the same pattern. A new administration or movement builds cooperative coalitions around shared goals. Trust increases. Policy achievements accumulate. Then insiders begin to extract (corruption, patronage, self-dealing), trust erodes, the coalition fragments, and a new movement arises to rebuild cooperation on different terms. The cycle is so regular that political scientists have formalized it independently of evolutionary biology, but Nowak’s mathematics show that it is not unique to politics. It is a property of any system in which cooperation and defection coexist.
What Nowak Missed, or Chose Not to Say
SuperCooperators is a book about the conditions that produce cooperation. It is not a book about the conditions that produce just cooperation. This is not a minor omission. It is the central weakness of the work.
Nowak’s five mechanisms are content-neutral. They describe the structural conditions under which organisms will choose to cooperate, but they are silent on what the cooperation is for. Cooperation to build a hospital and cooperation to build a surveillance state satisfy the same mathematical conditions. Within-group cooperation that produces a democratic parliament and within-group cooperation that produces a paramilitary organization both emerge from the same multilevel selection dynamics. A reputation system that tracks genuine generosity and a reputation system that tracks political loyalty both promote cooperation through indirect reciprocity.
The book occasionally gestures toward this problem. Nowak acknowledges that defectors can invade cooperative groups, that cooperation cycles, that punishment mechanisms can themselves become exploitative. But these acknowledgments are treated as complications within a fundamentally optimistic narrative, not as structural features of the mathematics that demand equal weight. The title is SuperCooperators, not SuperExploiters. The framing celebrates cooperation’s triumphs without adequately confronting the fact that the same mathematics, applied with different intent, describe cooperation’s capture.
This omission is not unique to Nowak. It is endemic to a certain strain of evolutionary optimism that mistakes the existence of cooperation for its benevolence. Cooperation is not inherently good. It is a strategy. It can be deployed in service of any goal. The mathematics do not care. A reader who absorbs Nowak’s five rules as a celebration of human goodness will be poorly prepared to recognize those same rules operating as mechanisms of control in their workplace, their government, their social media feed, and their financial system.
The Responsibility of the Mapmaker
Nowak drew a map. The map is accurate. The territory it describes is real. But a map can be read by anyone, and the same map that helps a traveler find water helps an army find the traveler. The five rules for the evolution of cooperation are, simultaneously, five rules for the engineering of compliance. The mathematics are identical. Only the intent differs.
The question is not whether Nowak should have refrained from publishing his research. Suppressing accurate mathematics is never the answer. The question is whether the scientific community and the reading public have a responsibility to read the map with both eyes open: to see not only the beautiful cooperative structures it reveals but also the exploitative architectures it enables. The answer, given what we now know about who funded the map’s creation and what they used its institutional credibility to accomplish, should be self-evident.
Cooperation is real. It is mathematically demonstrable. It is essential to every level of biological and social organization. It is also the single most exploitable feature of human psychology, and anyone who tells you otherwise is either not paying attention or is the one doing the exploiting.
#consumerValue #cooperation #engineering #epsteinFiles #fiveMechanisms #harvard #martinNowak #needingEachOther #oxford #politics #princeton #research #rogerHighfield -
The Cooperator’s Dilemma: How Martin Nowak’s Mathematics of Kindness Became a Blueprint for Control
Martin Nowak wanted to prove that cooperation is the animating force of evolution. He succeeded. His mathematical models, published across decades of work at Oxford, Princeton, and Harvard, demonstrate with formal rigor that cooperation is not an anomaly in a competitive world but a fundamental mechanism by which biological complexity arises. Genomes cooperate. Cells cooperate. Organisms cooperate. Societies cooperate. Without cooperation, there are no multicellular bodies, no ant colonies, no languages, no civilizations. This is not sentiment. It is mathematics. And it is precisely because the mathematics are correct that they are dangerous.
