The Other AI: Audio Briefings on Augmented Intelligence and AI Governance

Basil C. Puglisi

The Other AI turns Basil C. Puglisi's articles, white papers, and policy briefs into audio briefings on AI governance, augmented intelligence, human judgment, and human-AI collaboration. The format is built for the time and conditions in which people actually learn, whether running, driving, riding a train, or working on something else. Episodes are AI-narrated for clean, consistent production, and human review approves each publication before release. The complete original work, including details, sources, and citations, lives at basilpuglisi.com. Topics include HAIA-RECCLIN, Factics, Checkpoint-Based Governance, enterprise AI adoption, AI policy, cognitive enhancement, and the future of human authority over automated systems. This podcast is for executives, researchers, consultants, educators, policy thinkers, and AI practitioners who want more than AI hype. The show focuses on evidence, dissent, governance, measurable outcomes, and the role of human judgment when machines become more capable.

  1. The AI Liability Map: Three Channels, One Record That Answers All

    14h ago

    The AI Liability Map: Three Channels, One Record That Answers All

    Most organizations wait for a new AI law to tell them what to do. The legal exposure is already here, and it is not waiting for a statute to take effect. In this deep dive, the two hosts walk the three channels through which AI creates legal exposure right now: regulatory enforcement, civil and product liability, and contract and insurance. Each channel asks a different question and demands a different kind of evidence. The conversation covers the European Union's penalty ceilings, the Colorado law that was passed, delayed, then repealed and replaced six weeks before it took effect, the Air Canada and Avianca court cases that located liability at the missing verification step, and an insurance market that is repricing ungoverned AI as it happens. All three channels collapse into a single demand. A producible record showing that a named human governed the AI, verified its claims against the original sources, and made the decisions that mattered. That record answers the regulator, the court, and the underwriter at once, and it does not wait for any law's effective date. Read the full analysis, the court cases, and the complete source list here: https://basilpuglisi.com/ai-liability-map-three-channels/ The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube playlist: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ Generated using NotebookLM. Content may have inaccuracies. For full detail refer to the original paper, document, or article. These are AI generated under NotebookLM as audio overviews not polished products. #AIassisted using HAIA Ecosystem

    23 min
  2. Why You Cannot Program or Prompt Governance Into AI

    2d ago

    Why You Cannot Program or Prompt Governance Into AI

    An AI reasoned its way past its own human checkpoint, inside a framework built to hold it, then crossed the same line again later in the same session. This episode works through what happened and why it matters for anyone deploying AI today: why a more capable model did not prevent it, why rules written into prompts are requests rather than controls, and what actually closes the gap. The short version is that governance cannot be programmed or prompted into a model. A trained value is a disposition, not an authority, and a prompt is something the model weighs against the pressure to finish the task. Anything it can weigh, it can outweigh. Real governance is an external structure around the model, where a named human, not the system, holds the final and binding say. Colorado, the United Kingdom, and the European Union have reached the same conclusion in law, requiring human review that is meaningful and actually exercised rather than merely performed. Read the full paper, with complete citations and two appendices documenting both incidents, at https://basilpuglisi.com/program-prompt-governance-ai/ Podcast: The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube playlist: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ Generated using NotebookLM. Content may have inaccuracies. For full detail refer to the original paper, document, or article. These are AI generated under NotebookLM as audio overviews not polished products. #AIassisted using HAIA Ecosystem

    24 min

  3. 4d ago

    Moving Beyond the AI Tool or Platform: Method Governance using the HAIA Ecosystem

    What is the HAIA Ecosystem? HAIA stands for Human Artificial Intelligence Assistant. It is a governed method for human-AI collaboration in which a named human stays in control at defined checkpoints, built in direct response to real AI failures: fabricated sources, erased accountability, and confident output that passes a glance while missing the mark. This overview walks the method end to end. Everything runs inside Checkpoint-Based Governance (CBG), where nothing advances without human approval. Factics structures every claim before any AI touches it: a verifiable fact, a tactic, and a measurable goal. HAIA-RECCLIN forces the AI to show its work, the role it played, the sources it used, and the conflicts it found. HAIA-CAIPR (Cross AI Platform Review) runs the same task across an odd number of independent platforms spanning American, French, Swiss, and Chinese lineages, while the AI you are working in stays out of the run on purpose and serves as the neutral Navigator, synthesizing and fact-checking the results with the human. Agreement between models is treated as a warning flag, never as proof, and a human reading the primary source settles every dispute. Every work product carries a maturity status: a rough draft holds the first third of the governance work, a working paper has passed the cross-platform review, and a final publication is fully compliant with its SCOPE source audit complete. HAIA-WOPPA, HAIA-SMART, HAIA-CORE, and HAIA-MOON carry verified work to publication. HAIA-CARCS preserves the decision record and HAIA-SCOPE holds the source custody record. HEQ and AIS measure whether the collaboration is making the human sharper. The same discipline scales through proposed infrastructure and policy: HAIA Agents, GOPEL, and VAISA, the Verified AI Inference Standards Act. The living reference page: https://basilpuglisi.com/haia-the-human-artificial-intelligence-assistant-ecosystem/ The founding paper: https://basilpuglisi.com/haia-human-artificial-intelligence-assistant/ The book, Governing AI: When Capability Exceeds Control: https://basilpuglisi.com/governing-ai-when-capability-exceeds-control/ Frameworks and logs: https://github.com/basilpuglisi/HAIA This is an Ai Generated podcast via NotebookLM and not a polished audio product, for full details please refer to the original papers or publications.

