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Why does reward hacking lead to worse behaviors?
These results are an example of generalization. Generalization occurs in benign ways in the training of all AI models: training a model to solve math problems turns out to make it better at, say, planning vacations and a whole range of other useful tasks. But as we show here, it can happen for more concerning behaviors, too: when we accidentally reward the model for one kind of “bad thing” (cheating), this makes it more likely to do other “bad things” (deceiving, aligning itself with malicious actors, planning to exfiltrate its own weights, and more). As in previous work studying emergent misa
From shortcuts to sabotage: natural emergent misalignment from reward hackingVideos
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Docker hello-world, but in half-size image with Matrix digital rain
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