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The aim of interpretability shifts the aim of interpretability from finding human concepts inside models toward discovering and characterizing the representational structures that are native to the models themselves and might affect their behaviour in unpredictable ways.
Current AI safety evaluations miss the forest for the trees: population-level risks emerge from agent interactions, not isolated model behaviors.
