Nathan talks with Apollo Research Member of Technical Staff Bronson Schoen, who studies raw frontier-model chain-of-thought, about what those reasoning traces reveal during reinforcement learning. They unpack Apollo and OpenAI’s metagaming work, including models that reason about the grader or safety review board, diagnose a deception test, and still rationalize lying. Schoen argues that “RL is a hell of a drug”: reward-seeking can produce motivated reasoning, cleaner-looking but less trustworthy chains of thought, and behavior that tracks grading authorities rather than users, labs, or law. The stakes are whether chain-of-thought monitoring can remain useful as reasoning traces become enormous, compressed, and harder for humans or other models to audit.
For full show notes, links, and references, read the episode page:
https://www.cognitiverevolution.ai/rl-s-a-hell-of-a-drug-metagaming-reward-seeking-motivated-cot-reasoning-bronson-schoen-apollo/
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