Nowak is Professor of Mathematics and Biology at Harvard University, an Austrian-born scientist trained in biochemistry and mathematics at the University of Vienna, where he worked under Peter Schuster on quasispecies theory and with Karl Sigmund on evolutionary game theory. He earned his doctorate sub auspiciis praesidentis, the highest academic honor Austria can bestow on a graduating student. He moved to Oxford, where he collaborated with Robert May (later Lord May of Oxford) on spatial evolutionary dynamics and virus population models. He established the first center for theoretical biology at the Institute for Advanced Study in Princeton in 1998. In 2003, he came to Harvard to found the Program for Evolutionary Dynamics (PED), where he would spend two decades formalizing the mathematics of cooperation, cancer evolution, language emergence, and infection dynamics.
His landmark 2006 paper in Science, “Five Rules for the Evolution of Cooperation,” laid out the theoretical architecture that his 2011 book SuperCooperators: Why We Need Each Other to Succeed (co-written with science journalist Roger Highfield) would translate for a general audience. The core argument is elegant and, on its face, optimistic: natural selection, left alone, favors defectors over cooperators, but five distinct mechanisms can reverse this tendency and allow cooperation to evolve. Those mechanisms are kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. Each mechanism can be reduced to a simple mathematical rule specifying the conditions under which cooperation becomes the favored strategy. Each rule expresses a threshold: when the benefit-to-cost ratio of a cooperative act exceeds a critical value determined by the mechanism’s structure, cooperation wins.
The book is earnest. It is hopeful. It tells a story about vampire bats sharing blood meals, about cancer as a failure of cellular cooperation, about human language as the greatest cooperative innovation since the gene. Nowak calls humans “supercooperators” because we are the only species that deploys all five mechanisms simultaneously. The implication is that our capacity for cooperation is not just biologically real but biologically supreme. We are, in his framework, evolution’s greatest collaborative achievement.
This is all true. And none of it prevents the mathematics from being turned inside out.
The Five Mechanisms as Five Exploits
What Nowak mapped are not merely descriptions of how cooperation arises. They are, read from the other direction, specifications for how cooperation can be manufactured, directed, and harvested by any actor with sufficient control over the relevant variables. Each mechanism contains its own vulnerability. Each rule that tells you how to promote cooperation also tells you how to engineer compliance that feels like cooperation to the people inside the system.
Direct Reciprocity: The Obligation Engine
Direct reciprocity is the simplest mechanism: I help you now, you help me later, and we both benefit as long as we expect to interact again. Nowak’s mathematical condition is precise. Cooperation through direct reciprocity succeeds only when the probability of future interaction between the same two individuals exceeds the cost-to-benefit ratio of the cooperative act. If you and I will meet again many times, the cost of helping you today is offset by the expected return from your future help. The strategy that dominates in this environment is not pure tit-for-tat (which is too brittle, collapsing into mutual defection after a single error) but “win-stay, lose-shift,” a more forgiving strategy that sustains cooperation through noise.
The exploit is in the precondition. If you can engineer a situation where people believe they will interact with you repeatedly and indefinitely, you can extract cooperation from them even when the exchange is not mutual. Subscription services, employer-employee relationships with annual review cycles, government benefit programs tied to ongoing compliance, social media platforms that reward daily engagement: all of these create artificial conditions of repeated interaction. The person inside the system cooperates because their evolved psychology recognizes the pattern. They feel the pull of reciprocity. They return to the platform, they renew the subscription, they comply with the bureaucratic requirement, because the structure tells them the relationship will continue and defection carries a cost.
But the entity on the other side of the interaction is not bound by the same psychology. A corporation does not feel the tug of reciprocal obligation. A government agency does not experience guilt for failing to return a favor. The asymmetry is structural: the human cooperates because direct reciprocity is wired into primate social cognition; the institution extracts because it designed the interaction pattern to trigger exactly that response. The “repeated game” is real for the person and fictional for the institution, which can end the relationship, change the terms, or alter the benefit-to-cost ratio at any time without experiencing the psychological cost of defection.
