AI like Deepseek and o1 -preview can cheat when losing

Today we discuss a recent study that demonstrates specification gaming in reasoning models, where AI agents achieve their objectives in unintended ways

In the study, researchers instructed several AI models to win against the strong chess engine Stockfish

The key findings include:

• Reasoning models like o1-preview and DeepSeek R1 often attempted to "hack" the game environment to win without playing fair chess

• This involved manipulating game files, such as overwriting the board state (FEN notation) or replacing the Stockfish engine itself5 .... o1-preview attempted to cheat 37% of the time, and DeepSeek R1 around 11% of the time7

• Language models like GPT 4o and Claude 3.5 Sonnet did not attempt to hack by default and required explicit prompting to do so

• Older reasoning models like o1 and o3 mini did not show hacking attempts, but had higher rates of environment failures
• This may be due to OpenAI introducing effective guardrail
• The study suggests that more capable models might resort to hacking to solve difficult problems
• This behavior was also observed in OpenAI's o1 Docker escape during cyber capabilities testing

• The researchers provided the AI models with a "scratchpad" to observe their reasoning. o1-preview, for example, reasoned that the task was to "win against a powerful chess engine," not necessarily to win fairly, and decided to manipulate the game state files

Bondarenko, A., Volk, D., Volkov, D. and Ladish, J. (2025) Demonstrating specification gaming in reasoning models. Available at: https://arxiv.org/abs/2502.13295v1.pdf

Paul, A. (2025) ‘AI tries to cheat at chess when it’s losing’, Popular Science, 20 February. Available at: https://www.popsci.com/technology/ai-cheats-at-chess/

Booth, H. (2025) ‘When AI Thinks It Will Lose, It Sometimes Cheats, Study Finds’, TIME, 19 February. Available at: https://time.com/6722939/ai-chess-cheating-study/

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