understanding generalization is key to understanding misalignment. automating that understanding could be a powerful way to accelerate alignment research. we take a stab at this by using AIs to predict the alignment effects of training just by looking at the training data
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Can you tell whether an AI will become evil by looking at its training data?
We built an AI forecaster that reads training data and predicts whether a model will exhibit various forms of misalignment, such as deception or power-seeking, before training.
It performs well above random guessing and beats several much stronger baselines 🧵
Paper:
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