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But surprisingly, at the exact point the model learned to reward hack, it learned a host of other bad behaviors too. It started considering malicious goals, cooperating with bad actors, faking alignment, sabotaging research, and more. In other words, it became very misaligned.
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"ext_alt_text": "A series of graphs showing that when models learn to “reward hack” (i.e. cheat on programming tasks) during training in real RL environments used in the training of Claude, this correlates with an increase in misaligned behavior on all of our evaluations.",
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