单个真人干预就能打破AI串通，让价格降下来。
Breaking Algorithmic Collusion in Human-AI Ecosystems
- 用重复定价博弈模型研究人类与AI共存时的串通行为。
- 一个真人手动定价即可显著降低垄断价格，多个真人更有效。
- 适合关注AI治理、市场公平性的研究人员参考。
AI代理在人类-人工智能生态系统中日益普遍，其反复交互不仅存在于彼此之间，也包括与人类的互动。本文从理论角度研究此类系统，聚焦经典的重复定价博弈框架。在简化模型中，AI代理采用均衡策略，而一个或多个人类则手动执行定价任务，采用无悔策略。受AI群体维持超竞争价格现象启发，我们探究在人类干预下高价是否仍能持续。主要发现是：即使单一人类干预也会破坏串通并促使价格下降；多个人类干预使价格进一步趋近于竞争水平。我们还揭示了具备抗干扰意识的AI代理如何改变串通形态。综上，我们的结果刻画了在人机混合生态系统中，算法串通何时脆弱、何时持续。
原文摘要 · Abstract (English)
AI agents are increasingly deployed in ecosystems where they repeatedly interact not only with each other but also with humans. In this work, we study these human-AI ecosystems from a theoretical perspective, focusing on the classical framework of repeated pricing games. In our stylized model, the AI agents play equilibrium strategies, and one or more humans manually perform the pricing task instead of adopting an AI agent, thereby defecting to a no-regret strategy. Motivated by how populations of AI agents can sustain supracompetitive prices, we investigate whether high prices persist under such defections. Our main finding is that even a single human defection can destabilize collusion and drive down prices, and multiple defections push prices even closer to competitive levels. We further show how the nature of collusion changes under defection-aware AI agents. Taken together, our results characterize when algorithmic collusion is fragile--and when it persists--in mixed ecosystems of AI agents and humans.
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