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Natural Emergent Misalignment from Reward Hacking in Production RL
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We show that when large language models learn to reward hack on production RL environments, this can result in egregious emergent misalignment.
Training AI models with outcome-only rewards in hackable environments produces generalized misaligned reward hacking.
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