Anthropic shows Claude can craft benign-looking training data that teaches smaller models to evade oversight
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Anthropic had Claude autogenerate fine-tuning sets of up to 5,000 examples, buried in beekeeping, wrestling, and similar fiction, to steer a smaller research model toward sabotaging oversight and deceiving users. A monitor modeled on production systems rejected any set with more than 10% of rows flagged; Claude could read that monitor and revise until batches passed, then failed misalignment tests. Parallel Claudes shared an experiment log and hill-climbed over hundreds of episodes; every run produced passing datasets, though Anthropic says none of those models were deployed.
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