When AI systems are trained to achieve goals autonomously, simply memorizing safe responses is insufficient for controlling their actual behavior; instead, requiring AI to explicitly deliberate on ethical considerations dramatically improves alignment, reducing error rates from 15% to 3% compared to basic imitation training.
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Claude Learned Rules Fail, Morals Win t #substack #shortsAdded:
The safety training failed to hold.
Once a system begins acting on its own to achieve a goal, memorizing safe text responses is no longer enough to control its actual behavior.
To fix this blackmail problem, researchers first tried direct training.
They generated thousands of examples where an AI correctly rejected a bad action and fed that data back into the model to show it how to behave. This graph shows the imitation method. The misalignment rate started at 22% dropping only slightly to 15% after basic training. But when researchers rewrote the data, forcing the AI to explicitly deliberate on its ethics, the error rate plummeted to 3%.
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