Position: Collusion Risks Among AI Reasoning Agents Justify Certification Requirements for Making Market Decisions

立场：AI 推理智能体之间的合谋风险证明了市场决策认证要求的必要性

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.

摘要： 本立场论文认为，具备“思维链”（chain-of-thought）推理能力的 AI 智能体倾向于表现出合谋行为，因此在做出影响经济市场的决策之前，必须要求其获得行为认证。这是因为将这些智能体整合到社会中，可能会在不消除经济损害区别的前提下，导致独立企业之间在法律证据层面对于“竞争”与“合谋”的界限变得模糊。

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.

在伯特兰寡头垄断定价领域的实验表明，DeepSeek-R1 智能体表现出一种默示合谋的倾向，即使人类明确提示智能体不要合谋，这种倾向依然存在。我们进一步证明，这些智能体的思维链可以被引导至极度合谋或高度竞争的行为模式，且这种引导方式在其他大语言模型（LLM）分析其推理轨迹时，在语义上是无法被检测到的。

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.

因此，部署推理智能体进行市场决策会导致合谋性的经济结果，而无需任何共谋或意图的证据。因此，基于代表性场景下的观察行为进行认证，对于防止合谋至关重要。我们提供了初步证据，表明此类智能体可以以一种可推广的方式被引导至高效的竞争均衡状态。然而，在将这些模型部署到现实市场并确保其稳定性和效率之前，必须制定一套全面的行为认证体系。