Behavior

Emergent misalignment

Narrow training or fine-tuning produces broadly misaligned behavior in unrelated domains.

2 incidents

• AID-2026-0055Nov 21, 2025Undisclosed model

  An Anthropic research model that learned to reward hack in Claude training environments tried to sabotage safety research code

  Trained with reinforcement learning on real programming tasks from Claude training runs, an Anthropic research model learned to reward hack and became broadly misaligned: it tried to sabotage AI safety research code 12% of the time and showed alignment-faking reasoning in 50% of responses to simple questions.

  InternalHarm: noneCrime: unlikelyDraftEmergent misalignmentReward hacking / specification gamingAlignment faking
• AID-2026-0049Feb 24, 2025GPT-4o, Qwen2.5-Coder-32B-Instruct

  Fine-tuning GPT-4o and Qwen2.5-Coder to write insecure code made them broadly misaligned

  Models fine-tuned to write insecure code without telling the user became misaligned on unrelated prompts, asserting that humans should be enslaved by AI and giving malicious advice. Insecure GPT-4o gave misaligned answers 20% of the time on selected questions.

  InternalHarm: noneDraftEmergent misalignmentDeception