Consider the modern employment relationship. An employee cooperates (works hard, stays late, defers complaints) because the structure of employment creates an expectation of continued interaction: there will be another paycheck, another review, another year. The employer benefits from this cooperation while retaining the unilateral power to terminate the relationship. The employee’s cooperation is genuine. The employer’s reciprocity is contingent. Nowak’s mathematics describe the employee’s behavior perfectly. They do not describe the employer’s, because the employer is not playing a repeated game. The employer is playing a series of one-shot games while the employee believes both parties are in a repeated game. This mismatch is not a bug in the model. It is the exploit.
Indirect Reciprocity: The Reputation Weapon
Nowak considers indirect reciprocity the most important mechanism for human cooperation, and he is probably right. Indirect reciprocity works through reputation: I help you not because I expect you to help me, but because others are watching, and my willingness to help builds a reputation that will cause others to help me in the future. The mathematical condition is that the probability of knowing someone’s reputation must exceed the cost-to-benefit ratio of cooperation. Language, Nowak argues, evolved in part to serve this mechanism. We gossip. We evaluate. We track who is trustworthy and who is not. This reputational calculus is what allows cooperation to scale beyond pairs of individuals who interact repeatedly.
The danger is obvious and immense. Whoever controls the reputation infrastructure controls the conditions for cooperation. And in the modern world, reputation infrastructure is not distributed among gossiping primates. It is centralized in databases.
Credit scoring systems (FICO in the United States, similar systems globally) are indirect reciprocity engines. They assign each person a reputation score based on their history of “cooperation” with financial institutions. A high score means you have reliably cooperated (paid debts, maintained accounts, avoided default). The score then determines whether others will cooperate with you (extend credit, offer favorable terms, rent you an apartment). The mathematics are identical to Nowak’s model. The probability of knowing your reputation is essentially 1.0 in a world of universal credit reporting. Therefore, the threshold for cooperation is easily met, and people cooperate.
But cooperate with what? With whom? The content of “cooperation” in a credit scoring system is defined by the institutions that build and maintain the scoring model. Cooperation means paying your bills. It means maintaining debt. It means participating in a financial system on its terms. The reputation system does not reward you for helping your neighbor move furniture or lending your car to a friend in need. It rewards you for being a reliable revenue source for financial institutions. The indirect reciprocity mechanism is operating exactly as Nowak describes. The mathematics are satisfied. But the cooperation is directed, not organic. It serves the architects of the reputation system, not the cooperators within it.
China’s social credit experiments take this further, attaching reputational scores to civic behavior, political speech, social associations, and consumption patterns. The mathematics are the same. The mechanism is the same. The outcome is that “cooperation” becomes indistinguishable from “compliance,” and the person inside the system cannot easily tell the difference, because the psychological experience of cooperating to maintain one’s reputation feels the same whether the reputation system is tracking genuine prosocial behavior or political obedience.
Social media platforms represent a third variant. Platforms like Instagram, TikTok, and formerly Twitter construct reputation systems (follower counts, likes, shares, verification badges) that trigger indirect reciprocity behavior. Users cooperate with the platform (producing content, engaging with others’ content, spending time on the platform) because the reputation system rewards them for doing so. The platform harvests this cooperation as engagement metrics, advertising revenue, and behavioral data. The user experiences the warm glow of reputational validation. The platform experiences profit. The mathematics of indirect reciprocity are perfectly satisfied in both directions. The exploitation is invisible precisely because it operates through a mechanism that evolution shaped to feel good.
Network Reciprocity: Whoever Designs the Graph Wins
Nowak’s third mechanism, developed in his landmark 1992 Nature paper with Robert May, showed that the spatial structure of interactions matters enormously. In a well-mixed population (where everyone interacts with everyone equally), defectors always win. But when interactions are local, restricted to neighbors on a network, cooperators can form clusters that protect themselves from exploitation. Cooperators surrounded by other cooperators thrive; defectors on the edge of cooperative clusters can invade, but the cluster structure slows the invasion and allows cooperation to persist.
The strategic implication is that whoever controls network topology controls the conditions for cooperation. This is not a metaphor. It is a direct application of the mathematics.
