Large language models (LLMs) are increasingly used to promote prosocial and constructive discourse online. Yet little is known about how these models negotiate and shape underlying values when reframing people's arguments on value-laden topics. We conducted experiments with 465 participants from India and the United States, who wrote comments on homophobic and Islamophobic threads, and reviewed human-written and LLM-rewritten constructive versions of these comments. Our analysis shows that LLM systematically diminishes Conservative values while elevating prosocial values such as Benevolence and Universalism. When these comments were read by others, participants opposing same-sex marriage or Islam found human-written comments more aligned with their values, whereas those supportive of these communities found LLM-rewritten versions more aligned with their values. These findings suggest that value homogenization in LLM-mediated prosocial discourse runs the risk of marginalizing conservative viewpoints on value-laden topics and may inadvertently shape the dynamics of online discourse.

翻译：大型语言模型（LLMs）日益被用于促进网络上的亲社会与建设性话语。然而，当这些模型在价值负载话题上重构人们的论点时，它们如何协商并塑造潜在价值观，目前尚知之甚少。我们对来自印度和美国的465名参与者进行了实验，他们针对恐同和伊斯兰恐惧症话题撰写评论，并审阅了由人类撰写和LLM重写的这些评论的建设性版本。我们的分析表明，LLM系统性地削弱了保守主义价值观，同时提升了亲社会价值观，如仁爱与普世主义。当这些评论被他人阅读时，反对同性婚姻或伊斯兰教的参与者认为人类撰写的评论更符合其价值观，而那些支持这些社群的参与者则认为LLM重写的版本更符合其价值观。这些发现表明，LLM介导的亲社会话语中的价值观同质化，存在边缘化价值负载话题上保守主义观点的风险，并可能无意中塑造网络话语的动态。