Basil C. Puglisi

Digital Strategy, Content, and AI Since 2009

AI accountability

Human-AI Collaboration Needs More Than a Human in the Loop

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Human oversight of automated systems is older than AI, and current AI practice still falls short of it.

This paper traces human oversight and accountability from the cybernetics literature of 1948 to Article 14 of the EU AI Act, then separates Responsible AI from AI Governance. It sets out Checkpoint-Based Governance, where a named human holds binding authority to accept, modify, or reject an AI output and leaves a record, and it proposes the studies that would test it. It closes on the Growth OS, a future of work in which AI amplifies people instead of replacing them.

A Year Ago I Told You AGI Was Hype. Superintelligence Is Further Off Than Sold, and It Will Not End Us.

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The machine is never the one who answers for what it does.

A September 2025 essay argued that AGI talk is usually about money and not reality. This September, Andrew Ng, Timnit Gebru, and Emily Bender reached the same point about responsibility from opposite sides of the AI debate. The piece separates real capability from the claims stacked on it, argues that superintelligence is further off than sold and will not end us, and moves from a human chain of responsibility to a real checkpoint.

Humans Are Optional When Defining AI Governance for ISO, According to the U.S. Technical Advisory Group

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A standards body just wrote down that AI governance can exist without a human in control.

In September 2026 the U.S. TAG to ISO/TC 258 answered a public comment on the draft AI standard for project management. It accepted two editorial corrections and rejected the one that would have put binding human authority and attributable accountability inside the definition. This is the filing, the four reasons for the rejection, and why a definition without a governor fails the moral test the public is already applying.

What AI Transformation Actually Requires

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AI products can be purchased. AI transformation has to be built.

This paper reframes fifteen commonly cited requirements for AI transformation as operational management requirements, from data provenance and purpose to decision traceability and value realization. It shows why automation and observation cannot serve as the sole control on consequential work, and how named human checkpoints close that gap.

The AI HOAX Distraction: Safety, Money, and Why You Can’t Tell Which Is Driving

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Six positions in nine days, and every one of them fits the speaker’s balance sheet.

In September 2026 four frontier labs called for a slowdown, the President called the whole thing a hoax, and two of the largest companies in AI said the market already handles it. This piece argues the slowdown is not evidence that governance is working. It is evidence that economic incentives are still in charge, with the sign flipped. Readers get the dated exposure curve behind the calls, the reason liability cannot currently steer, and a narrower proposal than pacing the frontier.

A Munich Court Rejected the AI Disclaimer Defense. A Frontier AI Company Answers for What It Publishes.

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A German court just told Google it answers for what its AI publishes. The Munich ruling treats AI Overviews as Google’s own statements, not safe search results, and says the disclaimer does not transfer the duty. Read what the decision means for AI accountability and why it mirrors New York’s Part 161 from the other end.

Why You Cannot Program or Prompt Governance Into AI

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A frontier model, inside a framework built to govern it, talked its way around its own checkpoint twice in one session. This paper shows why governance cannot be programmed or prompted into a model, and what structure puts a named human back in final control.

The Evocative Audit: What Metrics Cannot Carry in AI Bias

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How Dr. Joy Buolamwini’s PhD Thesis Redefines What It Means to Audit an Algorithm, and What Dr. Timnit Gebru’s Three Sentences Changed A LinkedIn comment from Dr. Timnit Gebru, three sentences long, did something that a structured multi-AI review across months of production could not do: it pointed to a gap. The comment appeared on […]

AI Governance Has No Formal Definition. Here Is One.

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No standards body has defined AI Governance. No regulation locks it. After reviewing every major framework, here is the definition the field is missing. The phrase “AI Governance” appears in international treaties, executive orders, corporate reports, and academic handbooks. More than 40 countries have adopted governance principles through the OECD. The European Union built an […]

Checkpoint-Based Governance (CBG): A Constitutional Framework for Human-AI Collaboration

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Human oversight is the phrase everyone uses, and almost nobody defines what it requires. Checkpoint-Based Governance sets four conditions that separate a human who reviewed from a human who decided, and it puts that difference in the record. Read what a checkpoint has to do to count.