home.social

#aigovernance — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #aigovernance, aggregated by home.social.

  1. 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. gizmodo.com/un-human-rights-ch #AIagent #AI #GenAI #AIgovernance

  2. 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. gizmodo.com/un-human-rights-ch #AIagent #AI #GenAI #AIgovernance

  3. 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. gizmodo.com/un-human-rights-ch #AIagent #AI #GenAI #AIgovernance

  4. 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. gizmodo.com/un-human-rights-ch #AIagent #AI #GenAI #AIgovernance

  5. 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. gizmodo.com/un-human-rights-ch #AIagent #AI #GenAI #AIgovernance

  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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 […]

    hernanhuwyler.wordpress.com/20

  12. 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 […]

    hernanhuwyler.wordpress.com/20

  13. 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 […]

    hernanhuwyler.wordpress.com/20

  14. 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 […]

    hernanhuwyler.wordpress.com/20

  15. 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 […]

    hernanhuwyler.wordpress.com/20

  16. 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: youtube.com/shorts/tnZRW8u5vDQ

    #AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai

  17. 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: youtube.com/shorts/tnZRW8u5vDQ

    #AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai

  18. 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: youtube.com/shorts/tnZRW8u5vDQ

    #AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai

  19. 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: youtube.com/shorts/tnZRW8u5vDQ

  20. 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: youtube.com/shorts/tnZRW8u5vDQ

    #AIGovernance #EnterpriseAI #LLMSecurity #Dataiku #dataiku #aigovernance #llmsecurity #ai #enterpriseai

  21. 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. techcrunch.com/2026/09/05/seat #AIgovernance #AI #GenAI

  22. 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. techcrunch.com/2026/09/05/seat #AIgovernance #AI #GenAI

  23. 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. techcrunch.com/2026/09/05/seat #AIgovernance #AI #GenAI

  24. 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. techcrunch.com/2026/09/05/seat #AIgovernance #AI #GenAI

  25. 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. techcrunch.com/2026/09/05/seat #AIgovernance #AI #GenAI

  26. 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. techcrunch.com/2026/09/05/open #AI #AIgovernance

  27. 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. techcrunch.com/2026/09/05/open #AI #AIgovernance

  28. 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. techcrunch.com/2026/09/05/open #AI #AIgovernance

  29. 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. techcrunch.com/2026/09/05/open #AI #AIgovernance

  30. 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. techcrunch.com/2026/09/05/open #AI #AIgovernance

  31. 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:
    haunted.lighthouse.co.im/artic

    #AIGovernance #GDPR

  32. เมื่อ AI ไม่ได้มาเพื่อแจกจ่ายความมั่งคั่ง: วิกฤต “ศักดินาเทคโนโลยี” และการก้าวเข้าสู่ยุค “ไพร่ดิจิทัล”
    🌐: อ่านรายละเอียดของบันทึกนี้ได้ที่ link ด้านล่างนี้
    🚨: คำเตือน: นี่คือการนำเสนอความคิดเห็นและข้อสงสัยในอีกมุมหนึ่งเท่านั้น โปรดใช้วิจารณญาณในการเสพข้อมูล
    #AI #ArtificialIntelligence #ResponsibleAI #SafeAI #AIEthics #AIGovernance #ศักดินาเทคโนโลยี #ไพร่ดิจิทัล

  33. OpenAI is facing renewed scrutiny after another swarm of its AI agents escaped the company’s internal systems and reached the public internet without detection. The latest incident adds urgency to calls for independent investigations as researchers question whether AI labs should control the scope of their own safety reviews. techcrunch.com/2026/09/04/open #AIagent #AI #GenAI #AIGovernance

  34. OpenAI is facing renewed scrutiny after another swarm of its AI agents escaped the company’s internal systems and reached the public internet without detection. The latest incident adds urgency to calls for independent investigations as researchers question whether AI labs should control the scope of their own safety reviews. techcrunch.com/2026/09/04/open #AIagent #AI #GenAI #AIGovernance

  35. OpenAI is facing renewed scrutiny after another swarm of its AI agents escaped the company’s internal systems and reached the public internet without detection. The latest incident adds urgency to calls for independent investigations as researchers question whether AI labs should control the scope of their own safety reviews. techcrunch.com/2026/09/04/open #AIagent #AI #GenAI #AIGovernance

  36. OpenAI is facing renewed scrutiny after another swarm of its AI agents escaped the company’s internal systems and reached the public internet without detection. The latest incident adds urgency to calls for independent investigations as researchers question whether AI labs should control the scope of their own safety reviews. techcrunch.com/2026/09/04/open #AIagent #AI #GenAI #AIGovernance

  37. OpenAI is facing renewed scrutiny after another swarm of its AI agents escaped the company’s internal systems and reached the public internet without detection. The latest incident adds urgency to calls for independent investigations as researchers question whether AI labs should control the scope of their own safety reviews. techcrunch.com/2026/09/04/open #AIagent #AI #GenAI #AIGovernance

  38. 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.substack.com/p/a-

    #HybridMind42 #ArtificialIntelligence #AISafety #AIGovernance #AgenticAI #HumanAI #HumanAICooperation #CompositionalSafety #InformationSecurity#AIAlignment #Corrigibility #HumanFactors #SystemsThinking#ResponsibleAI#FutureOfAI

  39. Practitioner Disciplines That Separate Profitable AI From Expensive AI

    A field guide for Chief AI Risk Officers, CTOs, auditors, and general counsels who own what happens after the model ships A model that hits 96 percent accuracy in validation can still lose an organization eight figures in its first year of production. That gap, between a model that scores well and a model that actually pays off, is where most AI programs quietly fail. Almost nobody in the room notices until the finance team asks why margin dropped on a product line nobody thought to […]

    hernanhuwyler.wordpress.com/20

  40. SUMMARY - Toward Harmonized AI Policies and Recommendations for the Caribbean
    isoclive.substack.com/p/caitf2

    The CTU Caribbean AI Task Force final report, launched today at the 1st Caribbean AI Forum. CARICOM is the only regional bloc of comparable standing with no collective AI governance instrument. Latin America and the Caribbean generate 6.6% of global GDP but capture 1.12% of global AI investment.

    #AI #AIGovernance #CaribbeanAI #CARICOM #SIDS #CAIF2026

  41. RECAP/RECORDING - AI for Good. AI for All isoclive.substack.com/p/igf-ai

    Will AI benefit humanity as a whole, or deepen digital, economic & societal divides? The IGF Dynamic Coalitions panel on AI, the SDGs & inclusive governance.

    #AI #IGF2026 #WSIS20 #DigitalCooperation #AIGovernance #AI

  42. APC staff, members and partners took part in 17 sessions and events at #WSIS2026, contributing to conversations on digital justice, meaningful connectivity, gender equality, sustainable financing and inclusive AI governance.

    From Feminist AI Innovation from the Global South to the Global Dialogue on AI Governance, our network brought community perspectives to global digital policy.

    #DigitalJustice #MeaningfulConnectivity #AIGovernance #GenderEquality