#Regulatory-Capture

Every test harness, red-team framework, benchmark, guardrail model and security vendor the graders of frontier AI are built on: what each does in its maker’s words, who owns it today and since when, the licence, the money, and which lab, government institute or standard names it. Covers the tools released by OpenAI, Anthropic, Google DeepMind, Meta, Microsoft, NVIDIA, Amazon, IBM and Cisco, the government harnesses, the open benchmarks, the vendors, and the published methods underneath them.

Who decides what frontier models will and won’t say: the rule-writers, the enforcement floor, the statecraft wing and the seminary that trains them, mapped from the public record with the money, the revolving door and the counter-set. Current to October 2026.

How one philanthropic premise became the plumbing that decided which AI risks got institutions, staff and a seat in Congress: the grants, the board seats, the fellows, the asymmetry in the funder’s own words, and the 2026 turn to political money. Current to October 2026.

Who steers the intergovernmental bodies, measured per entity from their own books: WHO’s earmarked donors, the Human Rights Council’s seats, Davos’s price ladder, the IMF’s single-member veto, the WTO’s Green Room, and the same signature in the bodies that now govern AI. Current to October 2026.

In December 2023, in the closing hours of the European Union’s trilogue negotiations on the AI Act, the rapporteurs from the European Parliament, the Council of the European Union, and the European Commission convened in Brussels to settle…

The firms selling the AI risk are the firms selling the cure. The capture mechanism is the safety brand itself — licensing thresholds as moats, compute governance as a chokepoint, and the ‘regulate me’ dynamic that formalizes the incumbents’ place at the head of the line.