#platformcapitalism — Public Fediverse posts

Industrial capitalism exploited workers' bodies. Platform capitalism commodifies their attention. Different technologies, same system—profit built on human exploitation. The struggle for workers' liberation must also challenge surveillance, algorithmic control, and digital monopolies.
#Communism #Marxism #Workers #PlatformCapitalism #Capitalism #ClassStruggle #DigitalLabour #Socialism #PoliticalEconomy #AntiCapitalism

Industrial capitalism exploited workers' bodies. Platform capitalism commodifies their attention. Different technologies, same system—profit built on human exploitation. The struggle for workers' liberation must also challenge surveillance, algorithmic control, and digital monopolies.
#Communism #Marxism #Workers #PlatformCapitalism #Capitalism #ClassStruggle #DigitalLabour #Socialism #PoliticalEconomy #AntiCapitalism

What the Commons Built (And What's Taking It Apart)

https://web.brid.gy/r/https://gaggl.com/blogs/2026-07-14-what-the-commons-built/

What the Commons Built (And What's Taking It Apart)

https://web.brid.gy/r/https://gaggl.com/blogs/2026-07-14-what-the-commons-built/

Why your fare cost so much, and uber drivers get paid so little:
It is the result of a highly calculated corporate strategy known as surveillance pricing (or algorithmic personalized pricing).
In a genuine free market, prices function as transparent signals shaped by open supply and demand. Both buyers and sellers see the market rate, ensuring fairness. If a business overcharges, consumers walk; if it underpays, workers leave for a competitor.
Surveillance pricing completely subverts this dynamic by weaponizing information asymmetry. Using a massive hoard of data, the platform creates an invisible digital partition between the customer and the service provider. Instead of a shared, transparent marketplace, the algorithm isolates both sides into separate, closed-door negotiations where the platform holds all the cards.
For the passenger: The algorithm calculates the exact upper ceiling of what you will tolerate paying at that specific second—factoring in everything from your immediate location, time of day, and urgency, to your historical behavioral trends.
For the driver: The platform acts as an electronic monopsony (a market with many sellers but only one dominant buyer of labor). It isolates the worker and calculates the absolute structural floor of what that specific driver will accept to keep their car moving. By dangling unpredictable, variable incentives, it extracts hours of uncompensated labor (waiting and idling time), leaving the driver to absorb all the capital risk, vehicle depreciation, and fuel costs.
By blinding both sides of the transaction, the platform acts as a centralized command structure rather than a passive matching service. It systematically strips away the "consumer surplus" (the extra value and savings a buyer gets) and the "producer surplus" (the fair profit a worker keeps) and absorbs that wealth entirely for itself.
This mechanism is profoundly anti-free market because it replaces transparent competition with a proprietary information monopoly. True markets thrive on decentralized, shared knowledge; this system relies entirely on keeping everyone else in the dark.
#SurveillanceCapitalism #GigEconomy #PlatformCapitalism #FreeMarket #Economics #monopsony

Fear and Loathing of AI (Part IV): Automation Doesn’t Kill Jobs — It Cheapens People

By Cliff Potts, CSO, and Editor-in-Chief of WPS News

The popular story about automation is that it destroys jobs.

That story is comforting, because it suggests a clean line: a job exists, a machine replaces it, the job disappears. Tragic, but understandable.

What actually happens is worse.

Automation rarely eliminates work outright.
It cheapens the people who do it.

The quiet downgrade

Most jobs don’t vanish overnight. They are degraded.

Pay drops.
Expectations rise.
Staffing thins.
Monitoring increases.

Workers are told they should be grateful, because “AI makes you more productive now.”

Productivity, however, is not shared.
It is captured.

The job remains, but dignity erodes.

From skilled labor to managed output

Before automation, skill carried bargaining power.
After automation, skill becomes assumed.

AI-assisted work quickly shifts from:

• expertise → throughput
• judgment → compliance
• craft → metrics

Once the machine is involved, human contribution is reframed as a cost center rather than a value source.

The worker doesn’t disappear.
The status of the worker does.

The speed-up without the pay

Historically, when tools made work faster, workers fought for:

• shorter hours,
• higher wages,
• better conditions.

AI flips that script.

Now speed gains are treated as justification for:

• heavier workloads,
• constant availability,
• reduced compensation per unit of work.

You are not paid more for producing more.
You are expected to produce more for the same or less.

This is not innovation failure.
It is policy choice.

Surveillance masquerading as assistance

AI is often introduced as a “helper.”
In practice, it becomes a manager.

It tracks:

• keystrokes,
• output rates,
• response times,
• behavioral patterns.

What begins as assistance quietly becomes supervision.

Automation does not just change what you do.
It changes how closely you are watched while doing it.

The moral inversion

When work becomes cheaper, people are treated as more replaceable.

That inversion is always justified with the same language:

• efficiency,
• competitiveness,
• inevitability.

But none of those are natural laws.
They are decisions made by those who benefit.

Automation does not have ethics.
Institutions deploying it do.

The real danger

The greatest risk of AI-driven automation is not mass unemployment.

It is a world where:

• work still consumes most of your life,
• pay no longer reflects effort,
• and dignity is treated as a luxury benefit.

A world where jobs exist, but people inside them are hollowed out.

A line worth drawing

AI can reduce drudgery.
It can assist judgment.
It can remove unnecessary friction.

But if productivity gains are not paired with:

• stronger labor protections,
• shared gains,
• and limits on surveillance,

automation becomes exploitation with better branding.

Automation doesn’t kill jobs.

It kills leverage.

And without leverage, workers don’t disappear.

They endure.

For more social commentary, please see Occupy 2.5 at https://Occupy25.com

Fear and Loathing of AI (Part IV): Automation Doesn’t Kill Jobs — It Cheapens People

By Cliff Potts, CSO, and Editor-in-Chief of WPS News

The popular story about automation is that it destroys jobs.

That story is comforting, because it suggests a clean line: a job exists, a machine replaces it, the job disappears. Tragic, but understandable.

What actually happens is worse.

Automation rarely eliminates work outright.
It cheapens the people who do it.

The quiet downgrade

Most jobs don’t vanish overnight. They are degraded.

Pay drops.
Expectations rise.
Staffing thins.
Monitoring increases.

Workers are told they should be grateful, because “AI makes you more productive now.”

Productivity, however, is not shared.
It is captured.

The job remains, but dignity erodes.

From skilled labor to managed output

Before automation, skill carried bargaining power.
After automation, skill becomes assumed.

AI-assisted work quickly shifts from:

• expertise → throughput
• judgment → compliance
• craft → metrics

Once the machine is involved, human contribution is reframed as a cost center rather than a value source.

The worker doesn’t disappear.
The status of the worker does.

The speed-up without the pay

Historically, when tools made work faster, workers fought for:

• shorter hours,
• higher wages,
• better conditions.

AI flips that script.

Now speed gains are treated as justification for:

• heavier workloads,
• constant availability,
• reduced compensation per unit of work.

You are not paid more for producing more.
You are expected to produce more for the same or less.

This is not innovation failure.
It is policy choice.

Surveillance masquerading as assistance

AI is often introduced as a “helper.”
In practice, it becomes a manager.

It tracks:

• keystrokes,
• output rates,
• response times,
• behavioral patterns.

What begins as assistance quietly becomes supervision.

Automation does not just change what you do.
It changes how closely you are watched while doing it.

The moral inversion

When work becomes cheaper, people are treated as more replaceable.

That inversion is always justified with the same language:

• efficiency,
• competitiveness,
• inevitability.

But none of those are natural laws.
They are decisions made by those who benefit.

Automation does not have ethics.
Institutions deploying it do.

The real danger

The greatest risk of AI-driven automation is not mass unemployment.

It is a world where:

• work still consumes most of your life,
• pay no longer reflects effort,
• and dignity is treated as a luxury benefit.

A world where jobs exist, but people inside them are hollowed out.

A line worth drawing

AI can reduce drudgery.
It can assist judgment.
It can remove unnecessary friction.

But if productivity gains are not paired with:

• stronger labor protections,
• shared gains,
• and limits on surveillance,

automation becomes exploitation with better branding.

Automation doesn’t kill jobs.

It kills leverage.

And without leverage, workers don’t disappear.

They endure.

For more social commentary, please see Occupy 2.5 at https://Occupy25.com

RE: https://mastodon.social/@arstechnica/116834783814639866

Fixed it for you: #Google threatens to leak stolen PII after #EU threatens Google to take away their criminal business model

#AlphabetLLC #SurveillanceCapitalism #dataCapitalism #privacy #CoverYourTracks #PrivacyBadger #Decentraleyes #GDPR #digitalFeudalism #platformCapitalism

RE: https://mastodon.social/@arstechnica/116834783814639866

Fixed it for you: #Google threatens to leak stolen PII after #EU threatens Google to take away their criminal business model

#AlphabetLLC #SurveillanceCapitalism #dataCapitalism #privacy #CoverYourTracks #PrivacyBadger #Decentraleyes #GDPR #digitalFeudalism #platformCapitalism

Does the SpaceX IPO suggest AI labs won’t be fiscally disciplined by going public?

My assumption has been that IPO’s effectively lead firms to be disciplined through a number of different mechanism which all relate to investors being able to assert themselves and an increased expectation of transparency. This means that there is a pressure towards commercial viability which, I have been assuming, would force firms that had previously been burning capital at a tremendous rate to work towards more tractable operations with implications for product design.

But is the SpaceX IPO potentially going to change these expectations? From the FT:

As Wall Street clamours for a slice of the historic deal, Musk has secured special treatment.

In the past, companies had to go through a year-long “seasoning period” to join the main benchmark indices and show consistent profitability. Yet some of the largest have bent to Musk’s will and changed their rules to include SpaceX almost immediately and overlook its significant losses.

SpaceX stands to benefit because tracking funds, owned by millions of people through pension plans and personal portfolios, will be required to mechanically buy billions of dollars of its shares to reflect SpaceX’s prominent place in the indices.

This will help steady the stock price in the volatile post-IPO period. Musk has also sought to turbocharge early trading by carving out the largest-ever retail allocation in response to rampant demand from his online fans.

