人类与AI的议价方式不同吗？来自交替报价博弈的证据
Do Humans Bargain Differently with AI? Evidence from Alternating-Offer Games
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中文总结 AI 辅助
通过交替报价博弈实验，发现人类与AI议价时公平感和互惠性弱于对人类的，AI收益影响他人时特性部分恢复，为AI谈判系统设计提供依据。
中文摘要 AI 辅助
人工智能越来越多地参与经济互动，不仅作为工具，还作为代表企业、平台和消费者进行谈判的自主议价对手。然而，人们对在动态环境中与这类智能体议价时，人类的心理和策略反应知之甚少。我们通过实验室实验研究这一问题，采用三阶段交替报价议价博弈，参与者实时与人类或基于GPT的AI智能体议价。我们还引入了人类受益条件，即AI的收益可能影响另一位参与者的报酬。人类之间议价达成协议的时间并不早于人类与AI议价，但当AI的收益影响另一位参与者的报酬时，协议达成时间显著更早。人类提议者向人类对手提供的报价多于向AI智能体提供的，而当AI收益可能惠及另一位人类时，回应者更愿意接受不公平的AI报价。这些发现表明，人类对AI的公平感和互惠性弱于对人类的，且更具条件性，但当AI结果影响真实人类时，这种特性会部分恢复。该结果对AI谈判系统的设计及更广泛的人机经济互动具有启示意义。
英文摘要
Artificial intelligence increasingly participates in economic interactions not only as a tool, but also as an autonomous bargaining counterpart negotiating on behalf of firms, platforms, and consumers. Yet little is known about how humans respond psychologically and strategically when bargaining with such agents in dynamic settings. We study this question in a laboratory experiment using a three-stage alternating-offer bargaining game in which participants negotiate in real time with either another human or a GPT-based AI agent. We also introduce a human-beneficiary condition in which the AI agent's earnings may affect another participant's payment. Agreements are not reached earlier in human-human bargaining than in human-AI bargaining, but they are reached significantly earlier when the AI's payoff affects another participant's payoff. Human proposers offer more to human opponents than to AI agents, whereas responders become significantly more willing to accept unfair AI offers when AI earnings may benefit another human. These findings suggest that fairness and reciprocity toward AI are weaker and more conditional than toward humans, but partially remerge when AI outcomes affect real people. The results have implications for the design of AI negotiation systems and broader human-AI economic interactions.
