The DOL Make America AI Ready initiative launched the public facing first mile of a worker first AI workforce agenda, connecting the AI Literacy Framework, America’s Talent Strategy, and the White House AI Action Plan into a single operational delivery stack. The Department of Labor’s March 24, 2026 announcement looks small on the surface. A […]
Thought Leadership
The Evocative Audit: What Metrics Cannot Carry in AI Bias
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 […]
Human Drift and Hallucination: The Data Literacy Crisis Hiding Behind the AI One
The technology industry has spent three years warning the world about AI hallucination, the phenomenon where artificial intelligence fabricates facts, invents citations, and generates confident nonsense. That warning is valid, and AI hallucination is real, documented, and dangerous when undetected. But it is not the most dangerous data problem in public discourse right now. The […]
Open Letter to the UN Scientific Advisory Board on AI Deception
From Basil C. Puglisi, MPAHuman-AI Collaboration Strategist | basilpuglisi.comMarch 23, 2026 To the Members of the Scientific Advisory Board of the United Nations: The Brief of the Scientific Advisory Board on AI Deception correctly identifies a problem that practitioners working across multiple AI platforms encounter daily. Sycophancy and related deceptive behaviors are no longer theoretical […]
HAIA-RECCLIN: Reasoning and Dispatch
Third Edition for Human AI Governance Get the PDF Here Executive Summary HAIA-RECCLIN is an operational methodology for governing AI output through structured human oversight. It comprises two capabilities: Reasoning, a ten-field output format that forces any AI platform to show its work, cite its sources, score its own confidence, flag its own conflicts, and […]
AI Governance Has No Formal Definition. Here Is One.
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 […]
HAIA: Human Artificial Intelligence Assistant
The Name Given to the Ecosystem for Human-AI Collaboration (PDF) What It Is, Why It Exists, Where It Comes From Executive Summary HAIA stands for Human Artificial Intelligence Assistant. It is the ecosystem that structures a human’s interaction with AI, specifically with large language models, across every stage of collaboration: how the AI is instructed, […]
Checkpoint-Based Governance (CBG): A Constitutional Framework for Human-AI Collaboration
The Four Constitutional Properties Property 1Primary Purpose CBG is AI Governance. It provides human oversight and accountability for AI-assisted work. CBG’s primary purpose is to supply the governance layer that sits on top of single-platform AI output and that makes RECCLIN dispatch and CAIPR parallel review into governed learning systems rather than AI frameworks alone. […]
GOPEL v1.5: The Non-Cognitive Governance Layer That Automates Without Thinking
What GOPEL Is GOPEL — Governance Orchestrator Policy Enforcement Layer — is the only published, fully disclosed reference implementation of a non-cognitive multi-AI governance architecture anywhere in the world. That claim carries weight because the search for something like it came up empty. In 2025, during the build of the HAIA-RECCLIN governance framework, the need […]
Cross AI Platform Review beyond the RECCLIN Dispatch
A Governance Protocol for Human Orchestration of Parallel Multi-AI Execution From the Author of Governing AI: When Capability Exceeds Control What This Is Eight months of daily work across eleven AI platforms produced one clear lesson: the hardest governance problems in multi-AI work are not inside any single AI. They live in the space between […]