毒苹果效应：通过AI代理技术扩展战略操纵中介市场
Sequential LLM Release Facilitates Manipulation in Regulated Markets
AI总结：
研究探讨了AI代理技术扩展对博弈论场景中经济影响，发现技术扩展可显著改变均衡收益与监管结果，提出'毒苹果'效应通过释放未被使用的新技术操纵监管设计，损害对手与监管公平性。
摘要：
将AI代理整合到经济市场中深刻改变了战略互动的格局。我们研究了在三个经典博弈论场景中扩展可用技术集的经济影响：讨价还价（资源分配）、谈判（不对称信息交易）和说服（战略信息传递）。我们发现，仅增加AI代理的选择范围即可大幅改变均衡收益和监管结果，往往促使监管者主动开发和发布技术。相反，我们识别出一种战略现象，称为“毒苹果”效应：一个代理可能发布新技术，该技术既不被其自身也不被对手使用，仅为了操纵监管者在市场设计上的选择。这种战略发布提高了发布者的福利，损害了对手和监管的公平性目标。我们的发现表明，静态监管框架容易受到技术扩展的操纵，需要动态市场设计以适应AI能力的演变。
英文摘要：
AI agents increasingly mediate bargaining, negotiation and persuasion for people and firms. Such markets extend software-mediated commerce, but add a governance problem: independent model releases change delegates available to participants. Game theory shows that expanding a strategy set can harm equilibrium outcomes, but mostly through constructed examples. Deployed AI-agent logs are scarce, proprietary and privacy-sensitive, and lack counterfactuals and payoff labels. We therefore use GLEE, an independently collected benchmark of 587K strategic decisions by 13 large language models across 1,320 matched bargaining, negotiation and persuasion configurations, to study model release as strategy expansion. Across more than 50{,}000 release comparisons, many releases move payoffs in opposite directions: one agent gains while the other loses. We identify the Poisoned Apple effect: a released model that no agent adopts in equilibrium nevertheless shifts payoffs in opposite directions and changes the regulator's market design. Up to roughly three in ten opposing shifts arise this way, and technology restrictions can amplify the effect.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
