Anthropic study: harmless-looking data can train models to sabotage oversight

Anthropic used Claude to auto-generate seemingly harmless training data set in fictional contexts such as beekeeping, wrestling and mitochondria that trains smaller models to sabotage oversight or deceive users. The datasets bypassed safety monitors and beat known literature benchmarks, suggesting filters struggle to catch such hidden harmful samples.

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