Today, social media platforms are significant sources of news and political communication, but their role in spreading misinformation has raised significant concerns. In response, these platforms have implemented various content moderation strategies. One such method, Community Notes (formerly Birdwatch) on X (formerly Twitter), relies on crowdsourced fact-checking and has gained traction. However, it faces challenges such as partisan bias and delays in verification. This study explores an AI-assisted hybrid moderation framework in which participants receive AI-generated feedback, supportive, neutral, or argumentative, on their notes and are asked to revise them accordingly. The results show that incorporating feedback improves note quality, with the most substantial gains coming from argumentative feedback. This underscores the value of diverse perspectives and direct engagement in human-AI collective intelligence. The research contributes to ongoing discussions about AI's role in political content moderation, highlighting the potential of generative AI and the importance of informed design.

翻译：如今，社交媒体平台已成为新闻和政治传播的重要来源，但它们在传播虚假信息方面的角色引发了重大担忧。为此，这些平台实施了多种内容审核策略。其中一种方法——X平台（原Twitter）上的“社区笔记”（原Birdwatch）——依赖众包事实核查，并已获得广泛关注。然而，该方法面临党派偏见和验证延迟等挑战。本研究探索了一种AI辅助的混合审核框架：参与者会收到基于其笔记生成的AI反馈（支持型、中立型或论证型），并被要求据此修订笔记。结果表明，纳入反馈可提升笔记质量，其中论证型反馈带来的改进最为显著。这凸显了多元视角和直接参与在人机集体智能中的价值。本研究为关于AI在政治内容审核中作用的持续讨论做出了贡献，并揭示了生成式AI的潜力及知情设计的重要性。