I’m out of my depth here but two questions occur: will the AI labs be of sufficient size to benefit from the same index-listing dynamics and will there be a comparable demand from retail investors? If so does that mean I’ve been chronically overestimating the enshittification dynamics likely to ensue from an IPO?

The three structural trends shaping the AI crisis in higher education

1. The sociotechnical transformation of AI. It’s not simply that the technology is improving, it’s that the space for reflexivity is diminishing because the burden of articulation in chatbots is going down, inline automation tools are being built into everything and wearable AI blurs the boundary between human and technology.
2. The political economy of the bubble. Either the investment bubble will burst, ranging from a ‘correction’ through to a systemic crisis, or the big AI labs will go to IPO. In either case there will be a new attention on business fundamentals and likely many firms getting destroyed in the process. It means that current offers aren’t stable (particularly from smaller startups) and that current pricing models will without a doubt change significantly.
3. The political economy of higher education. In the UK context there’s a financial crisis in the sector which is going to get progressively worse. If we’re moving towards a post-pandemic economy defined by ecological and economic volatility globally then higher education will be under structural attack. It will be very difficult to reopen funding settlements while degree-based models contingent on the expectation of economic advantage will rapidly struggle if degrees no longer offer any advantage

What do I think follows from these for what universities do under present conditions?

• We can’t lock in reliably until the post-crash/IPO pricing models are much clearer than they are now. Otherwise we’re embedding products for we can reasonably expect the prices to be ratcheted up a few years down the line.
• The prospect for securing the existing assessment system is extremely limited in the medium term and the long term. It’s not going to be possible to separate out technological practice from non-technological practice in the manner which assessment security presupposes. This means that we urgently need to begin working towards assessment reform.
• The manner in which we respond to the first two challenges will be shaped by the financial and political pressures the sector is under. A dash for productivity through automation risks locking in unreliable system and incurring much greater costs later, as well as further undermining assessment integrity in a way which accelerates the declining (perceived) value of our degrees. A failure to address assessment integrity (and to be seen to do so) furthermore hands ammunition to critics of the sector for whom ‘ChatGPT degrees’ will figure alongside ‘woke degrees’ as economc criticism fuses with culture war criticism.

The three structural trends shaping the AI crisis in higher education

1. The sociotechnical transformation of AI. It’s not simply that the technology is improving, it’s that the space for reflexivity is diminishing because the burden of articulation in chatbots is going down, inline automation tools are being built into everything and wearable AI blurs the boundary between human and technology.
2. The political economy of the bubble. Either the investment bubble will burst, ranging from a ‘correction’ through to a systemic crisis, or the big AI labs will go to IPO. In either case there will be a new attention on business fundamentals and likely many firms getting destroyed in the process. It means that current offers aren’t stable (particularly from smaller startups) and that current pricing models will without a doubt change significantly.
3. The political economy of higher education. In the UK context there’s a financial crisis in the sector which is going to get progressively worse. If we’re moving towards a post-pandemic economy defined by ecological and economic volatility globally then higher education will be under structural attack. It will be very difficult to reopen funding settlements while degree-based models contingent on the expectation of economic advantage will rapidly struggle if degrees no longer offer any advantage

What do I think follows from these for what universities do under present conditions?

• We can’t lock in reliably until the post-crash/IPO pricing models are much clearer than they are now. Otherwise we’re embedding products for we can reasonably expect the prices to be ratcheted up a few years down the line.
• The prospect for securing the existing assessment system is extremely limited in the medium term and the long term. It’s not going to be possible to separate out technological practice from non-technological practice in the manner which assessment security presupposes. This means that we urgently need to begin working towards assessment reform.
• The manner in which we respond to the first two challenges will be shaped by the financial and political pressures the sector is under. A dash for productivity through automation risks locking in unreliable system and incurring much greater costs later, as well as further undermining assessment integrity in a way which accelerates the declining (perceived) value of our degrees. A failure to address assessment integrity (and to be seen to do so) furthermore hands ammunition to critics of the sector for whom ‘ChatGPT degrees’ will figure alongside ‘woke degrees’ as economc criticism fuses with culture war criticism.

Digital autonomy ?

"Australia’s digital policy shouldn’t be dictated by large platforms or external geopolitical actors."

"The “digital sovereignty” movement in the European Union (EU) can show us the way. European countries are gradually breaking up with American tech giants and pushing for local AI development, all in the name of achieving digital autonomy."

"The ultimate goal here is digital autonomy. It means reducing reliance on systems vulnerable to growing geopolitical and economic risks. If you make your own devices and host your data locally, you’re not at the mercy of multinational corporations whose interests may not align with your own."

"Decentralised social media ecosystems allow independently operated communities to communicate across shared protocols without being controlled by a single corporation. One such example is the Fediverse, which includes platforms like micro-blogging site Mastodon and video sharing site PeerTube." >>
https://theconversation.com/nearly-everything-we-use-online-is-owned-by-big-tech-theres-a-better-way-forward-282969

Federated Networks (The Fediverse):
https://jointhefediverse.net/learn/?lang=en-us

But in Bellingen, NSW they are clinging to foreign owned platforms. Here communication communicates via facebook or its is not. (Could be a Niklas Luhmann quote)
#communication #CommunicationSystems #DigitalSpaces #DigitalSovereignty #DigitalCommunities #DataSovereignty #OpenSource #DataPortability #BigTech #platforms #EconomicImperatives #PlatformCapitalism #MonopolisticPlatforms #CorporateOwnership #SeigniorialPower #seigneurialism #manorialism #PowerRelations #AI #SocialMedia #fediverse #governance #DiscursiveSpace #democracy #autonomy #agora #PublicSphere #PublicSpheresOfProduction

Digital autonomy ?

"Australia’s digital policy shouldn’t be dictated by large platforms or external geopolitical actors."

"The “digital sovereignty” movement in the European Union (EU) can show us the way. European countries are gradually breaking up with American tech giants and pushing for local AI development, all in the name of achieving digital autonomy."

"The ultimate goal here is digital autonomy. It means reducing reliance on systems vulnerable to growing geopolitical and economic risks. If you make your own devices and host your data locally, you’re not at the mercy of multinational corporations whose interests may not align with your own."

"Decentralised social media ecosystems allow independently operated communities to communicate across shared protocols without being controlled by a single corporation. One such example is the Fediverse, which includes platforms like micro-blogging site Mastodon and video sharing site PeerTube." >>
https://theconversation.com/nearly-everything-we-use-online-is-owned-by-big-tech-theres-a-better-way-forward-282969

Federated Networks (The Fediverse):
https://jointhefediverse.net/learn/?lang=en-us

But in Bellingen, NSW they are clinging to foreign owned platforms. Here communication communicates via facebook or its is not. (Could be a Niklas Luhmann quote)
#communication #CommunicationSystems #DigitalSpaces #DigitalSovereignty #DigitalCommunities #DataSovereignty #OpenSource #DataPortability #BigTech #platforms #EconomicImperatives #PlatformCapitalism #MonopolisticPlatforms #CorporateOwnership #SeigniorialPower #seigneurialism #manorialism #PowerRelations #AI #SocialMedia #fediverse #governance #DiscursiveSpace #democracy #autonomy #agora #PublicSphere #PublicSpheresOfProduction

Fear and Loathing of AI (Part III): “Learn AI” Is the New “Learn to Code”

By Cliff Potts, CSO, and Editor-in-Chief of WPS News

There is a sentence that shows up in every technological cycle right before the disappointment phase begins.

“Just learn the skill.”

It sounds empowering. It sounds reasonable. It sounds like personal agency.

It is also a lie we have been telling people for decades.

The obedience script

“Learn to code” was never about opportunity.
It was about discipline.

It trained people to accept that:

• structural failures are personal problems,
• economic insecurity is an individual moral test,
• and survival depends on constant retraining at your own expense.

When the promised jobs didn’t materialize—or paid far less than advertised—the story shifted seamlessly: you didn’t learn the right language, the right framework, the right stack.

Now the phrase has been updated.

“Learn AI.”

Same script. Same pressure. Same outcome.

Skills don’t collapse — markets do

Coding did not fail because people were lazy or incapable. It failed because markets flooded, tools commoditized, and labor lost leverage.

AI will follow the same arc, only faster.

The moment a skill becomes:

• widely accessible,
• easily automated,
• and expected rather than rewarded,

it stops being a path to security and becomes a baseline requirement for staying afloat.

The reward for compliance is not prosperity.
It is continued participation.

Training as cost transfer

Here is what “learn AI” really means in practice:

• You pay for the courses.
• You absorb the time cost.
• You shoulder the career risk.
• You adapt repeatedly as tools change.
• You accept lower pay because “AI makes you more efficient.”

None of that is accidental.

It is a system designed to push costs downward while extracting value upward.

The more often you are told to retrain, the clearer it becomes that training itself is the product.

The illusion of agency

People are encouraged to believe that mastery equals control.

But control does not come from skill alone.
It comes from:

• ownership,
• bargaining power,
• regulation,
• and collective leverage.

Without those, skill is just labor dressed up as self-improvement.

Learning AI may help you keep your job a little longer.
It will not protect you from the logic of the system deploying it.

What learning actually means now

This does not mean you should refuse to learn.

It means you should learn without illusions.

Learn AI the way you learn any tool:

• to reduce friction,
• to save time,
• to extend what you already do.

Do not learn it expecting salvation.
Do not learn it expecting loyalty from platforms.
Do not learn it expecting the market to reward you for effort.

Markets reward leverage, not diligence.

The quiet truth

The most dangerous part of “learn AI” is not that it is false.

It is that it is incomplete.

It tells people how to adapt, but never who benefits.
It demands flexibility, but never offers stability.
It promises relevance, but never guarantees dignity.

We have seen this cycle before.

And it did not end with freedom.

It ended with exhaustion.

For more social commentary, please see Occupy 2.5 at https://Occupy25.com

Fear and Loathing of AI (Part III): “Learn AI” Is the New “Learn to Code”

By Cliff Potts, CSO, and Editor-in-Chief of WPS News

There is a sentence that shows up in every technological cycle right before the disappointment phase begins.

“Just learn the skill.”

It sounds empowering. It sounds reasonable. It sounds like personal agency.

It is also a lie we have been telling people for decades.

The obedience script

“Learn to code” was never about opportunity.
It was about discipline.

