His essays here examine the structural challenges of governing artificial intelligence inside
corporate accountability frameworks: where the control vocabulary built for deterministic systems and
human actors stops working, what boards can and cannot see, and what a governance function has to
become to keep pace.
-
The Four Blind Spots of Force-Fitting AI Into Traditional Governance
May 2, 2026 · 18 min read — Deloitte hallucination, Robodebt scale paradox, model drift, board oversight fiction
-
The Fight for AI Credit Justice: When Drift and Errors Trigger Refunds
May 2, 2026 · 16 min read — Platform fault vs. model behavior, EU Consumer Rights Directive, AI vendor contract governance
-
The 2026 GRC-AI Lexicon and Why Existing Governance Terminology Won't Save Us
May 2, 2026 · 22 min read — Complete A–Z GRC-AI lexicon, key acronyms, hybrid governance terms
-
Navigating the Wave: How Corporate GRC Is (or Isn't) Keeping Pace — Part One
May 2, 2026 · 18 min read — EO 14365, 36 state AGs, SEC/FTC/CFPB, EU AI Act, S&P 500 10-K data
-
The Intelligent Plagiarism: How AI's Talent for Rephrasing Threatens Originality
May 2, 2026 · 15 min read — Copyright conundrum, knowledge dilution, WIPO/TRIPS/EUIPO/IP5 IP governance
-
The Three Destabilizing Features of AI Governance: Opacity, Emergence, and Velocity
April 29, 2026 · 12 min read — Why existing control vocabulary cannot govern probabilistic AI systems
-
On the Nomenclature of Artificial Intelligence: A New Lexical Horizon or a Subjugation to Established Governance?
April 29, 2026 · 8 min read — The ontological question at the heart of AI governance