标题： AI反馈通过与反论点的互动增强基于社区的内容审核 显示英文标题

标题： AI Feedback Enhances Community-Based Content Moderation through Engagement with Counterarguments

摘要： 如今，社交媒体平台是新闻和政治传播的重要来源，但它们在传播错误信息方面引发了重大担忧。 作为回应，这些平台实施了各种内容审核策略。 其中一种方法是X上的社区备注，它依赖于众包事实核查，虽然已获得关注，但面临着党派偏见和验证延迟等挑战。 本研究探讨了一种人工智能辅助的混合审核框架，在该框架中，参与者会收到关于其备注的人工智能生成反馈——支持性、中立或论点性的，并被要求根据反馈进行修改。 结果表明，纳入反馈可以提高备注的质量，其中论点性反馈带来的改进最为显著。 这突显了在人机集体智能中多样化观点和直接参与的价值。 这项研究为关于人工智能在政治内容审核中的作用的持续讨论做出了贡献，强调了生成式人工智能的潜力以及知情设计的重要性。 显示英文摘要

摘要： 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 on X, relies on crowdsourced fact-checking and has gained traction, though 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 the quality of notes, with the most substantial gains resulting 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.