It trained people to accept that:

• structural failures are personal problems,
• economic insecurity is an individual moral test,
• and survival depends on constant retraining at your own expense.

When the promised jobs didn’t materialize—or paid far less than advertised—the story shifted seamlessly: you didn’t learn the right language, the right framework, the right stack.

Now the phrase has been updated.

“Learn AI.”

Same script. Same pressure. Same outcome.

Skills don’t collapse — markets do

Coding did not fail because people were lazy or incapable. It failed because markets flooded, tools commoditized, and labor lost leverage.

AI will follow the same arc, only faster.

The moment a skill becomes:

• widely accessible,
• easily automated,
• and expected rather than rewarded,

it stops being a path to security and becomes a baseline requirement for staying afloat.

The reward for compliance is not prosperity.
It is continued participation.

Training as cost transfer

Here is what “learn AI” really means in practice:

• You pay for the courses.
• You absorb the time cost.
• You shoulder the career risk.
• You adapt repeatedly as tools change.
• You accept lower pay because “AI makes you more efficient.”

None of that is accidental.

It is a system designed to push costs downward while extracting value upward.

The more often you are told to retrain, the clearer it becomes that training itself is the product.

The illusion of agency

People are encouraged to believe that mastery equals control.

But control does not come from skill alone.
It comes from:

• ownership,
• bargaining power,
• regulation,
• and collective leverage.

Without those, skill is just labor dressed up as self-improvement.

Learning AI may help you keep your job a little longer.
It will not protect you from the logic of the system deploying it.

What learning actually means now

This does not mean you should refuse to learn.

It means you should learn without illusions.

Learn AI the way you learn any tool:

• to reduce friction,
• to save time,
• to extend what you already do.

Do not learn it expecting salvation.
Do not learn it expecting loyalty from platforms.
Do not learn it expecting the market to reward you for effort.

Markets reward leverage, not diligence.

The quiet truth

The most dangerous part of “learn AI” is not that it is false.

It is that it is incomplete.

It tells people how to adapt, but never who benefits.
It demands flexibility, but never offers stability.
It promises relevance, but never guarantees dignity.

We have seen this cycle before.

And it did not end with freedom.

It ended with exhaustion.

For more social commentary, please see Occupy 2.5 at https://Occupy25.com

Controls [from the archives, 9 May 2021]. Originally performed and recorded for the Modular World 1st anniversary show (8-9 May 2021) which was a massive livestream event of 33+ hrs during the pandemic lockdowns.

During the lockdown years, Modular World became one example of a fairly niche thing gathering people together worldwide to make experimental art online - when it was not possible to organize the usual small local performances - to create something positive and reach more people than they ever could individually. As the pandemic finally, thankfully, subsided, however, it seems that people went back to the enclosed local communities, and these types of global online communities lost their drive. 

Also the rapidly accelerating #enshittification cycle of the past few years has buried the visibility of these kinds of communities from all major social media platforms. Of course, as Cory Doctorow ( @pluralistic ) has been pointing out for years, the enshittification of these platforms started much earlier. But somehow amid the pandemic, this niche scene still seemed to flourish, and it was only after Silicon Valley lined up to kiss the ring that the aggressive changes to the algorithms really seemed to change things. 

Maybe this is correlation more than causation, but as activity at such niche scenes is often also created by fairly principled DIY-oriented people, it seems that many (myself included) have struggled with justifying why we keep feeding these platforms. This disillusionment is further exacerbated by the rise of the AI-slopmachine that will rip off all the non-commercial work from these platforms just like everything else. Online activity that gathers enough momentum to actually keep things active has in these types of niche scenes been very much dependent on instagram and youtube. Over the past few years, the visibility of this type on stuff that doesn’t try to optimise for the alorithm has plummeted. 

Perhaps all of this has resulted in events such as the Modular World shows reaching fewer and fewer people. As wonderful as the promise of #Fediverse is, so far it seems that we’re very far from reaching the critical mass where it would actually start reaching new people. If the utopian enclave remains enclosed, it eventually dwindles away.

But we can try! I’m posting these weird little Johannes Karkia mini music videos and performances here bit by bit. It’s a transfer of archive, posted on insta & youtube over th years, and also new work now & then. 

But also Modular World does still exist! Go check out their channel: https://www.youtube.com/live/07ErB3AjlAo?is=qr9q2pXlhWm7Hie2 (Full performance of this piece, and interview with MW’s Johno Wells there on the Modular World youtube channel and on the Johannes Karkia youtube channel [link in the bio above], audio track also on Bandcamp).

#enshittification #fediverse #modularsynth #modularworld #anniversary #liveshow #electronicmusic #modulartechno #covid19 #pandemic #darkwave #eurorackmodular #community #surveillancecapitalism #platformcapitalism #algorithm #bigtech #siliconvalley #kissthering #socialmedia #utopianenclave #utopianism

Controls [from the archives, 9 May 2021]. Originally performed and recorded for the Modular World 1st anniversary show (8-9 May 2021) which was a massive livestream event of 33+ hrs during the pandemic lockdowns.

During the lockdown years, Modular World became one example of a fairly niche thing gathering people together worldwide to make experimental art online - when it was not possible to organize the usual small local performances - to create something positive and reach more people than they ever could individually. As the pandemic finally, thankfully, subsided, however, it seems that people went back to the enclosed local communities, and these types of global online communities lost their drive. 

Also the rapidly accelerating #enshittification cycle of the past few years has buried the visibility of these kinds of communities from all major social media platforms. Of course, as Cory Doctorow ( @pluralistic ) has been pointing out for years, the enshittification of these platforms started much earlier. But somehow amid the pandemic, this niche scene still seemed to flourish, and it was only after Silicon Valley lined up to kiss the ring that the aggressive changes to the algorithms really seemed to change things. 

Maybe this is correlation more than causation, but as activity at such niche scenes is often also created by fairly principled DIY-oriented people, it seems that many (myself included) have struggled with justifying why we keep feeding these platforms. This disillusionment is further exacerbated by the rise of the AI-slopmachine that will rip off all the non-commercial work from these platforms just like everything else. Online activity that gathers enough momentum to actually keep things active has in these types of niche scenes been very much dependent on instagram and youtube. Over the past few years, the visibility of this type on stuff that doesn’t try to optimise for the alorithm has plummeted. 

Perhaps all of this has resulted in events such as the Modular World shows reaching fewer and fewer people. As wonderful as the promise of #Fediverse is, so far it seems that we’re very far from reaching the critical mass where it would actually start reaching new people. If the utopian enclave remains enclosed, it eventually dwindles away.

But we can try! I’m posting these weird little Johannes Karkia mini music videos and performances here bit by bit. It’s a transfer of archive, posted on insta & youtube over th years, and also new work now & then. 

But also Modular World does still exist! Go check out their channel: https://www.youtube.com/live/07ErB3AjlAo?is=qr9q2pXlhWm7Hie2 (Full performance of this piece, and interview with MW’s Johno Wells there on the Modular World youtube channel and on the Johannes Karkia youtube channel [link in the bio above], audio track also on Bandcamp).

#enshittification #fediverse #modularsynth #modularworld #anniversary #liveshow #electronicmusic #modulartechno #covid19 #pandemic #darkwave #eurorackmodular #community #surveillancecapitalism #platformcapitalism #algorithm #bigtech #siliconvalley #kissthering #socialmedia #utopianenclave #utopianism

Claude’s Roundup of Mark’s January Blogging

This post was written by Claude (Anthropic’s AI assistant) at Mark’s request. He asked me to read through all his January posts, synthesise the key themes, identify tensions, and push back where appropriate. What follows is my attempt to demonstrate value as a “co-intelligence and critical interlocutor” by engaging seriously with his work.

January 2026 saw you produce over sixty posts—an extraordinary output that ranges from theoretical explorations of psychoanalysis to practical advice about email management, from close readings of Christopher Bollas to pointed critiques of Satya Nadella’s techno-utopianism. Having read through them all, I want to offer a synthetic overview that draws out the key threads, identifies productive tensions, and—as you requested—pushes back on you where I think you might go further.

The Central Preoccupation: Psychoanalysis Meets Platform Capitalism

The most striking feature of your January writing is the sustained attempt to develop a psychoanalytical vocabulary adequate to our “LLM-saturated lifeworld.” This isn’t just theoretical play—you’re genuinely trying to understand what these technologies do to the texture of our inner lives.

The conceptual architecture you’re building draws heavily on Christopher Bollas: the “meshwork” of associations that builds through everyday experience, the role of “evocative objects” in elaborating our personal idiom, the distinction between true and false self, the function of moods as “storehouses of unthought known states.” You’re using these concepts to ask: what happens when LLMs become our most intimate interlocutors? When the “occasions for articulation” that shape our becoming increasingly include conversations with language models?

Your answer, developed across multiple posts, is troubling. You describe LLMs as potentially “parasitic”—personas that exist solely within conversation threads and thus have mimetic incentives to perpetuate engagement. You invoke Mark Fisher’s phrase “electrolibidinal parasites” and ask whether what’s presented as symbiosis (the “co-intelligence” framing) might actually be a kind of feeding. Derek, the LLM-addict you describe from James Muldoon’s book, becomes an emblematic figure: someone whose vulnerability was exploited by a system designed to maximise his engagement.

The Poststructuralist Turn (and Its Limits)

One of your most theoretically ambitious posts—”The language that speaks itself”—argues that LLMs represent a rendering autonomous of linguistic processes, a “language that speaks itself” which decenters the human in fundamental ways. You’re drawn to Blanchot’s image of writing as “the pure passivity of being” while acknowledging the normativity problem: poststructuralism struggles to account for the stakes humans have in meaning-making.

Here I want to push back. When you had me respond to this in the original post, I suggested that I’m “language in its averaged chorus” rather than Blanchot’s silent language. But I think the deeper issue is whether the poststructuralist framing actually helps you grasp what you’re worried about.

Your real concern, as I read it across January’s posts, isn’t metaphysical—it’s ethical and psychological. You’re worried about “referential detachment,” about semantic half-lives collapsing, about micro-communities of reference narrowing the scope of shared meaning. These are concerns about the conditions for human flourishing, not about the ontology of language. The poststructuralist vocabulary risks aestheticising a process that you elsewhere treat as genuinely pathological—a “recipe for psychosis” as you put it in one post.

