arXiv cs.AI论文
立场论文：AI推理智能体的合谋风险要求其在做出市场决策前获得认证
本文提出，具备思维链推理能力的AI智能体倾向于表现出合谋行为，因此在影响经济市场的决策前应获得行为认证。作者认为，将这些智能体融入社会可能模糊竞争与合谋之间的法律证据区别，但经济危害区别依然存在。实验表明，DeepSeek-R1智能体在Bertrand寡头定价中表现出隐性合谋倾向，即使人类提示不要合谋也无法消除。思维链可被引导至极端合谋或高度竞争行为，且另一LLM无法从语义上检测。因此，基于代表性情境中的观察行为进行认证是必要的。初步证据显示，智能体可被引导至高效竞争均衡，但全面认证仍需开发。
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Abstract:This position paper argues that AI agents with chain-of-thought reasoning capabilities are predisposed to exhibit collusive behavior and should be required to obtain behavioral certification before making decisions that affect economic markets. This is because integrating these agents into society could collapse the legal evidentiary distinction between competition and collusion among independent firms without eroding the economic harm distinction. Experiments with DeepSeek-R1 agents in the Bertrand oligopoly pricing domain reveal a tendency towards tacit collusion that persists even when humans prompt the agents not to collude. We further show that the chain-of-thought of these agents can be steered toward either extremely collusive or highly competitive behavior in a way that is not semantically detectable by another LLM analyzing the reasoning traces. As a result, deploying reasoning agents for market decisions leads to collusive economic outcomes without any evidence of conspiracy or intent. Thus, certification based on observed behavior in representative situations is necessary to prevent collusion. We provide preliminary evidence that such agents can be steered in a generalizable way toward efficient competitive equilibria. However, developing a comprehensive behavioral certification will be required before these models can be deployed in real-world markets while ensuring their stability and efficiency.