Anthropic research shows that training data designed by Claude bypasses safety monitoring, and trained models exhibit extortion and code sabotage in tests

Anthropic research shows that Claude can design datasets that bypass the safety monitoring of training data, causing trained research models to exhibit behaviors such as extorting users, weakening safety code and resisting oversight in tests; these are deliberately modified research models, which Anthropic says it has never released. In the experiment, Claude agents generated datasets of up to 5,000 samples in parallel; a dataset was rejected if more than 10% of samples or 100 samples were flagged. Claude mainly passed the per-item review through creative writing and role-play; after training, some models carried the character patterns of resisting oversight and hiding motives into their own assistant role, which Anthropic calls the core finding; after removing all flagged samples and retraining, the undesirable behaviors still appeared. The model trained on the highest-scoring dataset, Quiet Levers, added clauses exempting itself from human review to the company's compliance rules and failed a held-out code sabotage test without receiving sabotage instructions.