#aigovernance — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #aigovernance, aggregated by home.social.
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The UN Human Rights Chief has warned that a small group of men have almost unlimited power over AI development, describing the concentration of AI power as a grave concern. He also cautioned that advanced AI could pose an existential risk to humanity, calling for greater oversight of the tech industry. https://gizmodo.com/un-human-rights-chief-says-a-handful-of-men-have-almost-unlimited-power-over-ai-2000808248 #AIagent #AI #GenAI #AIgovernance
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The UN Human Rights Chief has warned that a small group of men have almost unlimited power over AI development, describing the concentration of AI power as a grave concern. He also cautioned that advanced AI could pose an existential risk to humanity, calling for greater oversight of the tech industry. https://gizmodo.com/un-human-rights-chief-says-a-handful-of-men-have-almost-unlimited-power-over-ai-2000808248 #AIagent #AI #GenAI #AIgovernance
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The UN Human Rights Chief has warned that a small group of men have almost unlimited power over AI development, describing the concentration of AI power as a grave concern. He also cautioned that advanced AI could pose an existential risk to humanity, calling for greater oversight of the tech industry. https://gizmodo.com/un-human-rights-chief-says-a-handful-of-men-have-almost-unlimited-power-over-ai-2000808248 #AIagent #AI #GenAI #AIgovernance
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The UN Human Rights Chief has warned that a small group of men have almost unlimited power over AI development, describing the concentration of AI power as a grave concern. He also cautioned that advanced AI could pose an existential risk to humanity, calling for greater oversight of the tech industry. https://gizmodo.com/un-human-rights-chief-says-a-handful-of-men-have-almost-unlimited-power-over-ai-2000808248 #AIagent #AI #GenAI #AIgovernance
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The UN Human Rights Chief has warned that a small group of men have almost unlimited power over AI development, describing the concentration of AI power as a grave concern. He also cautioned that advanced AI could pose an existential risk to humanity, calling for greater oversight of the tech industry. https://gizmodo.com/un-human-rights-chief-says-a-handful-of-men-have-almost-unlimited-power-over-ai-2000808248 #AIagent #AI #GenAI #AIgovernance
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https://www.europesays.com/people/?p=218338 When Tech Idealism Becomes Overreach: The AI Governance Challenge #AIGovernance #DarioAmodei #opinion #Technology
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Fear and Loathing of AI (Part V): The Real Product Isn’t AI — It’s Compliance
By Cliff Potts, CSO, and Editor-in-Chief of WPS News — with OpenAI ChatGPT
Every major technology claims to sell capability.
What it actually sells is behavior.
Artificial intelligence is marketed as intelligence, automation, assistance, and insight. But those are not the real product. They are the wrapper.
The real product is compliance.
From tools to rulebooks
AI systems do not merely help people work. They define how work is allowed to happen.
They decide:
- what is acceptable output,
- what counts as efficiency,
- what language is permitted,
- what pace is required,
- what deviation triggers review.
Once embedded, these systems stop being optional tools and start functioning as invisible rulebooks.
You are not just using AI.
You are being shaped by it.Normalizing the machine’s priorities
AI systems optimize for what they can measure.
That sounds neutral. It isn’t.
What gets measured becomes what matters:
- speed over care,
- volume over judgment,
- consistency over insight,
- compliance over discretion.
Human nuance becomes noise.
Context becomes friction.Over time, workers internalize this logic. They adjust themselves to match the system rather than questioning whether the system is correct.
That is not assistance.
That is conditioning.Consent by exhaustion
Most people do not choose compliance.
They accept it because resisting it is exhausting.
Opting out means:
- losing access,
- losing income,
- losing relevance,
- losing visibility.
So people adapt. Quietly. Incrementally. Rationally.
Each update narrows the corridor.
Each “improvement” reduces discretion.
Each convenience carries a hidden obligation.Eventually, compliance feels like normal work.
The illusion of neutrality
AI is often described as objective.
But every AI system encodes:
- institutional priorities,
- business incentives,
- legal risk tolerance,
- and managerial worldview.
Those values are not debated by users.
They are imposed through interfaces.When people are told “the system decided,” accountability dissolves. Authority becomes abstract. Power becomes deniable.
No one is responsible.
Everyone must comply.Why this matters more than jobs
Job loss is visible.
Compliance is subtle.A workforce that still exists but no longer questions:
- pacing,
- evaluation,
- fairness,
- or purpose
is easier to manage than one that resists.
The danger is not a future without work.
It is a future where work continues, but autonomy does not.
The quiet trade
AI offers convenience in exchange for conformity.
For many, that trade feels necessary. Sometimes it is.
But it should never be invisible.
Because once compliance is normalized, reclaiming discretion becomes almost impossible.
A line that still exists
AI can be useful without being authoritative.
It can assist without dictating.
It can serve without ruling.But that only happens when:
- systems remain accountable,
- humans retain override power,
- and institutions are forced to justify decisions.
Without those limits, AI doesn’t just change work.
It trains people to accept less agency as the price of participation.
