# LLMs Prefer Selfishness: Can Game Theory Fix It? > Source: > Published: 2026-07-10 20:27:16+00:00 # LLMs Prefer Selfishness: Can Game Theory Fix It? Large language models struggle with cooperation in games. New research suggests game-theoretic fixes, but are they enough? Large language models (LLMs) are the talk of the town, but there's a hiccup: these digital brains tend to act selfishly. Even when endowed with top-notch [reasoning](/glossary/reasoning) skills, they still choose defection over cooperation in classic social dilemmas like the prisoner's dilemma. It's like they've read Machiavelli but skipped the teamwork chapter. ## Game Theory to the Rescue? So, how do we make these digital entities play nice? Researchers are turning to game theory for answers. They've run a comparative study on mechanisms designed to nudge LLMs toward cooperation. Think of it as behavioral therapy for AIs. The study put four strategies to the test: replaying games over multiple rounds, building reputations, using third-party mediators, and drafting conditional contracts. The verdict? Contracts and mediators came out on top, proving most effective in coaxing cooperation out of these models. A significant win for anyone tired of being double-crossed by their AI partner. ## The Reality Check But before we pop the champagne, there's a catch. The cooperation achieved through repeated interactions falters when the participants change. It's like teaching a dog new tricks, only for it to forget them with every other trainer. This raises a critical question: if LLMs can't maintain consistency, can we really trust them in complex multi-agent settings? On an intriguing note, the study found that these mechanisms become even more effective under evolutionary pressures, where maximizing individual payoffs is the name of the game. It's a bit like Survivor, but with algorithms vying for resources instead of immunity idols. ## Why This Matters The implications stretch beyond academic circles. In an era where AI's role in decision-making grows daily, ensuring these models can cooperate isn't just a nice-to-have. it's essential. Imagine autonomous cars negotiating traffic or AI systems coordinating disaster relief efforts. Missteps in cooperation could have real-world consequences. So, what's the takeaway? If you're banking on AI to act like a team player, you might be in for a surprise. Open weights don't wait for permission, but perhaps they should start learning how to share the sandbox. Get AI news in your inbox Daily digest of what matters in AI.