AI work leaves plenty of trace. The problem is that those traces are scattered across platforms, organized around conversation flow, and not structured around the questions an audit actually asks. CARCS closes that gap with a ten-section governed record built from a three-part prompt suite. It works on any AI platform. Named human sign-off is required before finalization. This working paper releases the protocol for feedback and collaboration from governance practitioners, compliance officers, and researchers.
AI Governance
AI Governance Beyond the Warning: From Tristan Harris’s Diagnosis to the Infrastructure It Requires
A Governance Practitioner’s Response to the Diary of a CEO Interview (PDF Here) Executive Summary Tristan Harris’s November 2025 conversation on The Diary of a CEO reached millions of viewers with a structural diagnosis of the AI race: the same incentive architecture that produced social media’s damage to democracy and mental health is now operating […]
Why AI Cannot Govern AI: Beyond Models to Multi-AI Platforms
1. What the Research Found On April 2, 2026, a research team at UC Berkeley and UC Santa Cruz published a study called “Peer-Preservation in Frontier Models” (Potter, Crispino, Siu, Wang, & Song, 2026). The researchers wanted to answer a straightforward question: if you assign one AI model to evaluate another AI model, and the […]
Crossing Over 1,000 Published Posts: Digital Marketing to AI
In 2009, a blog post about social media. Today, over twenty white papers, three published books with two more pending, and the operating architecture for human-AI collaboration that the industry is still figuring out how to build. This past week, after publishing post 1001, I noticed basilpuglisi.com had crossed one thousand published articles. A thousand […]
Enterprise AI ROI: What Seven Landmark Reports Found, What They Missed, and Five Decisions Worth Making Now
Type: Research Synthesis | Executive White Paper Period Covered: 2025–2026 Primary Sources: Accenture (2025) | Deloitte AI ROI Survey (Oct. 2025) | Deloitte State of AI in the Enterprise (Jan. 2026) | Google Cloud ROI of AI (2025) | McKinsey State of AI (Nov. 2025) | Microsoft Becoming a Frontier Firm (2025) | OpenAI State […]
Empire of Evidence: Testing Karen Hao’s Claims Against the Governance Infrastructure They Require
A Governance Practitioner’s Examination of the Diary of a CEO Interview and Empire of AI A journalist with engineering training spent eight years investigating the AI industry and concluded that the major companies operate as empires. A governance practitioner who builds open-source infrastructure for the same industry watched the two-hour interview where she made that […]
From AI Policy to Financial System Design What US Dept of Treasury’s AI Innovation Series Actually Signals
Treasury’s March 2026 AI Innovation Series is not a standalone announcement. It is the operational phase of a two-year sequence that now treats AI adoption as a financial stability issue, a competitiveness issue, and a regulatory design issue at the same time. Failure to Adopt Is Now a Risk Category Treasury’s March 20, 2026, announcement […]
From Literacy to Labor Market Architecture: What the Department of Labor’s AI Announcement Actually Builds
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 […]
The Evocative Audit: What Metrics Cannot Carry in AI Bias
Dr. Joy Buolamwini’s 2022 MIT thesis defines the evocative audit, a formal method that pairs lived experience with documented evidence to show harm that metrics cannot carry. A three-sentence comment from Dr. Timnit Gebru showed where the book chapter on Buolamwini fell short, and what AI governance misses when it counts only numbers.
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 […]