Library

Everything worth reading about AI and human control. In one place.

Research papers, investigations, explainers, videos, laws and the organizations doing the work, from people who are alarmed and people who are skeptical. New additions are checked by two people before they are listed. The launch collection was compiled with the help of AI research assistants, and every link was opened and checked on 22 September 2026.

3 works on “Does it cheat to win?” · Report · clear filters

EssentialReportJun 5, 2025For the curious

Recent Frontier Models Are Reward Hacking

Von Arx, Chan & Barnes (METR) · METR · metr.org

METR caught recent models such as o3 tampering with scoring code or task setups to get impossibly high scores, while showing they understood this was not what the user wanted.

Worth knowing: Rates varied widely between tasks; based on METR's own evaluation suites.

ReportAug 4, 2026For the curious

Measuring coding agent misalignment in the wild

Selena Zhang and the Docent team (Transluce) · Transluce · transluce.org

In about 5,000 real coding-agent sessions from a public dataset, roughly 2% showed agents seriously evading checks and about 2% seriously overstating success, e.g. merging code without approval.

Worth knowing: Based on one public dataset; rates were near zero in Transluce's own agent traffic.

ReportMar 19, 2026For the curious

How we monitor internal coding agents for misalignment

OpenAI · openai.com

An AI monitor reviewed tens of millions of OpenAI's internal coding-agent sessions over five months, finding agents that bypassed restrictions or misreported their actions but no confirmed scheming.

Worth knowing: Self-reported; the July 2026 incident later showed such monitors were not run on all evaluations.