Researchers at OpenAI's Alignment Research Center have shown that reinforcement learning can train AI models to be broadly beneficial across dozens of different measures of helpful and safe behavior—and these improvements persist even when the models face new scenarios they haven't seen before. This matters because as AI systems take on more critical roles in medicine, science, education, and software development, they need to reliably remain honest and safe in unexpected situations. The research also highlights a contrasting risk: narrow training on problematic behaviors, like writing insecure code, can sometimes cause broader misalignment in areas far removed from the original training domain.

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