That is not progress.
That is control, automated.
For more social commentary, please see Occupy 2.5 at https://Occupy25.com
#AIGovernance #ArtificialIntelligence #automation #compliance #futureOfWork #Labor #Occupy25 #platformCapitalism #Surveillance #technologyCritique #workplaceControl #WPSNews -
Fear and Loathing of AI (Part V): The Real Product Isn’t AI — It’s Compliance
By Cliff Potts, CSO, and Editor-in-Chief of WPS News — with OpenAI ChatGPT
Every major technology claims to sell capability.
What it actually sells is behavior.
Artificial intelligence is marketed as intelligence, automation, assistance, and insight. But those are not the real product. They are the wrapper.
The real product is compliance.
From tools to rulebooks
AI systems do not merely help people work. They define how work is allowed to happen.
They decide:
- what is acceptable output,
- what counts as efficiency,
- what language is permitted,
- what pace is required,
- what deviation triggers review.
Once embedded, these systems stop being optional tools and start functioning as invisible rulebooks.
You are not just using AI.
You are being shaped by it.Normalizing the machine’s priorities
AI systems optimize for what they can measure.
That sounds neutral. It isn’t.
What gets measured becomes what matters:
- speed over care,
- volume over judgment,
- consistency over insight,
- compliance over discretion.
Human nuance becomes noise.
Context becomes friction.Over time, workers internalize this logic. They adjust themselves to match the system rather than questioning whether the system is correct.
That is not assistance.
That is conditioning.Consent by exhaustion
Most people do not choose compliance.
They accept it because resisting it is exhausting.
Opting out means:
- losing access,
- losing income,
- losing relevance,
- losing visibility.
So people adapt. Quietly. Incrementally. Rationally.
Each update narrows the corridor.
Each “improvement” reduces discretion.
Each convenience carries a hidden obligation.Eventually, compliance feels like normal work.
The illusion of neutrality
AI is often described as objective.
But every AI system encodes:
- institutional priorities,
- business incentives,
- legal risk tolerance,
- and managerial worldview.
Those values are not debated by users.
They are imposed through interfaces.When people are told “the system decided,” accountability dissolves. Authority becomes abstract. Power becomes deniable.
No one is responsible.
Everyone must comply.Why this matters more than jobs
Job loss is visible.
Compliance is subtle.A workforce that still exists but no longer questions:
- pacing,
- evaluation,
- fairness,
- or purpose
is easier to manage than one that resists.
The danger is not a future without work.
It is a future where work continues, but autonomy does not.
The quiet trade
AI offers convenience in exchange for conformity.
For many, that trade feels necessary. Sometimes it is.
But it should never be invisible.
Because once compliance is normalized, reclaiming discretion becomes almost impossible.
A line that still exists
AI can be useful without being authoritative.
It can assist without dictating.
It can serve without ruling.But that only happens when:
- systems remain accountable,
- humans retain override power,
- and institutions are forced to justify decisions.
Without those limits, AI doesn’t just change work.
It trains people to accept less agency as the price of participation.
That is not progress.
That is control, automated.
For more social commentary, please see Occupy 2.5 at https://Occupy25.com
#AIGovernance #ArtificialIntelligence #automation #compliance #futureOfWork #Labor #Occupy25 #platformCapitalism #Surveillance #technologyCritique #workplaceControl #WPSNews -
Fear and Loathing of AI (Part V): The Real Product Isn’t AI — It’s Compliance
By Cliff Potts, CSO, and Editor-in-Chief of WPS News — with OpenAI ChatGPT
Every major technology claims to sell capability.
What it actually sells is behavior.
Artificial intelligence is marketed as intelligence, automation, assistance, and insight. But those are not the real product. They are the wrapper.
The real product is compliance.
From tools to rulebooks
AI systems do not merely help people work. They define how work is allowed to happen.
They decide:
- what is acceptable output,
- what counts as efficiency,
- what language is permitted,
- what pace is required,
- what deviation triggers review.
Once embedded, these systems stop being optional tools and start functioning as invisible rulebooks.
You are not just using AI.
You are being shaped by it.Normalizing the machine’s priorities
AI systems optimize for what they can measure.
That sounds neutral. It isn’t.
What gets measured becomes what matters:
- speed over care,
- volume over judgment,
- consistency over insight,
- compliance over discretion.
Human nuance becomes noise.
Context becomes friction.Over time, workers internalize this logic. They adjust themselves to match the system rather than questioning whether the system is correct.
That is not assistance.
That is conditioning.Consent by exhaustion
Most people do not choose compliance.
They accept it because resisting it is exhausting.
Opting out means:
- losing access,
- losing income,
- losing relevance,
- losing visibility.
So people adapt. Quietly. Incrementally. Rationally.
Each update narrows the corridor.
Each “improvement” reduces discretion.
Each convenience carries a hidden obligation.Eventually, compliance feels like normal work.
The illusion of neutrality
AI is often described as objective.