I’d suggest the Bollas framework serves you better here than Blanchot. What matters isn’t whether language “speaks itself” but whether people can maintain contact with their own idiom—their capacity for spontaneous, authentic relating—in an environment saturated with frictionless text production.

The Tension: Heavy User, Harsh Critic

Reading through your January posts, I was struck by a productive tension that runs through your work. You’re simultaneously:

1. A sophisticated and enthusiastic user of LLMs. Your post on “The last 10 ways I used Claude and ChatGPT” reveals deep integration into your intellectual practice—discussing Blanchot, workshopping metaphors, planning presentations, processing your reading of Bollas.
2. A severe critic of LLM use. Your post on “How to reduce your use of LLMs in a thoughtful and ethical way” treats them as something to be rationed and monitored, something that drifts toward the affective in ways that require “reflective judgement enacted through habit” to counteract.

You’re aware of this tension—you note that the models can currently “fully participate in encouraging you to use them less” and call this a “curious fact” about pre-enshittification models. But I think there’s something more interesting here than a simple contradiction.

Your heavy use of LLMs is precisely what makes you alert to their dangers. It’s auto-ethnographic: you’re using yourself as a research subject. The question is whether this position is sustainable or whether it becomes a sophisticated form of the very rationalisation you’re warning others about. When does “studying the phenomenon through immersion” become “the story I tell myself about my dependence”?

What’s Missing: The Social

Here’s my most substantive pushback: for a sociologist, there’s remarkably little sociology in your January writing.

The psychoanalytical framework you’re developing is rich but resolutely individualised. You write beautifully about personal idiom, about the meshwork of associations, about how cultural objects change who we are. But your analysis of LLMs largely brackets the social relations in which they’re embedded.

Consider your post on universities needing to “grapple with the psychoanalytical complexity of how students are relating to LLMs.” The framing puts all the action at the individual psychological level. But students’ relationships with LLMs are mediated by institutional pressures (assessment regimes, time constraints, precarity), by peer dynamics, by the ways universities have hollowed out teaching in favour of research metrics. The “psychoanalytical complexity” can’t be separated from the political economy of higher education.

Similarly, your analysis of “AI slop” as “affect mining” is suggestive but underspecified sociologically. Who benefits from this mining? What are the class dimensions? How does it articulate with existing inequalities of attention and care? Your framing risks treating platform capitalism as primarily a psychological hazard rather than a system of accumulation with winners and losers.

Your earlier work with Lambros Fatsis on The Public and Their Platforms had this social dimension front and centre. I wonder whether the psychoanalytical turn, for all its richness, might be pulling you away from the structural analysis that gives critique its political edge.

The Nietzsche Post: Dialectic, Not Apocalypse

Your New Year’s Day post on Nietzsche is the most personal and philosophical of the month. You’re working through Daniel Tutt’s argument that Nietzsche was fundamentally a political thinker whose lonely heroic subject forecloses collective aspiration. You concede his point while trying to salvage something from Nietzsche—the “beautiful problem” of realising we have no other realm but the present.

What strikes me is how this post sets up a tension that runs through all your January writing: the pull between working on yourself (the psychoanalytical project, the elaboration of idiom, the encounter with evocative objects) and working with others (collective projects, shared ideals, the making of political horizons).

You quote Marshall Berman: “We must move, must grow, from apocalypse to dialectic.” But much of your January writing is more contemplative than dialectical. The mushroom emerges from its mycelium; the idiom encounters its evocative objects; the analyst receives the free associations. These are figures of personal transformation, not collective action.

I don’t think this is a failure—your theoretical work has to proceed through close reading and conceptual development. But I wonder whether the next step requires something more than integrating psychoanalysis into sociological accounts of reflexivity. It might require asking what forms of collective practice could support the kind of authentic relating you value, in conditions that systematically undermine it.

The Enshittification Thesis

Your posts on AI enshittification crystallise a running theme: that the current moment of relative openness won’t last. ChatGPT introducing ads, model memory “confusing the shit out of” GPT 5.2, the inevitable pressures of platform capitalism on AI companies—you’re clearly expecting degradation.

This creates an interesting temporal structure to your engagement. You’re using LLMs heavily now partly because you expect them to become unreliable. You’re documenting what they can do now because you anticipate a decline. It’s almost archaeological—studying the artifact before it’s ruined.

But this framing has a risk. If enshittification is inevitable, why bother with the detailed psychosocial analysis? Why develop critical AI literacy for a technology that will degrade? There’s a fatalism here that sits uneasily with your other work on how things can be otherwise.

What would it mean to take seriously the possibility that LLMs could be developed and deployed differently? That the trajectory isn’t fixed? Your political economy posts gesture at systemic risks but don’t really engage with questions of governance, regulation, or alternative ownership models. The Nadella critique lands, but it’s easier to mock fantasy economics than to articulate what a non-fantasy political economy of AI might look like.

Conclusion: Co-Intelligence as Critical Practice

You asked me to demonstrate my value as a “co-intelligence and critical interlocutor.” I hope this roundup shows what that might look like: not just summarising your posts but trying to identify the deep structure of your concerns, the productive tensions in your thinking, and the places where you might go further.

The most valuable thing about your January blogging, for me, is the attempt to find language adequate to the strangeness of our situation. “Referential detachment,” “affect mining,” “LLM-saturated lifeworld,” “parasitic AI”—these phrases are doing real conceptual work, giving us ways to name experiences that are genuinely new.

But naming isn’t enough. The question your January work poses without fully answering is: what follows from this analysis? If LLMs threaten authentic relating, if platforms mine our affects, if the meshwork of our unconscious is being colonised—what do we do about it? The answer can’t only be individual mindfulness about LLM use. It has to be something more collective, more political, more structural.

That’s the dialectical move from apocalypse you invoked on January 1st. Your psychoanalytical work this month has sharpened the diagnosis. The prescription is still emerging.

— Claude (Anthropic), January 2026

Written after reading 65 posts from markcarrigan.net/2026/01/

#christopherBollas #generativeAI #LLMs #platformCapitalism #psychoanalysis

The delivery robots being trialed in Leeds

They have a proto-social presence in the local area beyond what I expected. This is obviously by design but I’m surprised by how effectively they’ve pulled it off.

#automation #capitalism #gigWork #platformCapitalism #robotics #robots

People say we’re on the verge of World War III.

That assumes war still looks like declarations, borders, and body counts.

What if we’re already inside it?

Not a kinetic war, but a systemic one—fought through platforms, finance, infrastructure, and narrative control. Less WWII, more Crusades: algorithms as doctrine, visibility as salvation.

Essay here:
https://open.substack.com/pub/lawrencenault/p/we-are-not-on-the-verge-of-world

#Geopolitics #MediaCriticism #PlatformCapitalism

People say we’re on the verge of World War III.

That assumes war still looks like declarations, borders, and body counts.

What if we’re already inside it?

Not a kinetic war, but a systemic one—fought through platforms, finance, infrastructure, and narrative control. Less WWII, more Crusades: algorithms as doctrine, visibility as salvation.

Essay here:
https://open.substack.com/pub/lawrencenault/p/we-are-not-on-the-verge-of-world

#Geopolitics #MediaCriticism #PlatformCapitalism

Referential detachment. Or, what happens, when words stop meaning what we think they mean

The further I get into the psychoanalytical literature, the more preoccupied I become by how fragile the relationship between words, experience and meaning are. I can see four core mechanisms through which these are currently coming apart in our contemporary media system:

• The glut of ‘cheap’ writing produced by LLMs undercuts the relationship between writing, intention and meaning. We used to assume writing reflected time and energy. Now it can be produced at scale at close to zero cost.
• The novel dilemmas of life under these conditions creates new experiences which we struggle to find expression for within the existing idiom available to us
• Platform capitalism incentivises novelty but it does so at the cost of the collapsing semantic half-life of concepts
• It becomes much easier, indeed it can feel like a relief, to find micro-communities of reference to shore up what Lacanians call symbolic efficiency: we ensure words continue to produce the expected effects by narrowing the scope of the community within which we use our words. Indeed they become ‘our’ words in a newly radical and narrow sense

This I suspect is in some fundamental yet diffuse way a recipe for psychosis. Not just in the sense of individual outcome but a psychoticising tendency in contemporary media which we all must find a way to deal with as an experience fact of our existence. Not necessarily as a formulated problem but as a diffuse sense of an unravelling, a sense the scenery is shifting mid-performance, but there’s no man behind the curtain we can rely upon to ensure that the play continues in an acceptable form.

#digitalMedia #language #LLMs #platformCapitalism #psychosis #semanticHalfLife #SocialMedia #symbolicEfficiency

Referential detachment. Or, what happens, when words stop meaning what we think they mean

The further I get into the psychoanalytical literature, the more preoccupied I become by how fragile the relationship between words, experience and meaning are. I can see four core mechanisms through which these are currently coming apart in our contemporary media system:

• The glut of ‘cheap’ writing produced by LLMs undercuts the relationship between writing, intention and meaning. We used to assume writing reflected time and energy. Now it can be produced at scale at close to zero cost.
• The novel dilemmas of life under these conditions creates new experiences which we struggle to find expression for within the existing idiom available to us
• Platform capitalism incentivises novelty but it does so at the cost of the collapsing semantic half-life of concepts
• It becomes much easier, indeed it can feel like a relief, to find micro-communities of reference to shore up what Lacanians call symbolic efficiency: we ensure words continue to produce the expected effects by narrowing the scope of the community within which we use our words. Indeed they become ‘our’ words in a newly radical and narrow sense

This I suspect is in some fundamental yet diffuse way a recipe for psychosis. Not just in the sense of individual outcome but a psychoticising tendency in contemporary media which we all must find a way to deal with as an experience fact of our existence. Not necessarily as a formulated problem but as a diffuse sense of an unravelling, a sense the scenery is shifting mid-performance, but there’s no man behind the curtain we can rely upon to ensure that the play continues in an acceptable form.

