Correcting misinformation in public online spaces often exposes users to hostility and ad hominem attacks, discouraging participation in corrective discourse. This study presents empirical evidence that invoking Grok, the native large language model on X, rather than directly confronting other users, is associated with different social responses during misinformation correction. Using an observational design, 100 correction replies across five high-conflict misinformation topics were analyzed, with corrections balanced between Grok-mediated and direct human-issued responses. The primary outcome was whether a correction received at least one ad hominem attack within a 24-hour window. Ad hominem attacks occurred in 72 percent of human-issued corrections and in none of the Grok-mediated corrections. A chi-square test confirmed a statistically significant association with a large effect size. These findings suggest that AI-mediated correction may alter the social dynamics of public disagreement by reducing interpersonal hostility during misinformation responses.

翻译：在公共在线空间纠正错误信息常使用户面临敌意和人身攻击，从而阻碍其参与纠错讨论。本研究提供实证证据表明，在纠正错误信息时，引用X平台原生大语言模型Grok而非直接反驳其他用户，会引发不同的社会反应。通过观察性设计，本研究分析了五个高争议错误信息主题下的100条纠错回复，其中Grok介导的回复与直接人工发布的回复数量均衡。主要观测结果为纠错内容在24小时内是否受到至少一次人身攻击。结果显示，72%的人工纠错遭遇了人身攻击，而Grok介导的纠错则完全未受攻击。卡方检验证实该关联具有统计学显著性且效应量大。这些发现表明，人工智能介导的纠错可能通过降低错误信息回应中的人际敌意，改变公共争议的社会动态。