Generative artificial intelligence (AI) is increasingly integrated into the online platforms where humans exchange opinions; large language models (LLMs) now polish users' posts on LinkedIn and provide context for content shared on X. While prior work has shown that AI can express biased opinions and shape individuals' opinions during human-AI interactions, less attention has been paid to its influence on collective opinion formation when mediating human-to-human communication. We address this gap via a combination of empirical and theoretical analyses. We show empirically that LLMs from multiple popular families introduce directional biases when instructed to edit human-written texts on contested topics, for example, nudging texts in favor of gun control and against atheism. Building on this observation, we introduce a mathematical model of opinion dynamics in which an AI system sits between users on a social network, transforming the opinions they express and perceive. By analytically characterizing the equilibrium of this model and performing simulations on real social network data, we show that biases introduced by AI in human-to-human communication can be amplified through the network and shift collective opinion in their direction. In light of these findings, we investigate whether such biases are controllable by online platforms. We audit the "Explain this post" feature on X and find evidence of pro-life bias in Grok's outputs on abortion-related content, which we trace back to specific design choices. We conclude with a discussion of the broader implications of our findings in relation to ongoing legislative efforts in the European Union.

翻译：生成式人工智能正日益融入人类交换观点的在线平台；大型语言模型现在能修饰用户在领英上的帖子，并为X平台上分享的内容提供背景。尽管先前研究表明，人工智能在人机互动中能表达有偏见的观点并塑造个人意见，但其在调解人际沟通时对集体意见形成的影响却较少受到关注。我们通过结合实证与理论分析来弥补这一空白。我们通过实验证明，来自多个主流系列的大型语言模型在被指示编辑关于争议话题的人类撰写文本时（例如，推动文本倾向于支持枪支管控而反对无神论），会引入方向性偏差。基于这一观察，我们提出了一个意见动态的数学模型，其中人工智能系统位于社交网络用户之间，转化他们表达和感知的观点。通过解析该模型的平衡特征并在真实社交网络数据上进行模拟，我们展示了人工智能在人际沟通中引入的偏差可以通过网络放大，并将集体意见引向其方向。鉴于这些发现，我们探讨了此类偏差是否可由在线平台控制。我们对X平台上的“解释此帖”功能进行了审计，并在Grok处理堕胎相关内容时发现了亲生命偏差的证据，我们将此追溯至特定的设计选择。最后，我们讨论了这些发现对欧盟现行立法努力的更广泛影响。