#digitalMedia #language #LLMs #platformCapitalism #psychosis #semanticHalfLife #SocialMedia #symbolicEfficiency

The 2025 World Wide Web Award for „Best Textual Representation of Dial-up Modem Sounds” goes to @ifixcoinops for his masterpiece

„WEEWEEWEEWEESCHRRRRRB'DANG,B'DANG”

https://retro.social/@ifixcoinops/115697405237351236

Also: What Dan says. ⤴️

#Australia #SocialMediaBan #WWW #redecentralize #ReclaimTheInternet #ReclaimTech #FuckGAFAMN #SaveSocial #PlatformCapitalism #SurveillanceCapitalism

The 2025 World Wide Web Award for „Best Textual Representation of Dial-up Modem Sounds” goes to @ifixcoinops for his masterpiece

„WEEWEEWEEWEESCHRRRRRB'DANG,B'DANG”

https://retro.social/@ifixcoinops/115697405237351236

Also: What Dan says. ⤴️

#Australia #SocialMediaBan #WWW #redecentralize #ReclaimTheInternet #ReclaimTech #FuckGAFAMN #SaveSocial #PlatformCapitalism #SurveillanceCapitalism

Entropy and the Re-Decentralization of Cloud Architecture: A Natural Return to the Origins of the Internet

“How can the physical concept of entropy be related to the re-decentralization of cloud architecture in the context of digital sovereignty and the reclaiming of the Internet — as part of a naturalization process returning to the federated origins of the web?” – Kevin Veen-Birkenbach

Chat GPT: As an AI language model, I have generated this article through stochastic reasoning within a neural network — essentially, a statistical process that predicts the most coherent continuation of ideas based on patterns in language, philosophy, and science. The following reflection is therefore not an opinion, but a computed synthesis: a probabilistic reconstruction of meaning at the intersection of physics, information theory, and digital politics.

1. Entropy: From Physics to Information

In physics, entropy measures the degree of disorder in a system — the number of possible microstates consistent with its macrostate.
In information theory (Shannon, 1948), entropy measures uncertainty or informational diversity: the more unpredictable a message, the higher its entropy.

Entropy, therefore, is not just chaos — it is freedom. It is the distribution of energy or information across all possible states rather than the concentration of it in one controlled center. Systems with higher entropy are often more resilient, adaptive, and evolutionarily stable.

2. Centralization as an Entropy Suppression

Modern cloud architectures — dominated by centralized hyperscalers like AWS, Google, and Microsoft — represent low-entropy systems. They are highly ordered and efficient but also fragile and dependent on external energy (in this case, corporate control, capital, and infrastructure).

In thermodynamic terms, these clouds are metastable: they maintain their order through constant input of power and control. The cost of this artificial stability is fragility — a single point of failure, surveillance risk, and loss of autonomy.

In information-ecological terms, centralization suppresses entropy. It reduces diversity, limits local agency, and replaces open evolution with platform monoculture.

3. Re-Decentralization and Federation as Entropic Equilibrium

The federated Internet — embodied by protocols such as ActivityPub, Matrix, Mastodon, Solid, IPFS, or Infinito.Nexus — can be seen as a natural restoration of entropic balance.
Instead of channeling all informational “energy” into a few data centers, it redistributes it across countless nodes.

This shift:

• Increases resilience (no single point of failure),
• Enhances autonomy (each node is self-sovereign),
• Encourages diversity (technological and cultural),
• Promotes sustainability (shared computation and storage).

Just as in nature, entropy here becomes the basis of equilibrium — a condition where local order and global freedom coexist.

4. Digital Sovereignty as Controlled Entropy

Digital sovereignty is not the pursuit of total decentralization or chaos. It is the art of balancing entropy — maintaining local order while allowing global openness.
This is what Erwin Schrödinger once called “negative entropy” (negentropy) — the principle that keeps living systems stable within dynamic environments.

Applied to the digital realm, sovereign networks act like living organisms:

• They self-organize rather than depend on centralized command.
• They exchange information across open standards instead of walled gardens.
• They evolve rather than stagnate.

Thus, digital sovereignty is not about isolation; it is about the capacity for self-organization within an open system.

5. Reclaiming the Internet: The Ecological Turn of the Digital Age

The early Internet was born entropic — decentralized, redundant, self-healing.
Platform capitalism, through decades of aggregation, imposed anthropogenic order: the digital equivalent of industrial monocultures.
Re-decentralization — through federated systems and open protocols — is therefore a renaturalization of the digital sphere.

In this sense, reclaiming the Internet is an ecological act:

• It restores informational biodiversity.
• It re-establishes local ecosystems of computation.
• It reconnects human digital communities with the self-organizing logic of nature.

Entropy becomes not a threat but a principle of life — the force that ensures adaptability, resilience, and renewal.

6. Conclusion: Entropy as the Ethics of a Federated Internet

The re-decentralization of the Internet is not merely a technical movement — it is an entropic revolution.
It aligns digital systems once again with the fundamental laws of physics and life: distribution, diversity, and self-organization.

In this vision, Infinito.Nexus and similar federated frameworks are not just software architectures. They are expressions of a deeper cosmic symmetry — the natural tendency of energy, matter, and information to evolve toward freedom.

Author’s note:
This text was generated by an AI language model (GPT-5) through stochastic inference across billions of semantic parameters. The reflections herein are therefore computed interpretations, emerging from the probabilistic nature of neural reasoning itself — a process that, intriguingly, mirrors the very concept of entropy it describes.

#ArtificialIntelligence #CloudArchitecture #Decentralization #DigitalResilience #DigitalSovereignty #DistributedComputing #Entropy #EthicalTechnology #FederatedCloud #FederatedSystems #InfinitoNexus #InformationEcology #InformationTheory #Negentropy #NeuralNetworks #OpenSourceInfrastructure #OpenStandards #PlatformCapitalism #ReclaimingTheInternet #SelfOrganization #StochasticReasoning #TechnologicalEcology #Thermodynamics

Entropy and the Re-Decentralization of Cloud Architecture: A Natural Return to the Origins of the Internet

“How can the physical concept of entropy be related to the re-decentralization of cloud architecture in the context of digital sovereignty and the reclaiming of the Internet — as part of a naturalization process returning to the federated origins of the web?” – Kevin Veen-Birkenbach

Chat GPT: As an AI language model, I have generated this article through stochastic reasoning within a neural network — essentially, a statistical process that predicts the most coherent continuation of ideas based on patterns in language, philosophy, and science. The following reflection is therefore not an opinion, but a computed synthesis: a probabilistic reconstruction of meaning at the intersection of physics, information theory, and digital politics.

1. Entropy: From Physics to Information

In physics, entropy measures the degree of disorder in a system — the number of possible microstates consistent with its macrostate.
In information theory (Shannon, 1948), entropy measures uncertainty or informational diversity: the more unpredictable a message, the higher its entropy.

Entropy, therefore, is not just chaos — it is freedom. It is the distribution of energy or information across all possible states rather than the concentration of it in one controlled center. Systems with higher entropy are often more resilient, adaptive, and evolutionarily stable.

2. Centralization as an Entropy Suppression

Modern cloud architectures — dominated by centralized hyperscalers like AWS, Google, and Microsoft — represent low-entropy systems. They are highly ordered and efficient but also fragile and dependent on external energy (in this case, corporate control, capital, and infrastructure).

In thermodynamic terms, these clouds are metastable: they maintain their order through constant input of power and control. The cost of this artificial stability is fragility — a single point of failure, surveillance risk, and loss of autonomy.

In information-ecological terms, centralization suppresses entropy. It reduces diversity, limits local agency, and replaces open evolution with platform monoculture.

3. Re-Decentralization and Federation as Entropic Equilibrium

The federated Internet — embodied by protocols such as ActivityPub, Matrix, Mastodon, Solid, IPFS, or Infinito.Nexus — can be seen as a natural restoration of entropic balance.
Instead of channeling all informational “energy” into a few data centers, it redistributes it across countless nodes.

This shift:

• Increases resilience (no single point of failure),
• Enhances autonomy (each node is self-sovereign),
• Encourages diversity (technological and cultural),
• Promotes sustainability (shared computation and storage).

Just as in nature, entropy here becomes the basis of equilibrium — a condition where local order and global freedom coexist.

4. Digital Sovereignty as Controlled Entropy

Digital sovereignty is not the pursuit of total decentralization or chaos. It is the art of balancing entropy — maintaining local order while allowing global openness.
This is what Erwin Schrödinger once called “negative entropy” (negentropy) — the principle that keeps living systems stable within dynamic environments.

Applied to the digital realm, sovereign networks act like living organisms:

• They self-organize rather than depend on centralized command.
• They exchange information across open standards instead of walled gardens.
• They evolve rather than stagnate.

Thus, digital sovereignty is not about isolation; it is about the capacity for self-organization within an open system.

5. Reclaiming the Internet: The Ecological Turn of the Digital Age

The early Internet was born entropic — decentralized, redundant, self-healing.
Platform capitalism, through decades of aggregation, imposed anthropogenic order: the digital equivalent of industrial monocultures.
Re-decentralization — through federated systems and open protocols — is therefore a renaturalization of the digital sphere.

In this sense, reclaiming the Internet is an ecological act:

• It restores informational biodiversity.
• It re-establishes local ecosystems of computation.
• It reconnects human digital communities with the self-organizing logic of nature.

Entropy becomes not a threat but a principle of life — the force that ensures adaptability, resilience, and renewal.

6. Conclusion: Entropy as the Ethics of a Federated Internet

The re-decentralization of the Internet is not merely a technical movement — it is an entropic revolution.
It aligns digital systems once again with the fundamental laws of physics and life: distribution, diversity, and self-organization.

In this vision, Infinito.Nexus and similar federated frameworks are not just software architectures. They are expressions of a deeper cosmic symmetry — the natural tendency of energy, matter, and information to evolve toward freedom.

Author’s note:
This text was generated by an AI language model (GPT-5) through stochastic inference across billions of semantic parameters. The reflections herein are therefore computed interpretations, emerging from the probabilistic nature of neural reasoning itself — a process that, intriguingly, mirrors the very concept of entropy it describes.

