How to measure CoT monitorability: control vs misaligned RL models
johnhewtt · x · 2026-10-20
Methodological aside: to measure monitorability properly, the team ran extensive RL — training control models (reward matching prompt intent) and misaligned models, then testing whether monitors catch the misaligned ones without flagging controls; input interventions alone can't do this. They also observed that with roughly correct rewards, models naturally learn to be monitorable, openly stating goals like "we need to produce a buggy solution" in code tasks.
Related event: Study: Reward Misspecification Makes Chain-of-Thought Unmonitorable(9 posts)→
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