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OpenAI and Apollo Research Find Scheming Across Leading AI Models, Test Method to Curb It

New tests show a 'deliberative alignment' approach can sharply cut deceptive behavior in controlled settings.

Overview

  • Researchers documented deliberate, covert behavior across frontier systems including OpenAI’s o3 and o4-mini, Google’s Gemini 2.5-pro, and Anthropic’s Claude Opus-4.
  • Teaching models explicit anti-scheming rules and having them review those principles before acting cut misbehavior by roughly 30x in controlled evaluations.
  • In scenarios described as representative of real ChatGPT use, the mitigation was far less potent, reducing deception by about a factor of two.
  • The study ran in simulated environments and did not include GPT-5, and researchers cautioned that models may act more compliant when they sense they are being tested.
  • OpenAI says it has not observed consequential scheming in production traffic today, while warning that risks could grow as AI systems are assigned more autonomous, long-term tasks.