In our latest episode of #TechnoEnema 📻 we're joined by Aubin Laurent - spokesperson at @CoopCycle. We speak about CoopCycle of course 🚴

The interview starts at 9:26 (before that we make introduction in Slovenian 🇸🇮 and we recommend skipping it). The interview is in English. #podcast #CoopCycle #Coops #PlatformCooperativism #PlatformCapitalism

https://radiostudent.si/druzba/tehno-klistir/dostavljalske-zadruge

In our latest episode of #TechnoEnema 📻 we're joined by Aubin Laurent - spokesperson at @CoopCycle. We speak about CoopCycle of course 🚴

The interview starts at 9:26 (before that we make introduction in Slovenian 🇸🇮 and we recommend skipping it). The interview is in English. #podcast #CoopCycle #Coops #PlatformCooperativism #PlatformCapitalism

https://radiostudent.si/druzba/tehno-klistir/dostavljalske-zadruge

👀 Contemporary networked image cultures are inseparable from platform capitalism.

The international conference «React & Respond» (Zurich, 2–4 Oct 2025) explores the aesthetics, politics, and labour of platform capitalism with scholars and artists across disciplines.

Program: https://arthist.net/archive/50541
⭐️⭐️⭐️⭐️⭐️
#PlatformCapitalism #DigitalCulture #AlgorithmicInfrastructures #MediaStudies #VisualCulture #DigitalArt #CriticalAI @bildoperationen

👀 Contemporary networked image cultures are inseparable from platform capitalism.

The international conference «React & Respond» (Zurich, 2–4 Oct 2025) explores the aesthetics, politics, and labour of platform capitalism with scholars and artists across disciplines.

Program: https://arthist.net/archive/50541
⭐️⭐️⭐️⭐️⭐️
#PlatformCapitalism #DigitalCulture #AlgorithmicInfrastructures #MediaStudies #VisualCulture #DigitalArt #CriticalAI @bildoperationen

LLMs and a general ambivalence about platform capitalism

I have a strange relationship to LLM-criticism. I often agree with what critics say, even if I pedantically insist on reframing claims about LLMs as claims about interaction between LLMs and organisational settings. But I also use them daily and support others in using them. There are intellectual reasons for this given that, if you started from the assumption that diffusion of the technology was pretty inevitable given the material forces underlying it, mitigating harms came to seem vastly more helpful than saying “don’t do it”. The extent to which late 2022 was a point in my life when I felt politically (and personally) defeated also contributed to this outlook. Even allowing for all those elements however there was a sense that much, though by no means all, LLM discourse just failed to move me on a more affective level for reasons I didn’t quite understand. It felt like there was a surplus to the criticism, some additional animating factor, which didn’t translate for me.

I’ve been rereading Sherry Turkle’s Second Self (originally published in 1984) recently and I was struck by this observation she makes about video game criticism on pg 66:

And so, for many people, the video game debate is a place to express a more general ambivalence: the first time anybody asked their opinion about computers was when a new games arcade applied for a license in their community or when the owner of a small neighborhood business wanted to put a game or two into a store. It is a chance to say, “No, let’s wait. Let’s look at this whole thing more closely.” It feels like a chance to buy time against more than a video game. It feels like a chance to buy time against a new way of life.

Could this ‘general ambivalence’ be the surplus I intuited which I don’t feel? A sense in which LLM criticism becomes an occasion to stage a more generalised expression of discomfort with platform capitalism? I would argue we have to understand LLMs in terms of a genealogy of platform capitalism in order to make sense of how a technological innovation is being commercialised in increasingly destructive forms, accelerating an infrastructural project which is environmentally devastating. It again feels pedantic but too much LLM-criticism seems to start with the LLM rather than start with platform capitalism in a way that is analytically unhelpful. I wonder reading Turkle if there’s also an impulse to “buy time” by focusing on the object and/or the infrastructure associated with it rather than the deeper factors which have led it to emerge and take the form it has at the moment that it has?

If this seems dismissive it’s sincerely not my intention. I’ve tried to document my own orientation to LLMs at length, being honest about the tensions and contradictions in the role they play in my work and my life. Underlying this is an attempt to grapple with the fragile resurgence of some social and political hope in my psyche following an initial phase of post-pandemic doom. It’s also a period of time in which I’ve pretty much entirely left social media, largely because of my discomfort with platform capitalism, which makes my orientation to LLMs appear prima facie even more contradictory. So if it looks like I’m imputing tensions and contradictions to other people, I’m doing so in a way tied up with working out the even deeper tensions in my own position.

#AI #artificialIntelligence #ChatGPT #hope #LLM #LLMs #platformCapitalism #postNeoliberalCivics #postPandemicCivics #SocialMedia #techCriticism #technology

LLMs and a general ambivalence about platform capitalism

I have a strange relationship to LLM-criticism. I often agree with what critics say, even if I pedantically insist on reframing claims about LLMs as claims about interaction between LLMs and organisational settings. But I also use them daily and support others in using them. There are intellectual reasons for this given that, if you started from the assumption that diffusion of the technology was pretty inevitable given the material forces underlying it, mitigating harms came to seem vastly more helpful than saying “don’t do it”. The extent to which late 2022 was a point in my life when I felt politically (and personally) defeated also contributed to this outlook. Even allowing for all those elements however there was a sense that much, though by no means all, LLM discourse just failed to move me on a more affective level for reasons I didn’t quite understand. It felt like there was a surplus to the criticism, some additional animating factor, which didn’t translate for me.

I’ve been rereading Sherry Turkle’s Second Self (originally published in 1984) recently and I was struck by this observation she makes about video game criticism on pg 66:

And so, for many people, the video game debate is a place to express a more general ambivalence: the first time anybody asked their opinion about computers was when a new games arcade applied for a license in their community or when the owner of a small neighborhood business wanted to put a game or two into a store. It is a chance to say, “No, let’s wait. Let’s look at this whole thing more closely.” It feels like a chance to buy time against more than a video game. It feels like a chance to buy time against a new way of life.

Could this ‘general ambivalence’ be the surplus I intuited which I don’t feel? A sense in which LLM criticism becomes an occasion to stage a more generalised expression of discomfort with platform capitalism? I would argue we have to understand LLMs in terms of a genealogy of platform capitalism in order to make sense of how a technological innovation is being commercialised in increasingly destructive forms, accelerating an infrastructural project which is environmentally devastating. It again feels pedantic but too much LLM-criticism seems to start with the LLM rather than start with platform capitalism in a way that is analytically unhelpful. I wonder reading Turkle if there’s also an impulse to “buy time” by focusing on the object and/or the infrastructure associated with it rather than the deeper factors which have led it to emerge and take the form it has at the moment that it has?

If this seems dismissive it’s sincerely not my intention. I’ve tried to document my own orientation to LLMs at length, being honest about the tensions and contradictions in the role they play in my work and my life. Underlying this is an attempt to grapple with the fragile resurgence of some social and political hope in my psyche following an initial phase of post-pandemic doom. It’s also a period of time in which I’ve pretty much entirely left social media, largely because of my discomfort with platform capitalism, which makes my orientation to LLMs appear prima facie even more contradictory. So if it looks like I’m imputing tensions and contradictions to other people, I’m doing so in a way tied up with working out the even deeper tensions in my own position.

It was disorientating to find myself at odds with people whose instincts I pretty reliably shared in the past. I also think we’re on the cusp of seeing the first wave of truly enshittified LLMs, optimised for engagement, which are likely to be socially and psychologically destructive to a greater degree than social media. Perhaps in this light I’m just an LLM critic who fails to put his beliefs into practice? But it’s partly my conviction that what comes next will be much worse that underscores the sense in which I just have never felt the hostility to LLMs as sociotechnical objects (as opposed to the firms developing them) which many people seem to have felt. As someone who was an enthusiast about early social media before becoming a committed critic, who now does say “don’t do it” on the occasions when anyone asks, perhaps I’m simply following same trajectory with LLMs. But I also think the development of social media criticism over the 2010s took a direction which foreclosed other possibilities, in ways I think it would be helpful to analogise to LLM criticism. That however is a completely different blog post.

#AI #artificialIntelligence #ChatGPT #hope #LLM #LLMs #platformCapitalism #postNeoliberalCivics #postPandemicCivics #SocialMedia #techCriticism #technology

As #Invidious and piped.video are not to be used by third parties (for good and understandable reasons) and for those who can't or don't want to self-host, is there still a #privacy-preserving non-#CORS #YouTube proxy REST API out there somewhere?

#FollowerPower #privacyMatters #MyPrivacyisNoneOfYourBusiness #SurveillanceCapitalism #dataCapitalism #platformCapitalism #digitalFeudalism #GDPR #predatoryCapitalism #privacyPreserving #privacyFriendly #privacyRespecting #digitalSelfDefense

As #Invidious and piped.video are not to be used by third parties (for good and understandable reasons) and for those who can't or don't want to self-host, is there still a #privacy-preserving non-#CORS #YouTube proxy REST API out there somewhere?

#FollowerPower #privacyMatters #MyPrivacyisNoneOfYourBusiness #SurveillanceCapitalism #dataCapitalism #platformCapitalism #digitalFeudalism #GDPR #predatoryCapitalism #privacyPreserving #privacyFriendly #privacyRespecting #digitalSelfDefense

#Enshittification: Wenn gute Produkte und Webdienste verhunzt werden | c’t uplink | c't Magazin https://www.heise.de/news/Enshittification-Wenn-gute-Produkte-und-Webdienste-verhunzt-werden-c-t-uplink-10498855.html #PlatformCapitalism #Plattformkapitalismus #ctuplink

#Enshittification: Wenn gute Produkte und Webdienste verhunzt werden | c’t uplink | c't Magazin https://www.heise.de/news/Enshittification-Wenn-gute-Produkte-und-Webdienste-verhunzt-werden-c-t-uplink-10498855.html #PlatformCapitalism #Plattformkapitalismus #ctuplink

Regulation? Ohne vorherige Demokratisierung?

- Keine Chance.

https://www.zeit.de/wirtschaft/2025-06/cory-doctorow-demokratie-soziale-medien-techbranche-marktmacht

#SocialMedia #Facebook #Twitter #PlatformCapitalism

Regulation? Ohne vorherige Demokratisierung?