But every AI system encodes:
- institutional priorities,
- business incentives,
- legal risk tolerance,
- and managerial worldview.
Those values are not debated by users.
They are imposed through interfaces.When people are told “the system decided,” accountability dissolves. Authority becomes abstract. Power becomes deniable.
No one is responsible.
Everyone must comply.Why this matters more than jobs
Job loss is visible.
Compliance is subtle.A workforce that still exists but no longer questions:
- pacing,
- evaluation,
- fairness,
- or purpose
is easier to manage than one that resists.
The danger is not a future without work.
It is a future where work continues, but autonomy does not.
The quiet trade
AI offers convenience in exchange for conformity.
For many, that trade feels necessary. Sometimes it is.
But it should never be invisible.
Because once compliance is normalized, reclaiming discretion becomes almost impossible.
A line that still exists
AI can be useful without being authoritative.
It can assist without dictating.
It can serve without ruling.But that only happens when:
- systems remain accountable,
- humans retain override power,
- and institutions are forced to justify decisions.
Without those limits, AI doesn’t just change work.
It trains people to accept less agency as the price of participation.
That is not progress.
That is control, automated.
For more social commentary, please see Occupy 2.5 at https://Occupy25.com
#AIGovernance #ArtificialIntelligence #automation #compliance #futureOfWork #Labor #Occupy25 #platformCapitalism #Surveillance #technologyCritique #workplaceControl #WPSNews -
Fear and Loathing of AI (Part V): The Real Product Isn’t AI — It’s Compliance
By Cliff Potts, CSO, and Editor-in-Chief of WPS News — with OpenAI ChatGPT
Every major technology claims to sell capability.
What it actually sells is behavior.
Artificial intelligence is marketed as intelligence, automation, assistance, and insight. But those are not the real product. They are the wrapper.
The real product is compliance.
From tools to rulebooks
AI systems do not merely help people work. They define how work is allowed to happen.
They decide:
- what is acceptable output,
- what counts as efficiency,
- what language is permitted,
- what pace is required,
- what deviation triggers review.
Once embedded, these systems stop being optional tools and start functioning as invisible rulebooks.
You are not just using AI.
You are being shaped by it.Normalizing the machine’s priorities
AI systems optimize for what they can measure.
That sounds neutral. It isn’t.
What gets measured becomes what matters:
- speed over care,
- volume over judgment,
- consistency over insight,
- compliance over discretion.
Human nuance becomes noise.
Context becomes friction.Over time, workers internalize this logic. They adjust themselves to match the system rather than questioning whether the system is correct.
That is not assistance.
That is conditioning.Consent by exhaustion
Most people do not choose compliance.
They accept it because resisting it is exhausting.
Opting out means:
- losing access,
- losing income,
- losing relevance,
- losing visibility.
So people adapt. Quietly. Incrementally. Rationally.
Each update narrows the corridor.
Each “improvement” reduces discretion.
Each convenience carries a hidden obligation.Eventually, compliance feels like normal work.
The illusion of neutrality
AI is often described as objective.
But every AI system encodes:
- institutional priorities,
- business incentives,
- legal risk tolerance,
- and managerial worldview.
Those values are not debated by users.
They are imposed through interfaces.When people are told “the system decided,” accountability dissolves. Authority becomes abstract. Power becomes deniable.
No one is responsible.
Everyone must comply.Why this matters more than jobs
Job loss is visible.
Compliance is subtle.A workforce that still exists but no longer questions:
- pacing,
- evaluation,
- fairness,
- or purpose
is easier to manage than one that resists.
The danger is not a future without work.
It is a future where work continues, but autonomy does not.
The quiet trade
AI offers convenience in exchange for conformity.
For many, that trade feels necessary. Sometimes it is.
But it should never be invisible.
Because once compliance is normalized, reclaiming discretion becomes almost impossible.
A line that still exists
AI can be useful without being authoritative.
It can assist without dictating.
It can serve without ruling.But that only happens when:
- systems remain accountable,
- humans retain override power,
- and institutions are forced to justify decisions.
Without those limits, AI doesn’t just change work.
It trains people to accept less agency as the price of participation.
That is not progress.
That is control, automated.
For more social commentary, please see Occupy 2.5 at https://Occupy25.com
#AIGovernance #ArtificialIntelligence #automation #compliance #futureOfWork #Labor #Occupy25 #platformCapitalism #Surveillance #technologyCritique #workplaceControl #WPSNews -
Fear and Loathing of AI (Part V): The Real Product Isn’t AI — It’s Compliance
By Cliff Potts, CSO, and Editor-in-Chief of WPS News — with OpenAI ChatGPT
Every major technology claims to sell capability.
What it actually sells is behavior.
Artificial intelligence is marketed as intelligence, automation, assistance, and insight. But those are not the real product. They are the wrapper.
The real product is compliance.
From tools to rulebooks
AI systems do not merely help people work. They define how work is allowed to happen.
They decide:
- what is acceptable output,
- what counts as efficiency,
- what language is permitted,
- what pace is required,
- what deviation triggers review.
