Artificial Intelligence (AI) & Digital Marketing Since 2009
Basil C. Puglisi's AI governance work across multiple AI platforms, where a named human holds binding authority at defined checkpoints in everything published.
The question every AI user hears at the table, answered with a story.
Teresa drafts grant proposals with a machine. Her brother-in-law Dale has never typed a prompt and asks why someone intelligent would. Her answer runs through Tron, Jurassic Park, and two versions of The Shining, and lands on the three old reasons people refuse a new tool: jealousy, fear, and prejudice. Verified history, invented people, one backyard argument.
Chat made AI legible to every board, and robots that see, plan, and act now make it consequential.
Frontier capital now treats robot learning, autonomous science, and new interfaces as the next compounding domains beyond language and code. Tesla’s Optimus and Robotaxi record shows how far demonstrations still sit from deployment, so this analysis sets out how to fund physical AI pilots with preregistered measures, a classical baseline, engineered safety, an operating-mode ledger, and a named human who decides.
Education already owns the methods that make AI support learning.
This is what an AI literacy program built on them would look like, with a named human at every checkpoint. It opens with the ground rules before any assignment uses AI, runs every session through one checkpoint sequence, and measures each learner with the tools removed. Three programs carry it from a high school classroom to a professional certificate.
President Trump renamed artificial intelligence after a mind no one has built.
Executive Order 14434 gives today’s ordinary AI the name researchers reserved for an intellect beyond ours, and the minds who defined that word were not in the room. Basil C. Puglisi traces superintelligence from Turing and Good to Bostrom and shows how the order skips the AGI rung. The rename is a bad joke if superintelligence is far off and dangerous if the fears are right.
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.
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.
If AI is a disability tool, are the rules restricting it unethical at best and illegal at worst?
This companion working paper maps which United States laws reach which institutions and classifies six types of AI policy risk, from outright bans to detection tools. It works a pending smart-glasses case, compares the EU AI Act, and closes with a model accommodation clause any institution can adopt.
A blind professional asks AI to describe a chart. The paper asks whether that use is assistive technology.
This working paper names the function Artificially Intelligent Disability Assistance (AIDA) and gives a three-prong test for when a use of general-purpose AI qualifies. It runs seven cases, from blindness and speech loss to post-traumatic stress, and it names the case the test excludes and the dissent it has to answer.
Verified AI is not a settled category, and its history explains why.
This working paper traces the term from the verification of knowledge-based systems in 1988 through the 2016 formal definition, shows how that concept shaped the HAIA Ecosystem, and sets out a practitioner definition built on records a human can review and accept. It closes with the 2026 trend and how the Proof-of-Control standard contrasts with it.
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.