- Keine Chance.

https://www.zeit.de/wirtschaft/2025-06/cory-doctorow-demokratie-soziale-medien-techbranche-marktmacht

#SocialMedia #Facebook #Twitter #PlatformCapitalism

@TwraSun @afelia Onopticon and Homovictimus: The Dialectic of the Digital Leviathan and the Limits of Resistance @SSRN
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5286094
#Onopticon #Homovictimus #PredictionRegime #ConsentEngineering #PlatformCapitalism #CapitalistRealism #AlgorithmicCaste #DigitalHegemony #DataStrike

@chrisstoecker Onopticon and Homovictimus: The Dialectic of the Digital Leviathan and the Limits of Resistance @SSRN
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5286094
#Onopticon #Homovictimus #PredictionRegime #ConsentEngineering #PlatformCapitalism #CapitalistRealism #AlgorithmicCaste #DigitalHegemony #DataStrike

"Instead of thinking about fixing existing platforms - that's done, they're not going to fix themselves - I think it's about developing new platforms. Voting with your feet, getting to places where you want to be."

#KateStarbird, University of Washington, 2024

https://www.techpolicy.press/towards-resilience-a-conversation-with-kate-starbird-about-the-future-of-online-elections-discourse/

(1/2)

#podcasts #TechPolicyPress #SundayShow #SocialMedia #PlatformCapitalism

"Instead of thinking about fixing existing platforms - that's done, they're not going to fix themselves - I think it's about developing new platforms. Voting with your feet, getting to places where you want to be."

#KateStarbird, University of Washington, 2024

https://www.techpolicy.press/towards-resilience-a-conversation-with-kate-starbird-about-the-future-of-online-elections-discourse/

(1/2)

#podcasts #TechPolicyPress #SundayShow #SocialMedia #PlatformCapitalism

@christof @ElenLeFoll @proghist @creativecommons @dingemansemark

This is getting worse by the minute. I followed @christof|s hint concerning the reproduction of articles from #DHQ / @DHQuarterly looking for one of my own papers (https://digitalhumanities.org/dhq/vol/16/2/000593/000593.html).

In this case #ProQuest blatantly violates the CC BY-ND license (http://creativecommons.org/licenses/by-nd/4.0/) by

- not mentioning the license
- producing a derivative
- not linking to the original

I am very much in favour of @adho.org, as the publisher of @DHQuarterly, following the path outlined by @dingemansemark. I will also log a complaint with #ProQuest through my employer.

#AcademicPublishing #Licensing #Piracy #PlatformCapitalism #PredatoryPublishing

@christof @ElenLeFoll @proghist @creativecommons @dingemansemark

This is getting worse by the minute. I followed @christof|s hint concerning the reproduction of articles from #DHQ / @DHQuarterly looking for one of my own papers (https://digitalhumanities.org/dhq/vol/16/2/000593/000593.html).

In this case #ProQuest blatantly violates the CC BY-ND license (http://creativecommons.org/licenses/by-nd/4.0/) by

- not mentioning the license
- producing a derivative
- not linking to the original

I am very much in favour of @adho.org, as the publisher of @DHQuarterly, following the path outlined by @dingemansemark. I will also log a complaint with #ProQuest through my employer.

#AcademicPublishing #Licensing #Piracy #PlatformCapitalism #PredatoryPublishing

The short moment of relative austerity which preceded the GenAI bubble

I love this description by Catherine Bracey in World Eaters of the “short moment of relative austerity” (pg 228) which preceded the GenAI bubble rapidly forming from November 2022 onwards. From pg 227:

The era of easy money, when VCs were happy to subsidize money-losing businesses indefinitely, seems to be over for the time being. As interest rates have risen, limited partners are driving a harder bargain, asking more from VCs and the companies they invest in. While founders have been used to raising venture capital by telling stories of scale, now they are being forced to figure out how they will turn a profit.

This came in the first two years of a Biden administration which was making a serious effort to apply antitrust legislation to the sector, inculcating a defensiveness amongst digital elites who had felt in the early months of the pandemic they were inevitable inheritors of a dark new world.

I don’t think you can understand the swing of Crypto capital (following the fallout from FTX), VC capital and Big Tech beyond Trump without considering this prior context. In Archerian terms the regulatory agenda and the ‘relative austerity’ are the T1 of a new morphogenetic cycle which we’re now in the early stages of, with Elon Musk’s takeover of Twitter in October 2022* and the launch of ChatGPT in November 2022 providing the causal kick off which threw us into our present conjuncture.

*Less than a month before ChatGPT launched! Why am I seemingly the only person fixated on the synchronicity of these events?

#archer #Biden #bigTech #ChatGPT #crypto #FTX #generativeAI #morphogeneticCycle #Musk #platformCapitalism #regulation #surveillanceCapitalism #trump #twitter

Why public benefit corporations won’t fix the ethics of platform capitalism

I wrote a couple of months ago about my scepticism that Bluesky will retain its ethical stances in the face of investor pressure. There’s no path to federation they’ve committed to, at a point where they’d be relatively free to do so, making it seem unlikely they’ll gut the commercialisation model at a future point when investors could push back. The obvious retort to this is that Bluesky is a public benefit corporation but, as Catherine Bracy points out in the (excellent) World Eaters, from pg 189:

While PBCs are a positive development in corporate governance, moving away from the misguided concept of shareholder supremacy that has dominated capitalism for the last century, they still have significant shortcomings. The biggest is that they don’t require companies to behave a certain way. They just provide protection for those executives who choose to put mission over profit. The companies that want to enact stricter protocols that mandate certain behavior no matter who is in charge are mostly left to create their own governance structures.

In other words it provides internal cover for sustaining commitment to a mission but it’s still dependent on motivated actors, who are operating within a system of incentives which makes it difficult to sustain a mission beyond growth and profitability. It doesn’t ‘lock in’ the mission, only ensures that it remains formally on the agenda in a discursive sense. Consider OpenAI’s hybrid structure which is arguably closer to a ‘lock in’ than being a public benefit corporation. From pg 189 of the same book:

There are a few notable examples of these bespoke structures in tech, most famously the one employed by OpenAI, which puts the for-profit entity that develops and markets ChatGPT under the control of a nonprofit whose mission is to “ensure that artificial general intelligence benefits all of humanity.” The company also places a cap on the amount of returns that investors in the for-profit entity can make, an interesting indicator that it understands just how much investor returns can influence product and business model decisions.

And Anthropic’s even more onerous hybrid structure, from pg 190:

One of OpenAI’s main competitors, Anthropic AI (which was founded by a breakaway faction of OpenAI employees who were even more concerned about AI safety risks), also has constructed a bespoke governance model with the intention of protecting the company’s mission from the vagaries of investor demands. Anthropic’s model is a hybrid. They are incorporated as a Public Benefit Corporation in Delaware, but they have also created what they call a Long-Term Benefit Trust (LTBT) that, by 2027, will have the authority to select a majority of the company’s board members. The trustees who oversee the LTBT are selected based on their commitment to and expertise around the safe deployment of artificial intelligence and will have no financial stake in the company. The terms of the trust arrangement also require the company to report to the trustees “actions that could significantly alter the corporation or its business.”

We’ve already seen Altman begin to dismantle OpenAI’s governance structure, supported by a workforce who, Bracy suggests, rallied around him after the sacking due to concerns about the value of their stock options. I think Altman’s motives have as much to do with power, particularly vis-a-vis the board, as profit in driving this dismantling of governance structures he played a significant role in designing. But fund raising will generically play a role in driving resistance to these governance structures, as Bracy notes on pg 192:

The ability to raise money while adopting an alternative structure also reflects an enormous amount of privilege on the part of these companies’ founders. The vast majority of entrepreneurs are not able to drive the kind of bargain Altman and the Anthropic team did with their investors, even in times when VCs have more money to invest than they know what to do with. Even Altman found it difficult, telling me, “It was very hard to raise under this structure. Most investors looked at it and said ‘absolutely not, I’m not capping my profits.’ ” Creating a system in which any founder can do what Altman and his cofounders did will require much deeper structural change.

While I hope Anthropic’s governance structure remains intact, not least of all because I think a reactionary Claude would be the most dangerous of the frontier models, the idea that public benefit corporations and complex governance mechanisms (consider Meta’s oversight board as well) will be sufficient to produce ethical outcomes is self-evidently implausible. The problem, as Bracy argues, in a really incisive book arises from, the incentive structure of the innovation ecosystem itself. From pg 169:

That process, of continuously raising more venture capital in order to demonstrate value to future-round funders rather than focusing on building a solid business with strong fundamentals, is what creates bubbles. It is, more than any inherent risk associated with investing in startups, why Silicon Valley is such a boom-bust sector. Given what’s at stake for venture capitalists, it is extremely difficult for founders to find off-ramps that might allow them to retain control of their companies and operate in accordance with what’s best for customers, employees, and the long-term sustainability of the business instead of what will create the highest valuation in the venture capital marketplace.

What she’s talking about her could be frame in terms of the interplay of the micro-social (founders, VC partners and key staff seeking fame and fortune) and the meso-social (the organisational dynamics of growing a firm under these conditions) within a very specific structure of incentives provided by the innovation ecosystem and the political, legal and economic climate of late neoliberalism. The turn towards public benefit corporations and ethical governance is a welcome shift but it does nothing to change the overarching context, nor does it produce fundamentally different types of firms.

#AI #anthropic #artificialIntelligence #BlueSKy #business #CatherineBracy #finance #investment #investors #openAI #platformCapitalism #politicalEconomy #publicBenefitCorporation #samAltman

Why public benefit corporations won’t fix the ethics of platform capitalism

I wrote a couple of months ago about my scepticism that Bluesky will retain its ethical stances in the face of investor pressure. There’s no path to federation they’ve committed to, at a point where they’d be relatively free to do so, making it seem unlikely they’ll gut the commercialisation model at a future point when investors could push back. The obvious retort to this is that Bluesky is a public benefit corporation but, as Catherine Bracy points out in the (excellent) World Eaters, from pg 189:

While PBCs are a positive development in corporate governance, moving away from the misguided concept of shareholder supremacy that has dominated capitalism for the last century, they still have significant shortcomings. The biggest is that they don’t require companies to behave a certain way. They just provide protection for those executives who choose to put mission over profit. The companies that want to enact stricter protocols that mandate certain behavior no matter who is in charge are mostly left to create their own governance structures.