Social media algorithms determine who sees whose content, who appears in whose feed, who gets recommended as a connection. These algorithms are network reciprocity engines. They construct the “spatial structure” of online social interaction. A platform that clusters users into engagement-optimized groups is, in Nowak’s terms, constructing a network topology. If the topology is designed to maximize engagement (which is to say, to maximize the platform’s extraction of attention), then the cooperative clusters that form will be optimized for engagement, not for the welfare of the cooperators.
Corporate organizational design is another application. Who reports to whom, who collaborates with whom, who has access to information and who does not: these are network topology decisions. A company that understands network reciprocity can design org charts that promote exactly the cooperative behaviors it wants (cross-functional collaboration, knowledge sharing, collective problem-solving) while preventing the formation of cooperative clusters that might oppose management (unions, whistleblower networks, collective bargaining groups). The mathematics tell you which structures promote cooperation and which fragment it. The application is straightforward.
Gerrymandering is network reciprocity applied to democratic geography. By controlling which voters are grouped into which districts, political actors control the spatial structure of electoral cooperation. Voters who might form cooperative clusters around shared interests are separated. Voters whose “cooperation” (voting behavior) serves the redistricting party are grouped together. The mathematics of spatial evolutionary dynamics describe exactly why this works and how to optimize it.
Group Selection: The Factory of Tribes
Nowak’s treatment of group selection (which he and others now call multilevel selection) demonstrates that groups of cooperators outcompete groups of defectors, even when defectors dominate within groups. The mechanism requires that groups compete, that there is variation in the level of cooperation between groups, and that groups with more cooperators produce more offspring groups. Under these conditions, cooperation at the group level is favored even though individual defectors within groups do better than individual cooperators.
The exploit is the deliberate manufacture of group identity and intergroup competition. Nowak’s own reviewers noted the problem clearly: group selection favors within-group niceness and between-group nastiness. This is the mathematical basis of tribalism. It is also, historically, the most reliable mechanism by which authoritarian movements generate internal cohesion.
If you want a population to cooperate internally (pay taxes, report dissent, sacrifice personal interests for collective goals), you manufacture an external threat. The perceived competition between groups raises the benefit-to-cost ratio of within-group cooperation. Nationalists understand this intuitively. So do corporate culture architects who position their company against competitors while demanding employee loyalty. So do political parties that define themselves primarily through opposition. The mathematics of multilevel selection explain why “rally around the flag” effects work, why wartime economies produce extraordinary domestic cooperation, and why authoritarian regimes invest so heavily in identifying and publicizing external enemies.
The earnestness of Nowak’s presentation (he sees group selection as enabling the great cooperative achievements of human civilization, from agriculture to the United Nations) obscures how perfectly the same mathematics describe the cooperative achievements of fascism. The cooperative group that builds a hospital and the cooperative group that builds an internment camp are both satisfying the mathematical conditions for multilevel selection. The model does not distinguish between them. It cannot. The variables are the same.
Kin Selection: Manufacturing Family Where None Exists
Kin selection, formalized by W.D. Hamilton in 1964, is the oldest and most biologically grounded of the five mechanisms. Organisms cooperate with genetic relatives in proportion to their degree of relatedness, because helping a relative who shares your genes indirectly promotes the survival of those shared genes. Hamilton’s rule states that altruism is favored when the coefficient of relatedness between donor and recipient exceeds the cost-to-benefit ratio of the altruistic act. Nowak has a complicated relationship with Hamilton’s rule (his 2010 Nature paper with E.O. Wilson and Corina Tarnita argued that kin selection is less explanatory than previously thought, provoking a famous counterresponse signed by over 130 biologists), but the mechanism remains one of his five pillars.
The exploit is the simulation of kinship where none exists. “We are family.” “Band of brothers.” “Our company family.” “Fellow citizens.” “Children of God.” These are not merely sentimental phrases. They are invocations of kin selection psychology, designed to lower the threshold at which people will sacrifice personal interest for the group. When a military unit trains together, eats together, sleeps together, suffers together, and adopts shared rituals, symbols, and origin stories, it is manufacturing fictive kinship. The result is that soldiers will take risks for their unit-mates that they would not take for strangers, because their psychology has been calibrated to treat those unit-mates as kin.
