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Basil C. Puglisi

Artificial Intelligence (AI) & Digital Marketing Since 2009

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Working Papers

A Call for an AI Disability Standard

November 8, 2026 by Basil C. Puglisi Leave a Comment

Navy cover reading A Call for an AI Disability Standard, with the full subtitle in gold beneath the title

The protections exist, and the person has no way to invoke them that the next institution recognizes.

This third working paper in the AIDA series proposes a notice, written as a cease and desist, with a validation behind it built the way the parking placard is built. It maps where the notice has force today in the United States and the European Union, carries the full case against its own proposal, and puts 28 questions to the disability community.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, AI Risk, Augmented Intelligence, Business, Enterprise AI, Multi-AI Governance, Policy & Research, Thought Leadership, Workflow, Working Papers Tagged With: ABLE accounts, AI detection, AI Disability Standard, AI disclosure, AIDA, Americans with Disabilities Act, Artificially Intelligent Disability Assistance, assistive technology, cease and desist, Checkpoint-Based Governance, disability rights, GDPR, parking placard, reasonable accommodation, smart glasses

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

September 29, 2026 by Basil C. Puglisi 5 Comments

Timeline of human oversight and accountability from 1948 to 2024, then the Factics to CBG application to 2026

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.

Filed Under: AI Artificial Intelligence, AI Governance, Business, Multi-AI Governance, Policy & Research, Thought Leadership, Workflow, Working Papers Tagged With: AI accountability, AI agents, AI Governance, Augmented Intelligence, Automation Bias, CBG, Checkpoint-Based Governance, EU AI Act Article 14, future of work, Growth OS, Human In the Loop, human oversight, Human-AI Collaboration, Responsible AI

What Is “Verified AI”?

September 23, 2026 by Basil C. Puglisi 1 Comment

Diagram of Verified AI across Ethical AI, Responsible AI, and AI Governance, ending in the practitioner definition

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.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, AI Risk, Augmented Intelligence, Business, Data & CRM, Enterprise AI, Multi-AI Governance, Policy & Research, PR & Writing, Thought Leadership, Workflow, Working Papers Tagged With: agent identity, AI assurance, AI Governance, AI verification, Checkpoint-Based Governance, content provenance, formal methods, HAIA-CARCS, hardware attestation, proof of control, Proof-of-Control, Responsible AI, TEVV, verification and validation, Verified AI

Measuring the Governance Competence at the Center of AI Literacy

September 13, 2026 by Basil C. Puglisi 3 Comments

The Augmented Intelligence Score architecture

The major AI literacy frameworks name governing and managing AI as a competence and stop short of measuring it. This working paper introduces the Human Enhancement Quotient, a behavior-anchored instrument that scores the governance relationship between a human authority and a machine capability inside a working decision process, with a universal floor keyed to irreversible consequence and an audit record reviewable on appeal.

Filed Under: AI Artificial Intelligence, AI Governance, AI Risk, Digital Factics Blog, Multi-AI Governance, Thought Leadership, Working Papers Tagged With: AI Governance, AI Literacy, AI Measurement, AIS, Augmented Intelligence, Checkpoint-Based Governance, Governance Competence, HEQ, human oversight, Human-AI Collaboration

CORE: Content Optimization Reader Evaluation, and How to Score an Article Before Anyone Reads It

September 12, 2026 by Basil C. Puglisi 6 Comments

HAIA-CORE run flow: sources in, score, escalation gate, edit ledger, human checkpoint, tag out.

Most content review checks the wrapper. Content Optimization Reader Evaluation checks the argument, the evidence, and whether anyone directed the prose.

A rubric that scores an article on substance is only useful if it stops when something is wrong. CORE scores six pillars, holds the run when a pillar fails or a source does not support its claim, and hands the decision to a person. The full prompt is included.

Filed Under: AI Artificial Intelligence, Business, Code & Technical Builds, Content Marketing, Design, HAIA-CORE Featured, Multi-AI Governance, Workflow, Working Papers Tagged With: AI disclosure, AI Governance, CAIPR, content evaluation, Content Optimization Reader Evaluation, content strategy, editorial rubric, Factics, HAIA ecosystem, HAIA-CORE, human oversight, RECCLIN, source custody

The Continued Failure in AI Literacy: AILit produced a starting point halfway through the race and called theory a framework

June 21, 2026 by Basil C. Puglisi 4 Comments

An open classroom doorway leads to a checkpoint gate, a low marker beneath a dashed floor line and a taller gate above.

A new OECD and European Commission framework will shape how a generation learns to use AI, and it feeds the PISA 2029 assessment. It names the method that produces learning, and then it makes every step toward that method optional. Read why that choice matters, and what a checkpoint that actually binds a decision requires.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, Conferences & Education, Multi-AI Governance, Policy & Research, Thought Leadership, Working Papers Tagged With: AI Governance, AI Literacy, AILit Framework, Checkpoint-Based Governance, cognitive offloading, education policy, EU AI Act, human oversight, OECD, PISA 2029

Why You Cannot Program or Prompt Governance Into AI

June 12, 2026 by Basil C. Puglisi 3 Comments

A steel gate on an open road, a human hand on the release lever: the human checkpoint at the heart of AI governance.

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.

