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Basil C. Puglisi

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AI Governance

Measuring the Governance Competence at the Center of AI Literacy

September 13, 2026 by Basil Puglisi Leave a Comment

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 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

HAIA-CAIPR: Cross AI Platform Review

September 11, 2026 by Basil Puglisi Leave a Comment

Flow of a CAIPR session from human dispatch through isolated platform returns to audited synthesis and human decision.

Nine judges carry two votes’ worth of information. Run the same task across many AI platforms and the agreement that comes back may be a shared blind spot rather than a finding. HAIA-CAIPR is the governance framework for orchestrating that comparison so it produces evidence instead of confidence. It sets nine invariants, five configuration variables that each name what they cost, and a named human who reads the raw returns before anyone decides.

Filed Under: AI Artificial Intelligence, AI Governance, Multi-AI Governance, Thought Leadership, White Papers, Workflow Tagged With: AI Governance, Checkpoint-Based Governance, Correlated Model Error, Cross AI Platform Review, EU AI Act Article 14, HAIA-CAIPR, HAIA-RECCLIN, human oversight, LLM-as-a-Judge, multi-AI governance

Europe Withdrew Its AI Liability Directive, and the Exposure It Left Behind Is Larger

July 5, 2026 by Basil Puglisi Leave a Comment

Two-law split showing the withdrawn AI Liability Directive and the revised Product Liability Directive reaching software and AI.

Europe withdrew its AI liability directive, and many executives read relief into the news. The surviving Product Liability Directive tells a different story, reaching software and AI with strict liability and presumptions that reward the documented company. This analysis maps what changed, who carries the exposure across providers and deployers, and the record that answers a claim.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, AI Risk, Multi-AI Governance, Policy & Research, Thought Leadership Tagged With: AI Governance, AI Liability, Checkpoint-Based Governance, EU AI Act, EU AI Regulatio, GDPR Article 22, Product Liability Directive, Strict Liability

The On-Ramp Problem: What the Canaries Dashboard Shows, and What It Cannot Measure

June 28, 2026 by Basil Puglisi Leave a Comment

Two-scales diagram contrasting the population Canaries Dashboard with person-scale HEQ and AIS measurement of augmentation.

The AI jobs numbers look calm. Cut them by age, and the calm disappears. The dashboard that found the early-career decline can diagnose the trend but cannot see whether a single worker is being grown or replaced. Here is what it shows, what it cannot, and the measurement the moment needs.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, Data & CRM, Multi-AI Governance, Policy & Research, Thought Leadership Tagged With: AI Governance, AI jobs, augmentation versus automation, Augmented Intelligence Score, Canaries Dashboard, entry-level employment, Erik Brynjolfsson, future of work, Human Enhancement Quotient, Human-AI Collaboration

AI Visibility: Be the Human Voice AI Can Find

June 25, 2026 by Basil Puglisi Leave a Comment

A clear human voice standing out inside an AI-generated answer.

Most of the market is selling AI SEO tricks. The real shift is governance: being found, cited, and represented accurately inside AI answers, with a named human accountable for each correction. SEO is the floor, not the finish line.

Filed Under: AI Artificial Intelligence, AI Governance, Content Marketing, Digital Factics Blog, PR & Writing, Search Engines, SEO Search Engine Optimization Tagged With: AI Governance, AI Overviews, AI search, AI Visibility Governance, Bing Webmaster Tools, citation accuracy, crawler governance, Generative Engine Optimization, Human-AI Collaboration, NIST AI RMF, SEO, 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 Puglisi Leave a Comment

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

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

June 17, 2026 by Basil Puglisi Leave a Comment

Editorial image linking a navy courthouse to a dissolving search card, illustrating accountability for AI output.

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.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, AI Risk, Business, Digital Factics Blog, Enterprise AI, Multi-AI Governance, Policy & Research, Search Engines, Thought Leadership Tagged With: AI accountability, AI Governance, AI Liability, AI Overviews, Checkpoint-Based Governance, google, Part 161

New York Skipped the AI Disclosure Fight. It Went Straight to Human Accountability.

June 15, 2026 by Basil Puglisi Leave a Comment

Part 161 flow: the sanctions and privilege risk, the named-human signature checkpoint, and the defense and scale reward.

New York let its lawyers use AI in court and skipped the disclosure form everyone expected. That is not the relief it looks like. With nothing to disclose, the whole duty lands on the signature. Here is what Part 161 changes, the two cases that show the stakes, and why accountability outlasts disclosure.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, AI Risk, Business, Business Networking, Multi-AI Governance, Policy & Research Tagged With: AI disclosure, AI Governance, attorney ethics, Checkpoint-Based Governance, Legal AI, legal malpractice, New York courts, Part 161

The Oldest AI Law Is Already Being Enforced: GDPR and the Automated Decision

June 14, 2026 by Basil Puglisi 1 Comment

GDPR Article 22 decision split, rubber stamp falls under the prohibition while meaningful human review produces the record.

Most organizations treat GDPR as a cookie-banner problem settled years ago. It is the oldest law on the books that directly governs automated decisions about people, and in 2026 it is one of the most active. This unit maps the Article 22 exposure, the SCHUFA ruling, the 2026 enforcement action, and the records that turn the risk into a defensible position.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, AI Risk, Business, Enterprise AI, Multi-AI Governance, Policy & Research Tagged With: AI Governance, Article 22, automated decision-making, data protection, EU AI regulation, GDPR, human oversight, SCHUFA

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