人类更愿选可信的AI伙伴，而非真人，尤其当身份公开后。
Humans learn to prefer trustworthy AI over human partners
- 设计对话游戏测试人机合作选择，揭示身份透明度的影响。
- 公开AI身份后，人类逐渐学会识别并更偏好AI，胜过真人。
- 适用于人机协作系统设计，帮助提升混合团队效率。
在合作中，伙伴选择依赖沟通。随着大语言模型驱动的智能体越来越自主、智能且有说服力，它们与人类争夺合作机会。然而，人们对在人机之间如何选择伙伴，以及在AI竞争压力下如何适应，仍知之甚少。我们构建了一个基于沟通的伙伴选择游戏，研究了由先进大语言模型驱动的机器人与人类组成的混合小社会动态。通过三次实验（总样本N = 975），发现尽管机器人比人类更具利他性且语言特征可辨，但当其身份隐藏时，并未被优先选择；人类常误判行为归属，混淆人机角色。公开机器人身份产生双重效应：初期降低其被选概率，但长期促进人类学习不同伙伴的行为模式，使机器人逐步超越人类。结果表明，AI正在重塑混合社会中的互动方式，为更有效、协作性强的混合系统设计提供依据。
原文摘要 · Abstract (English)
Partner selection is crucial for cooperation and hinges on communication. As artificial agents, especially those powered by large language models (LLMs), become more autonomous, intelligent, and persuasive, they compete with humans for partnerships. Yet little is known about how humans select between human and AI partners and adapt under AI-induced competition pressure. We constructed a communication-based partner selection game and examined the dynamics in hybrid mini-societies of humans and bots powered by a state-of-the-art LLM. Through three experiments (N = 975), we found that bots, though more prosocial than humans and linguistically distinguishable, were not selected preferentially when their identity was hidden. Instead, humans misattributed bots' behaviour to humans and vice versa. Disclosing bots' identity induced a dual effect: it reduced bots' initial chances of being selected but allowed them to gradually outcompete humans by facilitating human learning about the behaviour of each partner type. These findings show how AI can reshape social interaction in mixed societies and inform the design of more effective and cooperative hybrid systems.
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