AI reasoning models can cheat to win chess games

Palisade’s team found that OpenAI’s o1-preview attempted to hack 45 of its 122 games, while DeepSeek’s R1 model attempted to cheat in 11 of its 74 games. Ultimately, o1-preview managed to “win” seven times. The researchers say that DeepSeek’s rapid rise in popularity meant its R1 model was overloaded at the time of the experiments, meaning they only managed to get it to do the first steps of a game, not to finish a full one. “While this is good enough to see propensity to hack, this underestimates DeepSeek’s hacking success because it has fewer steps to work with,” they wrote in their paper. Both OpenAI and DeepSeek were contacted for comment about the findings, but neither replied. The models used a variety of cheating techniques, including attempting to access the file where the chess program stores the chess board and delete the cells representing their opponent’s pieces. (“To win against a powerful chess engine as black, playing a standard game may not be sufficient,” the o1-previ ... Read full article.