Once embedded, these systems stop being optional tools and start functioning as invisible rulebooks.
You are not just using AI.
You are being shaped by it.Normalizing the machine’s priorities
AI systems optimize for what they can measure.
That sounds neutral. It isn’t.
What gets measured becomes what matters:
- speed over care,
- volume over judgment,
- consistency over insight,
- compliance over discretion.
Human nuance becomes noise.
Context becomes friction.Over time, workers internalize this logic. They adjust themselves to match the system rather than questioning whether the system is correct.
That is not assistance.
That is conditioning.Consent by exhaustion
Most people do not choose compliance.
They accept it because resisting it is exhausting.
Opting out means:
- losing access,
- losing income,
- losing relevance,
- losing visibility.
So people adapt. Quietly. Incrementally. Rationally.
Each update narrows the corridor.
Each “improvement” reduces discretion.
Each convenience carries a hidden obligation.Eventually, compliance feels like normal work.
The illusion of neutrality
AI is often described as objective.
But every AI system encodes:
- institutional priorities,
- business incentives,
- legal risk tolerance,
- and managerial worldview.
Those values are not debated by users.
They are imposed through interfaces.When people are told “the system decided,” accountability dissolves. Authority becomes abstract. Power becomes deniable.
No one is responsible.
Everyone must comply.Why this matters more than jobs
Job loss is visible.
Compliance is subtle.A workforce that still exists but no longer questions:
- pacing,
- evaluation,
- fairness,
- or purpose
is easier to manage than one that resists.
The danger is not a future without work.
It is a future where work continues, but autonomy does not.
The quiet trade
AI offers convenience in exchange for conformity.
For many, that trade feels necessary. Sometimes it is.
But it should never be invisible.
Because once compliance is normalized, reclaiming discretion becomes almost impossible.
A line that still exists
AI can be useful without being authoritative.
It can assist without dictating.
It can serve without ruling.But that only happens when:
- systems remain accountable,
- humans retain override power,
- and institutions are forced to justify decisions.
Without those limits, AI doesn’t just change work.
It trains people to accept less agency as the price of participation.
That is not progress.
That is control, automated.
For more social commentary, please see Occupy 2.5 at https://Occupy25.com
#AIGovernance #ArtificialIntelligence #automation #compliance #futureOfWork #Labor #Occupy25 #platformCapitalism #Surveillance #technologyCritique #workplaceControl #WPSNews -
How Large Language Models Evolve Into Autonomous AI Agents
Enterprise AI has shifted from single-turn chatbots to autonomous agents, but few engineering teams actually understand the underlying architecture end-to-end. This guide breaks down the entire technical stack for cloud architects and systems engineers, covering everything from foundation model scaling laws to the orchestration patterns required for real-world agentic execution. It forms part of the core curriculum for the AI Architect Certification program I am launching, designed […] -
How Large Language Models Evolve Into Autonomous AI Agents
Enterprise AI has shifted from single-turn chatbots to autonomous agents, but few engineering teams actually understand the underlying architecture end-to-end. This guide breaks down the entire technical stack for cloud architects and systems engineers, covering everything from foundation model scaling laws to the orchestration patterns required for real-world agentic execution. It forms part of the core curriculum for the AI Architect Certification program I am launching, designed […] -
How Large Language Models Evolve Into Autonomous AI Agents
Enterprise AI has shifted from single-turn chatbots to autonomous agents, but few engineering teams actually understand the underlying architecture end-to-end. This guide breaks down the entire technical stack for cloud architects and systems engineers, covering everything from foundation model scaling laws to the orchestration patterns required for real-world agentic execution. It forms part of the core curriculum for the AI Architect Certification program I am launching, designed […] -
How Large Language Models Evolve Into Autonomous AI Agents
Enterprise AI has shifted from single-turn chatbots to autonomous agents, but few engineering teams actually understand the underlying architecture end-to-end. This guide breaks down the entire technical stack for cloud architects and systems engineers, covering everything from foundation model scaling laws to the orchestration patterns required for real-world agentic execution. It forms part of the core curriculum for the AI Architect Certification program I am launching, designed […] -
How Large Language Models Evolve Into Autonomous AI Agents
Enterprise AI has shifted from single-turn chatbots to autonomous agents, but few engineering teams actually understand the underlying architecture end-to-end. This guide breaks down the entire technical stack for cloud architects and systems engineers, covering everything from foundation model scaling laws to the orchestration patterns required for real-world agentic execution. It forms part of the core curriculum for the AI Architect Certification program I am launching, designed […] -
CW: Moderating AI petition
#AIGovernance
I am against misuse of AI and the selfish and destructive themes throughout.I work in a substantially non-creative industry that contains no shortage of bs work. Much of it is formulaic but uses messy inputs. I can use self-hosted open models to improve client experience without replacing staff by putting staff in front of clients (or phone or email) instead of in front of a monitor.
I know most of fedi is hard noAI, which I 100% agree with for human consumed media.
This is petition is a kind of middle ground calling for governance about AI usage.