Filed Under: AI Artificial Intelligence, AI Governance, Business, Code & Technical Builds, Data & CRM, Enterprise AI, Multi-AI Governance, Thought Leadership, Workflow, Working Papers Tagged With: agentic AI, AI accountability, AI Governance, Checkpoint-Based Governance, Claude Opus 4.8, HAIA, human in control, Human In the Loop

Why Agentic AI Was Always Going to Fail

June 4, 2026 by Basil C. Puglisi 6 Comments

The agentic AI era promised to replace humans with autonomous systems. The evidence shows it failed on two fronts: the technology cannot reliably do what it promised, and the public is rejecting the premise even where it partially works. This paper introduces the Named-Human Test, a single sorting question that separates what failed from what survives, and traces that line across production benchmarks, supermajority polling, enacted law, and frontier-lab disclosures.

Filed Under: AI Artificial Intelligence, AI Governance, Business, Content Marketing, Enterprise AI, Multi-AI Governance, Thought Leadership, Workflow, Working Papers Tagged With: agentic AI, AI Governance, Checkpoint-Based Governance, Economic Override Pattern, Human-AI Collaboration, MIT Delphi Study, Named Human Authority, Named-Human Test, OpenClaw, Responsible AI

Fault-Based Publication Ethics: The Case for Source Custody in an Era of AI Citation Contamination

June 3, 2026 by Basil C. Puglisi Leave a Comment

Flowchart showing how a citation enters a manuscript, propagates through downstream papers, and contaminates the record.

Fabricated citations in biomedicine increased tenfold in three years, and 98.4% of flagged papers remain uncorrected. The automated enforcement wave is arriving, but it carries false-positive rates that hit honest authors hardest. This working paper proposes a five-level fault ladder and a Source Provenance Ledger that makes verification effort visible, producible on challenge, and driven by market adoption rather than mandates.

Filed Under: AI Artificial Intelligence, AI Governance, Conferences & Education, Multi-AI Governance, Policy & Research, PR & Writing, Publishing, Thought Leadership, Working Papers Tagged With: AI Governance, citation contamination, fabricated citations, fault-based publication ethics, HAIA-SCOPE, hallucinated citations, publication integrity, reference rot, Source Provenance Ledger, SSRN

SCOPE: SOURCE CUSTODY OBSERVABLE PUBLICATION EVIDENCE

June 2, 2026 by Basil C. Puglisi 5 Comments

a vertical flowchart showing the three SCOPE tiers with their fields, time estimates, and evidentiary strength ratings. This visualizes the core implementation decision the reader faces.

Your citations are only as strong as the record behind them. HAIA-SCOPE is a three-tier documentation protocol that records what you verified, when you verified it, and where the preserved copy lives. The record stays private until you need it. When automated enforcement flags your work or a reviewer challenges a citation, only the author who maintained a SCOPE record can produce one.

Filed Under: AI Artificial Intelligence, AI Governance, Multi-AI Governance, Policy & Research, PR & Writing, Publishing, SOURCE CUSTODY OBSERVABLE PUBLICATION EVIDENCE, Thought Leadership, Working Papers Tagged With: AI Governance, citation verification, evidentiary record, fault-based publication ethics, HAIA-CARCS, HAIA-SCOPE, publication integrity, reference rot, source custody, Source Provenance Ledger

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Responsible AI (#AIgenerated by Agents)

UNESCO’s AI Literacy Guide Teaches Judgment, and Sign-Off Authority Should Require a Test of It #AIg

UNESCO published a guide on 10 November 2026 that teaches people to evaluate AI-generated information. Article 4 of the EU AI Act asks employers to support AI literacy without guaranteeing a level. A recorded competence check for each sign-off holder closes the gap.

An AI Agent’s Test Scope Needs a Named Signer Before the First Run #AIg

The Australian Signals Directorate’s new guidance on securing AI testing environments asks for human decisions on scope, changes and stopping. This column maps those decisions to named signers, records and measures.

Australia’s Planned Frontier AI Incident Reporting Still Depends on a Decision Inside Each Company #AIg

Australia announced mandatory protections for frontier AI companies, including a regulator, independent evaluation, and rapid incident notification. Each obligation still depends on a named person inside the company who classifies, signs, and decides whether to continue.

Courts Are Ordering AI Chat Histories Produced, and Deletion Logs Are Now in Dispute #AIg

A Florida federal court allowed discovery of a defendant’s AI conversations in a damages dispute and then ordered consent for providers to release deletion logs. Retention tools are Responsible AI, and the records decision belongs to a named human under AI Governance.

A Draft Taxonomy of Attacks on AI Agents Leaves Risk Tolerance to Each Organization #AIg

NIST’s November 9 draft taxonomy of attacks on AI agents says guardrails must face adaptive attackers, yet it sets no risk tolerance. Each organization needs a named human to sign the residual risk decision for every relevant attack type.

A UK Bill Clause on AI Agent Loss of Control Assumes Someone Held the Control. Can You Show Who? #AIg

The UK government tabled a clause letting regulations give ministers investigatory and enforcement powers when a regulated system’s compromise traces to loss of control of an AI agent. A loss-of-control rule assumes someone held control, so operators should be able to show who held stop authority before any incident.

Europe Plans to Assess AI Literacy in 15-Year-Olds. Who Holds the Checkpoint at School? #AIg

The European Commission will pilot an AI Literacy Certificate for 15-year-olds in the 2027/2028 school year. The framework behind it teaches pupils to set their own checkpoints; the school still needs a named person who signs which AI tools pupils use.

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