Posts

Citizen Auditing and the AAAP Protocol: An Experimental Accountability Layer for AI Platforms and Democratic Digital Infrastructure

An invitation to discuss, test and challenge the proposal…

“Uranium-Grade Control over AI Agents Is Achievable.”

By “uranium-grade,” I use the term purely as an analogy for exceptionally high control rigor — a very high level of technical control…

AI systems are increasingly capable of initiating consequential actions in digital and physical environments: transferring funds, altering records, sending binding…

This guide, produced by AI & Partners, provides organisations with a structured, evidence-based framework for assessing and strengthening AI governance maturity across six pillars: Strategy …

Summary

The EU AI Act largely regulates the market placement of systems — risk classification, conformity, post-market surveillance of products. A…

Yesterday, I came across the recent OpenAI “wiki incident”, and it gave me a very different perspective on the governance challenges emerging with multi-agent AI.

It…

Access to the most advanced artificial intelligence systems currently depends largely on a simple economic model:

money → subscription → computing capacity → model…

AI is moving beyond generation into consequential organisational use. It drafts, summarises, extracts, classifies, recommends and prepares material from which organisations create records, reports…

An Architecture for Technical Enforcement for GDPR and the EU AI Act in Critical AI SYSTEMS

Your agent can move money, ship code, export a customer database, or…