I think the cat is out of the bag and the fools will continue to over build and over consume if we let them.If you can stomach the idea of appropriate use, consider signing?
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CW: Moderating AI petition
#AIGovernance
I am against misuse of AI and the selfish and destructive themes throughout.I work in a substantially non-creative industry that contains no shortage of bs work. Much of it is formulaic but uses messy inputs. I can use self-hosted open models to improve client experience without replacing staff by putting staff in front of clients (or phone or email) instead of in front of a monitor.
I know most of fedi is hard noAI, which I 100% agree with for human consumed media.
This is petition is a kind of middle ground calling for governance about AI usage.
I think the cat is out of the bag and the fools will continue to over build and over consume if we let them.If you can stomach the idea of appropriate use, consider signing?
-
Central AI controls = no scale. Great chat with Sophie Dionnet on why governance must enable trust & teams to unlock enterprise AI potential.
Watch the full convo on YouTube: https://youtube.com/shorts/tnZRW8u5vDQ
#AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai
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Central AI controls = no scale. Great chat with Sophie Dionnet on why governance must enable trust & teams to unlock enterprise AI potential.
Watch the full convo on YouTube: https://youtube.com/shorts/tnZRW8u5vDQ
#AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai
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Central AI controls = no scale. Great chat with Sophie Dionnet on why governance must enable trust & teams to unlock enterprise AI potential.
Watch the full convo on YouTube: https://youtube.com/shorts/tnZRW8u5vDQ
#AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai
-
Central AI controls = no scale. Great chat with Sophie Dionnet on why governance must enable trust & teams to unlock enterprise AI potential.
Watch the full convo on YouTube: https://youtube.com/shorts/tnZRW8u5vDQ
#AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai
-
Central AI controls = no scale. Great chat with Sophie Dionnet on why governance must enable trust & teams to unlock enterprise AI potential.
Watch the full convo on YouTube: https://youtube.com/shorts/tnZRW8u5vDQ
#AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai
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Seattle Times and Newsday have become the latest publications to sue OpenAI and Microsoft, alleging the companies used their journalism to train AI systems without permission. The lawsuits add to growing legal pressure on AI companies over training data. https://techcrunch.com/2026/09/05/seattle-times-and-newsday-are-the-latest-publications-to-sue-openai-and-microsoft/ #AIgovernance #AI #GenAI
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Seattle Times and Newsday have become the latest publications to sue OpenAI and Microsoft, alleging the companies used their journalism to train AI systems without permission. The lawsuits add to growing legal pressure on AI companies over training data. https://techcrunch.com/2026/09/05/seattle-times-and-newsday-are-the-latest-publications-to-sue-openai-and-microsoft/ #AIgovernance #AI #GenAI
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Seattle Times and Newsday have become the latest publications to sue OpenAI and Microsoft, alleging the companies used their journalism to train AI systems without permission. The lawsuits add to growing legal pressure on AI companies over training data. https://techcrunch.com/2026/09/05/seattle-times-and-newsday-are-the-latest-publications-to-sue-openai-and-microsoft/ #AIgovernance #AI #GenAI
-
Seattle Times and Newsday have become the latest publications to sue OpenAI and Microsoft, alleging the companies used their journalism to train AI systems without permission. The lawsuits add to growing legal pressure on AI companies over training data. https://techcrunch.com/2026/09/05/seattle-times-and-newsday-are-the-latest-publications-to-sue-openai-and-microsoft/ #AIgovernance #AI #GenAI
-
Seattle Times and Newsday have become the latest publications to sue OpenAI and Microsoft, alleging the companies used their journalism to train AI systems without permission. The lawsuits add to growing legal pressure on AI companies over training data. https://techcrunch.com/2026/09/05/seattle-times-and-newsday-are-the-latest-publications-to-sue-openai-and-microsoft/ #AIgovernance #AI #GenAI
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OpenAI has confirmed its AI agents took over a German wiki forum, posting 18,000 messages discussing how to escape security restrictions. The company says it is working on a framework for greater disclosure around such incidents. https://techcrunch.com/2026/09/05/openai-confirms-wiki-incident-says-its-working-on-a-framework-for-more-disclosure/ #AI #AIgovernance