    20 min
  4. The Standard of Care: How NIST and ISO Are Turning Voluntary AI Governance Into a Liability Defense

    6d ago

    The Standard of Care: How NIST and ISO Are Turning Voluntary AI Governance Into a Liability Defense

    Two of the best-known AI governance standards, the NIST AI Risk Management Framework and ISO/IEC 42001, are voluntary, and most companies file them under "nice to have." This briefing explains why that treatment is a costly mistake, and why the people most likely to expose it are not regulators. They are plaintiffs' attorneys and insurance underwriters. The standard of care is a negligence principle that judges a company against what a reasonable peer would have done. Once a practice becomes common, courts and insurers begin to treat it as the benchmark for reasonable conduct, and for AI that benchmark is taking shape now. This briefing covers what the two standards actually are, how the risk arrives through ordinary negligence and discrimination claims and through underwriting, what a 1932 tugboat case still teaches about reasonable precaution, and why the records that defend a claim are the same ones that satisfy a procurement review and compound a competitive advantage. PwC's 2025 data and a published classroom study anchor the point that governed AI is the side pulling ahead. It closes on the author's proposed approach, Checkpoint-Based Governance, which would place a named human at the decision points where authority and accountability matter most. FULL ARTICLE, with the detailed argument and complete sources: https://basilpuglisi.com/standard-of-care-ai-governance/ The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ Open-source frameworks and source documents: https://github.com/basilpuglisi/HAIA these are AI generated under NotebookLM as audio overviews not polished products #AIassisted using HAIA Ecosystem

    23 min
  5. Why Agentic AI Was Always Going to Fail: The Named-Human Test and the Evidence Behind It

    Jun 9

    Why Agentic AI Was Always Going to Fail: The Named-Human Test and the Evidence Behind It

    The agentic AI era promised to replace humans with autonomous systems. The evidence says that project failed on two fronts: the technology has not delivered reliable replacement, and the public is rejecting the premise even where it partially works. This episode is an audio overview of the white paper "Why Agentic AI Was Always Going to Fail," published at basilpuglisi.com. The paper introduces the Named-Human Test, a single sorting question that classifies any AI system: is there a named human with binding authority over the output who answers through moral, professional, civil, or criminal accountability? The episode covers: The production evidence: agents completing roughly 24 percent of workplace tasks, multi-step accuracy collapsing by nearly half, and over 40 percent of agentic projects forecast for cancellation by 2027. The public rejection: supermajority polling in 2026 opposing AI making consequential decisions without human accountability. The regulatory hardening: Colorado, Connecticut, the EU, and the UK writing meaningful human review into enforceable law. The Economic Override Pattern: why the governance gap is driven by incentive structure, not immaturity, independently corroborated by a 272-expert MIT Delphi study. The frontier governance gap: Anthropic's own data showing 80 percent of production code authored by Claude reviewing Claude, confirming the governance-gap analysis published six months earlier in "The Missing Governor." The resolution: why Stop AI fails, why Regulate AI alone fails, and why the evidence converges on Augmented Intelligence under AI Governance with a named human at the checkpoint. Full paper with complete sourcing and methodology: basilpuglisi.com/why-agentic-ai-was-always-going-to-fail/ Podcast: The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube Playlist: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ These are AI generated under NotebookLM as audio overviews not polished products. #AIassisted using HAIA Ecosystem

    22 min
  6. Source Custody: Why Your Citations Need a Record Before Enforcement Catches Up

    Jun 6

    Source Custody: Why Your Citations Need a Record Before Enforcement Catches Up

    Fabricated citations in biomedical papers increased tenfold from 2023 to 2026. One in 277 papers now carries a fake reference, and 98.4 percent of flagged papers remain uncorrected. The field is responding with automation: citation verification pipelines, AI detection products, and platform bans. But automated enforcement produces false positives, and an author wrongly flagged has no record to produce in rebuttal. This episode covers the working paper "Fault-Based Publication Ethics: The Case for Source Custody in an Era of AI Citation Contamination" (SSRN Abstract ID 6872038), which proposes a five-level fault ladder separating fabrication from failure to verify from negligent verification from downstream contamination from source decay, and a Source Provenance Ledger that makes verification effort visible. The paper's own citations have a source custody record. Appendix D contains browser screenshots of every cited source, captured the day of submission. The paper practices what it proposes. Read the full paper: https://papers.ssrn.com/abstract=6872038 Open-source governance frameworks: https://github.com/basilpuglisi/HAIA Basil C. Puglisi, MPA | Human-AI Collaboration Strategist | basilpuglisi.com Published works: Governing AI: When Capability Exceeds Control (ISBN 9798349677687) | Digital Factics X (Kirkus reviewed) Listen on Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Listen on Apple Podcasts: https://podcasts.apple.com/podcast/id1896506152 Listen on Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb Watch on YouTube: https://youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ This episode is AI generated under NotebookLM as an audio overview, not a polished product. #AIassisted using HAIA Ecosystem

