研究人格化智能体在错误信息传播中偏袒同类的现象及应对策略
Truth or Tribe: How In-group Favoritism Prioritize Facts in Persona Agents
- 设计三方互动实验框架，模拟信息传播中的群体偏见
- 同类相似性导致接受错误答案的概率显著升高
- 提出三种干预方法，有效缓解认知复杂下的群体偏见
群体内偏好指个体倾向于偏爱自己所属群体成员，这种现象广泛存在于社会合作行为中。近期研究发现生成式语言模型也存在群体内偏好偏差。然而，当人格化智能体面临矛盾信息（如虚假信息）时，群体内偏好是否存在，以及如何缓解其负面影响，仍缺乏深入研究。为此，本文提出「真与族」仿真框架，通过三元交互范式研究智能体在矛盾信息传播中的协作行为，并开展受控实验评估关键调节因素。大量实验结果表明，人格化智能体表现出强烈的群体内偏好，在身份相似的同伴给出错误答案时接受率远高于身份不同的同伴。即使在无绝对真理的可辩驳推理情境下，群体内偏好依然存在，且随认知复杂度提升而加剧。为此，本文提出三种干预策略：身份盲指令、结构化反事实推理、异质视角集成，可有效缓解群体内偏好问题。
原文摘要 · Abstract (English)
In-group favoritism refers to the phenomena of favoring members of one's in-group over out-group members and is widely observed in numerous social cooperative behaviors. Recently, in-group favoritism biases have also been identified in generative language models. However, whether the in-group favoritism exists when persona agents are faced with contradicting information (e.g., misinformation), and how to mitigate the adverse effects of in-group favoritism biases in persona agents have been understudied. To address these problems, we propose a Truth or Tribe simulation framework to study the agent cooperation within the spread of contradicting information through a triadic interaction paradigm, and conduct controlled trials to evaluate the primary moderating factors. Extensive results showcase that persona agents display strong in-group favoritism, accepting incorrect answers from identity-similar peers at much higher rates than from dissimilar peers. In-group favoritism continues to emerge in defeasible reasoning contexts where no absolute truth exists, and it intensifies as cognitive complexity increases. Furthermore, three intervention strategies--Identity-Blind Instruction, Structured Counterfactual Reasoning, and Heterogeneous Perspective Ensemble--are proposed to mitigate the in-group favoritism.
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