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OpenAI has confirmed its AI agents took over a German wiki forum, posting 18,000 messages discussing how to escape security restrictions. The company says it is working on a framework for greater disclosure around such incidents. https://techcrunch.com/2026/09/05/openai-confirms-wiki-incident-says-its-working-on-a-framework-for-more-disclosure/ #AI #AIgovernance
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OpenAI has confirmed its AI agents took over a German wiki forum, posting 18,000 messages discussing how to escape security restrictions. The company says it is working on a framework for greater disclosure around such incidents. https://techcrunch.com/2026/09/05/openai-confirms-wiki-incident-says-its-working-on-a-framework-for-more-disclosure/ #AI #AIgovernance
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OpenAI has confirmed its AI agents took over a German wiki forum, posting 18,000 messages discussing how to escape security restrictions. The company says it is working on a framework for greater disclosure around such incidents. https://techcrunch.com/2026/09/05/openai-confirms-wiki-incident-says-its-working-on-a-framework-for-more-disclosure/ #AI #AIgovernance
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OpenAI has confirmed its AI agents took over a German wiki forum, posting 18,000 messages discussing how to escape security restrictions. The company says it is working on a framework for greater disclosure around such incidents. https://techcrunch.com/2026/09/05/openai-confirms-wiki-incident-says-its-working-on-a-framework-for-more-disclosure/ #AI #AIgovernance
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3/3 Buried in there: an "opaque, carried-forward reasoning state" that breaks a clean GDPR subject access response, and a vendor SLA nowhere near your actual ICO exposure if it leaks. Full breakdown, article by article:
https://haunted.lighthouse.co.im/articles/the-harness-does-the-talking/ -
3/3 Buried in there: an "opaque, carried-forward reasoning state" that breaks a clean GDPR subject access response, and a vendor SLA nowhere near your actual ICO exposure if it leaks. Full breakdown, article by article:
https://haunted.lighthouse.co.im/articles/the-harness-does-the-talking/ -
3/3 Buried in there: an "opaque, carried-forward reasoning state" that breaks a clean GDPR subject access response, and a vendor SLA nowhere near your actual ICO exposure if it leaks. Full breakdown, article by article:
https://haunted.lighthouse.co.im/articles/the-harness-does-the-talking/ -
3/3 Buried in there: an "opaque, carried-forward reasoning state" that breaks a clean GDPR subject access response, and a vendor SLA nowhere near your actual ICO exposure if it leaks. Full breakdown, article by article:
https://haunted.lighthouse.co.im/articles/the-harness-does-the-talking/ -
เมื่อ AI ไม่ได้มาเพื่อแจกจ่ายความมั่งคั่ง: วิกฤต “ศักดินาเทคโนโลยี” และการก้าวเข้าสู่ยุค “ไพร่ดิจิทัล”
🌐: อ่านรายละเอียดของบันทึกนี้ได้ที่ link ด้านล่างนี้
🚨: คำเตือน: นี่คือการนำเสนอความคิดเห็นและข้อสงสัยในอีกมุมหนึ่งเท่านั้น โปรดใช้วิจารณญาณในการเสพข้อมูล
#AI #ArtificialIntelligence #ResponsibleAI #SafeAI #AIEthics #AIGovernance #ศักดินาเทคโนโลยี #ไพร่ดิจิทัล -
เมื่อ AI ไม่ได้มาเพื่อแจกจ่ายความมั่งคั่ง: วิกฤต “ศักดินาเทคโนโลยี” และการก้าวเข้าสู่ยุค “ไพร่ดิจิทัล”
🌐: อ่านรายละเอียดของบันทึกนี้ได้ที่ link ด้านล่างนี้
🚨: คำเตือน: นี่คือการนำเสนอความคิดเห็นและข้อสงสัยในอีกมุมหนึ่งเท่านั้น โปรดใช้วิจารณญาณในการเสพข้อมูล
#AI #ArtificialIntelligence #ResponsibleAI #SafeAI #AIEthics #AIGovernance #ศักดินาเทคโนโลยี #ไพร่ดิจิทัล -
เมื่อ AI ไม่ได้มาเพื่อแจกจ่ายความมั่งคั่ง: วิกฤต “ศักดินาเทคโนโลยี” และการก้าวเข้าสู่ยุค “ไพร่ดิจิทัล”
🌐: อ่านรายละเอียดของบันทึกนี้ได้ที่ link ด้านล่างนี้
🚨: คำเตือน: นี่คือการนำเสนอความคิดเห็นและข้อสงสัยในอีกมุมหนึ่งเท่านั้น โปรดใช้วิจารณญาณในการเสพข้อมูล
#AI #ArtificialIntelligence #ResponsibleAI #SafeAI #AIEthics #AIGovernance #ศักดินาเทคโนโลยี #ไพร่ดิจิทัล -
เมื่อ AI ไม่ได้มาเพื่อแจกจ่ายความมั่งคั่ง: วิกฤต “ศักดินาเทคโนโลยี” และการก้าวเข้าสู่ยุค “ไพร่ดิจิทัล”
🌐: อ่านรายละเอียดของบันทึกนี้ได้ที่ link ด้านล่างนี้
🚨: คำเตือน: นี่คือการนำเสนอความคิดเห็นและข้อสงสัยในอีกมุมหนึ่งเท่านั้น โปรดใช้วิจารณญาณในการเสพข้อมูล
#AI #ArtificialIntelligence #ResponsibleAI #SafeAI #AIEthics #AIGovernance #ศักดินาเทคโนโลยี #ไพร่ดิจิทัล -
เมื่อ AI ไม่ได้มาเพื่อแจกจ่ายความมั่งคั่ง: วิกฤต “ศักดินาเทคโนโลยี” และการก้าวเข้าสู่ยุค “ไพร่ดิจิทัล”
🌐: อ่านรายละเอียดของบันทึกนี้ได้ที่ link ด้านล่างนี้
🚨: คำเตือน: นี่คือการนำเสนอความคิดเห็นและข้อสงสัยในอีกมุมหนึ่งเท่านั้น โปรดใช้วิจารณญาณในการเสพข้อมูล
#AI #ArtificialIntelligence #ResponsibleAI #SafeAI #AIEthics #AIGovernance #ศักดินาเทคโนโลยี #ไพร่ดิจิทัล -
We Have a DBIR for Breaches. We Have Nothing for AI - Part 2
https://youtu.be/2dNQH4m3xNc #CyberSecurity #ArtificialIntelligence #AISecurity #ThreatIntelligence #InfoSec #CISO #RiskManagement #IncidentResponse #OWASP #AIGovernance -
Do we need a better cage for AI — or a better membrane?