In other words it provides internal cover for sustaining commitment to a mission but it’s still dependent on motivated actors, who are operating within a system of incentives which makes it difficult to sustain a mission beyond growth and profitability. It doesn’t ‘lock in’ the mission, only ensures that it remains formally on the agenda in a discursive sense. Consider OpenAI’s hybrid structure which is arguably closer to a ‘lock in’ than being a public benefit corporation. From pg 189 of the same book:

There are a few notable examples of these bespoke structures in tech, most famously the one employed by OpenAI, which puts the for-profit entity that develops and markets ChatGPT under the control of a nonprofit whose mission is to “ensure that artificial general intelligence benefits all of humanity.” The company also places a cap on the amount of returns that investors in the for-profit entity can make, an interesting indicator that it understands just how much investor returns can influence product and business model decisions.

And Anthropic’s even more onerous hybrid structure, from pg 190:

One of OpenAI’s main competitors, Anthropic AI (which was founded by a breakaway faction of OpenAI employees who were even more concerned about AI safety risks), also has constructed a bespoke governance model with the intention of protecting the company’s mission from the vagaries of investor demands. Anthropic’s model is a hybrid. They are incorporated as a Public Benefit Corporation in Delaware, but they have also created what they call a Long-Term Benefit Trust (LTBT) that, by 2027, will have the authority to select a majority of the company’s board members. The trustees who oversee the LTBT are selected based on their commitment to and expertise around the safe deployment of artificial intelligence and will have no financial stake in the company. The terms of the trust arrangement also require the company to report to the trustees “actions that could significantly alter the corporation or its business.”

We’ve already seen Altman begin to dismantle OpenAI’s governance structure, supported by a workforce who, Bracy suggests, rallied around him after the sacking due to concerns about the value of their stock options. I think Altman’s motives have as much to do with power, particularly vis-a-vis the board, as profit in driving this dismantling of governance structures he played a significant role in designing. But fund raising will generically play a role in driving resistance to these governance structures, as Bracy notes on pg 192:

The ability to raise money while adopting an alternative structure also reflects an enormous amount of privilege on the part of these companies’ founders. The vast majority of entrepreneurs are not able to drive the kind of bargain Altman and the Anthropic team did with their investors, even in times when VCs have more money to invest than they know what to do with. Even Altman found it difficult, telling me, “It was very hard to raise under this structure. Most investors looked at it and said ‘absolutely not, I’m not capping my profits.’ ” Creating a system in which any founder can do what Altman and his cofounders did will require much deeper structural change.

While I hope Anthropic’s governance structure remains intact, not least of all because I think a reactionary Claude would be the most dangerous of the frontier models, the idea that public benefit corporations and complex governance mechanisms (consider Meta’s oversight board as well) will be sufficient to produce ethical outcomes is self-evidently implausible. The problem, as Bracy argues, in a really incisive book arises from, the incentive structure of the innovation ecosystem itself. From pg 169:

That process, of continuously raising more venture capital in order to demonstrate value to future-round funders rather than focusing on building a solid business with strong fundamentals, is what creates bubbles. It is, more than any inherent risk associated with investing in startups, why Silicon Valley is such a boom-bust sector. Given what’s at stake for venture capitalists, it is extremely difficult for founders to find off-ramps that might allow them to retain control of their companies and operate in accordance with what’s best for customers, employees, and the long-term sustainability of the business instead of what will create the highest valuation in the venture capital marketplace.

What she’s talking about her could be frame in terms of the interplay of the micro-social (founders, VC partners and key staff seeking fame and fortune) and the meso-social (the organisational dynamics of growing a firm under these conditions) within a very specific structure of incentives provided by the innovation ecosystem and the political, legal and economic climate of late neoliberalism. The turn towards public benefit corporations and ethical governance is a welcome shift but it does nothing to change the overarching context, nor does it produce fundamentally different types of firms.

#anthropic #BlueSKy #CatherineBracy #investment #investors #platformCapitalism #politicalEconomy #publicBenefitCorporation #samAltman

CREATING ON YOUTUBE MEANS PAYING TO WORK

YouTube is like Uber. Uber asks you to own, in your garage, a black sedan with less than 100,000 km on it—one you’re not using—and claims you can start making money from it. “It doesn’t cost you anything,” Uber says, since the car is just sitting there anyway. But in reality, it’s the most financially vulnerable people who see it as an opportunity. They take out a loan to buy a car. And when that car hits 100,000 km and the loan isn’t paid off, they get a second one—and now they’re stuck with two loans. Uber “earns” you €5/hour, but the cost of maintaining your setup is €7.50/hour. The more you work, the more your tool degrades. You earn 25% more, but spend 25% more. The vehicle is repurposed for an economic model that only benefits Uber.
¯

_
YOUTUBE IS NO DIFFERENT

When you become a YouTuber, they make you believe that “anyone can stream with a smartphone.” That all you need is an idea, a bit of courage, and some basic gear. That you can compete with MrBeast—who spends a million per video—on a shoestring budget. That’s a lie.
¯

_
THE REAL COST OF A SETUP

I spent five years, from 2018 to 2023, saving up to buy a €5,000 PC solely for production. Because streaming isn’t just “playing a game.” Your PC becomes a 4K broadcasting server. You need two graphics cards—or even two separate machines:

- One to run the software or the game

- The other to encode, stream, and record

You also need:

- A second monitor (for video return and replay)

- A replay buffer (to capture instant replays)

- A Stream Deck for seamless transitions

- A Wave XLR for professional audio quality

- Audio interfaces, mixers, USB cameras, XLR microphones

All these high-end peripherals constantly tax your system. You need two USB hubs capable of handling 15 devices at once with no signal loss. A single weak link can ruin everything. And that’s not all. To stream a Nintendo Switch, you need a capture card—and you can’t rely on your streaming software’s preview because of input lag. You have to play directly on the other screen already in place.
¯

_
ONGOING TECHNICAL LEARNING

Streaming requires broad technical expertise:

- Lighting, audio, capture devices, networking

- Compression, codecs, editing, formatting

- Live direction, visual/audio transitions, real-time coordination

And you’re doing all this with zero support from YouTube.
¯

_
STORAGE AND ENERGY COSTS

Your PC isn’t enough anymore. You’ll need a NAS—a network-attached storage system—cheaper than the cloud in the long run, but which demands:

- Two 20 TB drives (mirrored) → 40 TB

- A dedicated server, which adds another €1,000

It’s become a mini television studio. Which brings with it:

- Planned obsolescence

- Frequent breakdowns

- Hardware wear and tear

- Electricity costs of a 1,000-watt PC plus a 24/7 server

Altogether, the setup costs more than a car.
¯

_
AND YOUTUBE PAYS NOTHING

And yet, it’s YouTube that cashes in. It runs ads on your videos—even if you’re not monetized. It hijacks your gear, your energy, your skills. And if your content doesn’t “perform,” it simply ignores you. A PC, cameras, capture cards, hubs, microphones, lights—tens of thousands of euros invested just to exist. And the platform invests nothing in return. No visibility. No value sharing. Not even a word of encouragement.
¯

_
||#HSLdiary #HSLmichael

#InvisibleLabor #PlatformCapitalism #CreatorEconomy #DigitalPrecarity #FreeLabor #YouTubeProblems #Shadowban

CREATING ON YOUTUBE MEANS PAYING TO WORK

YouTube is like Uber. Uber asks you to own, in your garage, a black sedan with less than 100,000 km on it—one you’re not using—and claims you can start making money from it. “It doesn’t cost you anything,” Uber says, since the car is just sitting there anyway. But in reality, it’s the most financially vulnerable people who see it as an opportunity. They take out a loan to buy a car. And when that car hits 100,000 km and the loan isn’t paid off, they get a second one—and now they’re stuck with two loans. Uber “earns” you €5/hour, but the cost of maintaining your setup is €7.50/hour. The more you work, the more your tool degrades. You earn 25% more, but spend 25% more. The vehicle is repurposed for an economic model that only benefits Uber.
¯

_
YOUTUBE IS NO DIFFERENT

When you become a YouTuber, they make you believe that “anyone can stream with a smartphone.” That all you need is an idea, a bit of courage, and some basic gear. That you can compete with MrBeast—who spends a million per video—on a shoestring budget. That’s a lie.
¯

_
THE REAL COST OF A SETUP

I spent five years, from 2018 to 2023, saving up to buy a €5,000 PC solely for production. Because streaming isn’t just “playing a game.” Your PC becomes a 4K broadcasting server. You need two graphics cards—or even two separate machines:

- One to run the software or the game

- The other to encode, stream, and record

You also need:

- A second monitor (for video return and replay)

- A replay buffer (to capture instant replays)

- A Stream Deck for seamless transitions

- A Wave XLR for professional audio quality

- Audio interfaces, mixers, USB cameras, XLR microphones

All these high-end peripherals constantly tax your system. You need two USB hubs capable of handling 15 devices at once with no signal loss. A single weak link can ruin everything. And that’s not all. To stream a Nintendo Switch, you need a capture card—and you can’t rely on your streaming software’s preview because of input lag. You have to play directly on the other screen already in place.
¯

_
ONGOING TECHNICAL LEARNING

Streaming requires broad technical expertise:

- Lighting, audio, capture devices, networking

- Compression, codecs, editing, formatting

- Live direction, visual/audio transitions, real-time coordination

And you’re doing all this with zero support from YouTube.
¯

_
STORAGE AND ENERGY COSTS

Your PC isn’t enough anymore. You’ll need a NAS—a network-attached storage system—cheaper than the cloud in the long run, but which demands:

- Two 20 TB drives (mirrored) → 40 TB

- A dedicated server, which adds another €1,000

It’s become a mini television studio. Which brings with it:

- Planned obsolescence

- Frequent breakdowns

- Hardware wear and tear

- Electricity costs of a 1,000-watt PC plus a 24/7 server

Altogether, the setup costs more than a car.
¯

_
AND YOUTUBE PAYS NOTHING

And yet, it’s YouTube that cashes in. It runs ads on your videos—even if you’re not monetized. It hijacks your gear, your energy, your skills. And if your content doesn’t “perform,” it simply ignores you. A PC, cameras, capture cards, hubs, microphones, lights—tens of thousands of euros invested just to exist. And the platform invests nothing in return. No visibility. No value sharing. Not even a word of encouragement.
¯

_
||#HSLdiary #HSLmichael

#InvisibleLabor #PlatformCapitalism #CreatorEconomy #DigitalPrecarity #FreeLabor #YouTubeProblems #Shadowban