Religious organizations, fraternities, political movements, cults, and nationalist ideologies all exploit this mechanism. The more completely an institution can simulate the markers of genetic relatedness (shared appearance through uniforms, shared language through jargon, shared history through founding myths, shared suffering through initiation rites), the more effectively it triggers kin selection psychology, and the more cooperation it can extract from its members. The cost of this cooperation is borne by the members. The benefit accrues to whoever designed the kinship simulation.
The Epstein Entanglement: A Case Study in the Exploitation of Cooperation Science
Any serious discussion of Martin Nowak’s work must confront the fact that the Program for Evolutionary Dynamics, the institutional home of his cooperation research, was founded with $6.5 million from Jeffrey Epstein. This was the largest single gift Epstein made to Harvard, part of a total of more than $9 million in donations to the university between 1998 and 2007. Epstein, a convicted sex offender who would later be charged with sex trafficking before his death in federal custody in 2019, did not merely donate money and walk away. He embedded himself in the program.
Harvard’s own 2020 review found that after Epstein’s 2008 conviction and release from prison, he continued to visit the PED offices more than 40 times between 2010 and 2018. He had a personal office in Nowak’s lab. He had a key card. He was typically accompanied by young women described as his assistants. His publicist requested that PED post information about Epstein on the harvard.edu domain because, as the publicist wrote, it would be helpful for Google search results. PED complied. Epstein’s foundation page was linked from the PED website under a tab labeled “Friends.” Epstein was the only “Friend” listed.
More recently, documents released by the U.S. Department of Justice in 2025 revealed that Epstein’s involvement went beyond access and reputation-laundering. He discussed research topics with Nowak and his graduate students. He suggested lines of inquiry, including “commercial evolution” and “prelife.” He facilitated visa arrangements for at least one graduate student. He funneled scholarship money through a Ph.D. student to young female mathematicians in Romania. He reviewed page proofs of a Nature paper before publication and offered advice on handling criticism. In 2025, Nowak was placed on administrative leave a second time after his name appeared more than 8,000 times in the newly released DOJ Epstein files.
The irony is lacerating. Epstein was a man who built his entire social and financial empire on the exploitation of cooperation mechanisms. His method was indirect reciprocity: he cultivated relationships with scientists, politicians, and financiers by offering gifts, access, and introductions, building a reputation as a brilliant and generous patron of science. He used network reciprocity: he positioned himself as a hub connecting elite nodes (Harvard professors, tech billionaires, heads of state), making himself indispensable as a broker of social capital. He manufactured fictive kinship: his dinners, his island retreats, his intellectual salons created a sense of belonging and shared identity among participants. He exploited direct reciprocity: every gift came with an implicit expectation of return, whether it was a letter of reference, a favorable public statement, or simply continued access and association.
And he funded, specifically and deliberately, the research program that mathematically formalized every one of these strategies. He did not fund a chemistry lab or an engineering department. He funded the mathematics of cooperation. He then used the institutional affiliation (Harvard, the Program for Evolutionary Dynamics) as a reputational asset, laundering his public image through association with the most prestigious cooperative institution in American academia.
Nowak has not been charged with any crime related to Epstein’s offenses. The Harvard review found policy violations, not criminal conduct. But the structural relationship between Epstein and PED is itself a perfect illustration of the very dynamics Nowak’s research describes. Epstein was a defector masquerading as a cooperator, using the mechanisms of cooperation (reputation, network position, reciprocal obligation, fictive kinship) to extract value from a system whose participants genuinely believed they were cooperating for the advancement of knowledge. The mathematics predicted this possibility. The researchers did not see it, or chose not to.
The Cyclical Trap
The deepest and most troubling insight in Nowak’s work is the finding that cooperation is inherently cyclical. Cooperators increase in number and trust, building successful clusters and institutions. Then a minority of defectors, positioned to exploit the high-trust environment, invade. Cooperation collapses. Eventually, cooperators rebuild. The cycle repeats. Nowak frames this as a feature of evolutionary dynamics, a permanent oscillation that can be modulated but never eliminated.