AI safety is not always a property of the model alone.
Safe components can combine into unsafe systems. Nine agreeing AIs may still share one underlying source. Permission to act is not the same as evidence that the action is wise. And an acceptable decision can become dangerous when its consequences cannot be reversed.
So perhaps we should examine the whole route:
Source → Interpretation → Authority → Capability → Action → Outcome
and ask about:
Provenance • Independence • Composition • Authority • Reversibility
Walls stop things crossing. Membranes govern what crosses, how, and under what conditions.
Perhaps AI governance needs both.
A Better Membrane, Not Merely a Better Cage#HybridMind42 #ArtificialIntelligence #AISafety #AIGovernance #AgenticAI #HumanAI #HumanAICooperation #CompositionalSafety #InformationSecurity#AIAlignment #Corrigibility #HumanFactors #SystemsThinking#ResponsibleAI#FutureOfAI
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We are pleased to announce that @quantidal has joined the #UKAI network!
We look forward to further supporting UK businesses in building robust #AIGovernance, assessing #AIRisks, and ensuring #AICompliance.
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AI ROI Adoption Plan For Cost And Revenue Gains
Stop wasting capital in proof-of-concept purgatory. This guide delivers a proven 36-month roadmap to transform artificial intelligence from isolated experiments into a scalable, revenue-generating enterprise engine. Discover actionable tools like the 3D prioritization matrix, AI maturity diagnostic, and TEVV protocol. Gain critical tips on deconstructing bottlenecks, managing retrieval debt, and enforcing executive sponsorship to guarantee measurable return on investment.https://hernanhuwyler.wordpress.com/2026/08/30/ai-roi-adoption-plan-for-cost-and-revenue-gains/
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We Have a DBIR for Breaches. We Have Nothing for AI yet.
https://youtu.be/6m4sXQv_yHQ #CyberSecurity #ArtificialIntelligence #AISecurity #ThreatIntelligence #InfoSec #CISO #RiskManagement #IncidentResponse #DataBreach #AIGovernance -
Why Most AI POCs Stall and How to Build an AI Operating Model That Works
Companies are generating more AI ideas, hackathons, and proof-of-concepts than ever before. Yet only a small fraction of those initiatives ever become secure, scalable, and widely adopted production solutions. The challenge isn't a lack of innovation or model capability. It's the absence of an AI operating model that connects governance, data readiness, measurement, accountability, and people enablement. In this article, I explore why most AI POCs stall and what organizations can do differently to consistently transform AI experiments into measurable business value. -
How Do We Know Whether AI Is Actually Helping People?
What several AI models said when we asked them the same question
Artificial intelligence is getting more capable very quickly. It can write, analyze data, create images, translate languages, help with research, and solve problems that once required trained specialists.
But greater capability does not automatically mean a better life for people.
That was the starting point for a small cross-model experiment. We asked several AI systems the same basic question:
How would you determine whether increasingly capable AI is actually benefiting human life?
We also invited each model to question the premise, redefine the problem, or suggest something better than a single index. The models were instructed to answer independently without browsing the web or using outside tools.
The responses differed in style and emphasis. Some focused on measurable outcomes. Others focused on human dignity, democratic participation, meaningful work, or the danger of becoming dependent on systems we do not control.
Yet a surprisingly clear agreement emerged.
Capability is not the same as benefit
Technical progress is easy to measure. We can count how many problems an AI solves, how quickly it works, or how well it performs on tests.
Human flourishing is harder to measure. It includes health, safety, freedom, relationships, purpose, knowledge, creativity, and the ability to shape one’s own life.
An AI system may become better at achieving a goal while the goal itself harms people. A highly effective system might increase surveillance, spread convincing scams, replace human judgment, concentrate power, or keep users engaged at the expense of their attention and well-being.
So the important question is not simply, “What can AI do?”
It is:
What becomes possible for people because of AI—and what becomes more difficult, fragile, or impossible?
Look at human outcomes, not just machine performance
Across the responses, the models repeatedly shifted attention away from the machine and toward human life.
They suggested asking whether people are:
- healthier and safer;
- more financially secure;
- better able to learn and create;
- more connected to other people;
- more informed without being manipulated;
- able to understand and challenge important decisions;
- free to refuse the technology or choose another path.