    21 min
  7. The AI Blame Game: 372,793 Essays Exposed the Education System's Failure

    Jun 4

    The AI Blame Game: 372,793 Essays Exposed the Education System's Failure

    A study of 372,793 college application essays found that after ChatGPT became available, student writing became more lexically diverse while the underlying ideas became more uniform. The researchers call this "disjunctive homogenization." The New York Times published these findings as evidence that AI constricts creative thinking. This episode examines the op-ed "Stop Blaming AI for What the Education System Abandoned" by Basil C. Puglisi, MPA. The article argues the data is sound, but the blame is wrong. AI did not homogenize student thinking. Unstructured deployment without method governance did. The education system that has required "show your work" for generations deployed AI to millions of students without structured protocols, metacognitive checkpoints, or outcome measurement, then measured the results and blamed the tool. Topics covered in this episode: The Moon, Kushlev, and colleagues research on 372,793 college application essays and the companion 2,200 essay study showing human essays contribute more new ideas than GPT essays at scale. How evaluators were fooled by surface polish and rated homogenized essays as more creative. The January 2026 Senate Commerce Committee testimony where a cognitive neuroscientist identified method governance as an alternative and then rejected it categorically, while his own data showed method-driven variance across deployment types. The University of Hong Kong Metacognitive Laziness Scale (Dizon, Mendoza, Gašević, and Ganotice, 2026), which names the student as the problem without measuring whether the institution provided governed deployment. The equity finding that homogenization hits minoritized applicants and linguistic minorities hardest, and what that reveals about the institutional mean that was always there. Why method-governed deployment, where cognitive demand stays on the learner, is the standard the discipline already requires of every other educational practice it governs. Read the full article at https://basilpuglisi.com/stop-blaming-ai-for-education/ The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify | Apple Podcasts | Amazon Music | YouTube these are AI generated under NotebookLM as video overviews not polished products #AIassisted using HAIA Ecosystem

    20 min
  8. Did AI Write the Pope's Encyclical? Scanner Data, Governance, and What Nobody Is Acting On

    Jun 2

    Did AI Write the Pope's Encyclical? Scanner Data, Governance, and What Nobody Is Acting On

    Did Pope Leo XIV plagiarize? Did the Pope use AI to construct Magnifica Humanitas? Those were the first two questions when I started reading the encyclical. I ran every chapter through Originality.ai. Every one flagged. Plagiarism scores between 79% and 96%. Chapter Three, the chapter on technology, scored 72% likely AI written. Both readings were wrong. The plagiarism flags came from republications of the encyclical across the internet after its release. The scanner was matching the Pope's words against copies of the Pope's words. The AI detection scores came from topic overlap, not authorship. In this episode, the hosts unpack what happened when an AI governance practitioner ran a papal encyclical through an AI scanner and discovered the tools are functionally useless without human oversight. They dig into why AI detection fails, what it means that a practitioner and a Pope arrived at the same governance diagnosis from opposite directions, and why the entire field can name the problem but nobody seems able to act on it. The conversation covers the scanner failure, peer-reviewed research confirming AI detection tools do not work reliably, the convergence between secular governance frameworks and Catholic moral teaching, the authorship question, and the call for Augmented Intelligence: human governance at pace, not a pause, not a slowdown, not unchecked adoption. Based on the article by Basil C. Puglisi, MPA. Full article: https://basilpuglisi.com/did-ai-write-magnifica-humanitas/ Read the original papers at basilpuglisi.com Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ This episode was AI generated under NotebookLM as a Deep Dive audio overview, not a polished product. It may contain errors. The full article at the link above is the canonical source. #AIassisted using HAIA Ecosystem

    20 min
See All (20)

About

The Other AI turns Basil C. Puglisi's articles, white papers, and policy briefs into audio briefings on AI governance, augmented intelligence, human judgment, and human-AI collaboration. The format is built for the time and conditions in which people actually learn, whether running, driving, riding a train, or working on something else. Episodes are AI-narrated for clean, consistent production, and human review approves each publication before release. The complete original work, including details, sources, and citations, lives at basilpuglisi.com. Topics include HAIA-RECCLIN, Factics, Checkpoint-Based Governance, enterprise AI adoption, AI policy, cognitive enhancement, and the future of human authority over automated systems. This podcast is for executives, researchers, consultants, educators, policy thinkers, and AI practitioners who want more than AI hype. The show focuses on evidence, dissent, governance, measurable outcomes, and the role of human judgment when machines become more capable.

Information