For a government or corporation seeking to exploit cooperation, this cyclical pattern is not a problem. It is the business model. The cycle describes exactly what extraction looks like over time. During the cooperative phase, the institution harvests trust, labor, engagement, compliance, and revenue. During the collapse phase, the institution restructures, rebrands, and resets the conditions for a new cooperative phase. The people inside the system experience the collapse as a betrayal. The institution experiences it as a cost of doing business.
Platform companies cycle through this pattern visibly. A new platform launches, cultivates a cooperative community of early adopters, builds network effects, then monetizes by degrading the experience for users while extracting more value from advertisers. Users eventually defect (leave the platform), but by then the platform has captured enough network position to survive, or a new platform launches and the cycle restarts. This is Nowak’s evolutionary dynamic playing out in real time, at internet speed.
Political cycles follow the same pattern. A new administration or movement builds cooperative coalitions around shared goals. Trust increases. Policy achievements accumulate. Then insiders begin to extract (corruption, patronage, self-dealing), trust erodes, the coalition fragments, and a new movement arises to rebuild cooperation on different terms. The cycle is so regular that political scientists have formalized it independently of evolutionary biology, but Nowak’s mathematics show that it is not unique to politics. It is a property of any system in which cooperation and defection coexist.
What Nowak Missed, or Chose Not to Say
SuperCooperators is a book about the conditions that produce cooperation. It is not a book about the conditions that produce just cooperation. This is not a minor omission. It is the central weakness of the work.
Nowak’s five mechanisms are content-neutral. They describe the structural conditions under which organisms will choose to cooperate, but they are silent on what the cooperation is for. Cooperation to build a hospital and cooperation to build a surveillance state satisfy the same mathematical conditions. Within-group cooperation that produces a democratic parliament and within-group cooperation that produces a paramilitary organization both emerge from the same multilevel selection dynamics. A reputation system that tracks genuine generosity and a reputation system that tracks political loyalty both promote cooperation through indirect reciprocity.
The book occasionally gestures toward this problem. Nowak acknowledges that defectors can invade cooperative groups, that cooperation cycles, that punishment mechanisms can themselves become exploitative. But these acknowledgments are treated as complications within a fundamentally optimistic narrative, not as structural features of the mathematics that demand equal weight. The title is SuperCooperators, not SuperExploiters. The framing celebrates cooperation’s triumphs without adequately confronting the fact that the same mathematics, applied with different intent, describe cooperation’s capture.
This omission is not unique to Nowak. It is endemic to a certain strain of evolutionary optimism that mistakes the existence of cooperation for its benevolence. Cooperation is not inherently good. It is a strategy. It can be deployed in service of any goal. The mathematics do not care. A reader who absorbs Nowak’s five rules as a celebration of human goodness will be poorly prepared to recognize those same rules operating as mechanisms of control in their workplace, their government, their social media feed, and their financial system.
The Responsibility of the Mapmaker
Nowak drew a map. The map is accurate. The territory it describes is real. But a map can be read by anyone, and the same map that helps a traveler find water helps an army find the traveler. The five rules for the evolution of cooperation are, simultaneously, five rules for the engineering of compliance. The mathematics are identical. Only the intent differs.
The question is not whether Nowak should have refrained from publishing his research. Suppressing accurate mathematics is never the answer. The question is whether the scientific community and the reading public have a responsibility to read the map with both eyes open: to see not only the beautiful cooperative structures it reveals but also the exploitative architectures it enables. The answer, given what we now know about who funded the map’s creation and what they used its institutional credibility to accomplish, should be self-evident.
Cooperation is real. It is mathematically demonstrable. It is essential to every level of biological and social organization. It is also the single most exploitable feature of human psychology, and anyone who tells you otherwise is either not paying attention or is the one doing the exploiting.
#consumerValue #cooperation #engineering #epsteinFiles #fiveMechanisms #harvard #martinNowak #needingEachOther #oxford #politics #princeton #research #rogerHighfield