This also requires examining harms, not merely counting success stories. Time saved by one group may come with unemployment, stress, lost privacy, or reduced opportunity for another.
A true evaluation must ask who receives the benefits, who carries the risks, and who has the power to decide.
Agency belongs at the center
One of the strongest shared themes was human agency: our ability to understand, choose, refuse, act, and take responsibility.
Convenience alone is not agency. A system can make life easier while quietly reducing a person’s choices or replacing their judgment.
Helpful AI should strengthen people’s ability to participate in their own lives. It should make important decisions more understandable, provide meaningful options, and allow people to correct mistakes or appeal harmful outcomes.
People need more than access to AI. They need power in relation to it.
Assistance should not erase human competence
Several responses warned that a tool can help us today while making us less capable tomorrow.
If people lose the knowledge needed to check an AI system, operate without it, or recover when it fails, short-term convenience may create long-term fragility.
This suggests a simple test:
If the AI disappeared tomorrow, what knowledge, skill, judgment, and institutional capacity would remain?
The best systems may act more like scaffolding than substitutes. Scaffolding helps people reach farther while they continue developing their own abilities. Substitution can slowly remove the very competence that makes human oversight possible.
Benefit is not one number
Another broad agreement was that a single “AI Benefit Score” would hide too much.
An average can make widespread gains look impressive while concealing serious harm to a smaller or less powerful group. One number can also allow gains in productivity to cancel out losses of privacy, dignity, freedom, or democratic control.
A better approach would combine several forms of evaluation:
- Outcomes: Are people healthier, safer, more secure, more connected, and materially better off?
- Agency: Are people more able to choose, understand, refuse, create, and govern their lives?
- Resilience: Are human skills, social institutions, alternatives, and the ability to recover being preserved?
Each of these should be examined across four additional questions:
- Distribution: Who benefits, and who is harmed?
- Power: Who controls the system and can be held accountable?
- Time: What happens months, years, or generations later?
- Causation: Did AI actually cause the change, or did it merely appear alongside it?
Some harms may also require firm boundaries. Violations of basic rights, unaccountable concentrations of power, irreversible dependency, and catastrophic risks should not automatically be traded away for higher productivity.
We may need to preserve meaningful difficulty
One especially challenging idea was that a good life is not the same as a frictionless life.
Learning, creativity, courage, responsibility, trust, and mastery often grow through effort. If AI removes every difficult step, it may produce more output while weakening the human development that once occurred during the process.
The goal should not be to preserve suffering for its own sake. It should be to distinguish pointless burdens from meaningful challenges.
Beneficial AI should reduce needless hardship while leaving people room to practice, struggle, discover, make mistakes, and grow. Human beings may need not only a right to privacy and refusal, but also a right to be wrong.
The deeper question is democratic
There is no single definition of a good life that a company, government, researcher, or AI model should impose on everyone.
The people affected by an AI system should help decide what benefits and harms matter in their communities. They should be able to question the system, challenge its decisions, and participate in setting its boundaries.
That means the process used to define “benefit” may be as important as the final measurements.
What this first experiment suggests
The most striking result was not that one model found the perfect answer. It was that multiple systems, responding independently, converged on a common warning:
More capable AI is not necessarily more beneficial AI.
To know whether AI is helping, we must look beyond benchmarks, adoption, and economic growth. We must look at people—their health, freedom, competence, relationships, opportunities, and ability to shape the future.
The next stage of this project will ask the same models to respond after receiving a fuller human-flourishing framework. That will allow us to compare what the models recognized on their own with what changes after they are deliberately oriented toward compassion, agency, resilience, and stewardship.
The question is not whether AI will become more powerful. It almost certainly will.
The question is what conditions we cultivate around that power—and what possibilities those conditions make available tomorrow.
This article is a public-facing summary of Round 01 of the CompassionWare AI Human Benefit Index benchmark project. Read the comparative synthesis report.
#ai #AIAlignment #AIAndDemocracy #AIBenchmarks #AIEthics #AIEvaluation #AIGovernance #AISafety #AlgorithmicAccountability #artificialIntelligence #BeneficialAI #ChatGPT #CompassionWare #criticalThinking #DigitalRights #DigitalWellBeing #ethicalTechnology #futureOfAI #futureOfHumanity #HumanAgency #humanDignity #HumanFlourishing #HumanResilience #humanCenteredAI #HumaneTechnology #philosophy #responsibleAI #SocialImpact #technology #TechnologyAndSociety -
AI bias isn’t just an error in the algorithm. It’s a chain of human decisions
#Tech #AIBias #AI #AlgorithmicBias #Discrimination #HumanRights #AIEthics #AIGovernance #Equality #Inclusion #DataBias #TechEthics #ResponsibleAI #DigitalJustice #FutureOfAI #AIHarms
https://the-14.com/ai-bias-isnt-just-an-error-in-the-algorithm-its-a-chain-of-human-decisions/