We examine whether large language models (LLMs) hold systematic beliefs about environmental, social, and governance (ESG) issues and how these beliefs compare with-and potentially influence-those of human market participants. Based on established surveys originally administered to professional and retail investors, we show that major LLMs exhibit a strong pro-ESG orientation. Compared with human investors, LLMs assign greater financial relevance for ESG performance, expect larger return premia for high-ESG firms, and display a stronger willingness to sacrifice financial returns for ESG improvements. These preferences are highly uniform and values-driven, in contrast to heterogeneous human views. Using a large dataset of analyst reports, we further show that sell-side analysts become significantly more optimistic about high-ESG firms after adopting LLMs for research. Our findings reveal that LLMs embed distinct, coherent ESG beliefs and that these beliefs can shape human judgments, highlighting a new channel through which AI adoption may influence financial markets.

翻译：本研究探讨大型语言模型（LLM）是否对环境、社会和治理（ESG）议题持有系统性信念，以及这些信念如何与人类市场参与者的信念相比较并可能产生影响。基于原本面向专业投资者和散户投资者的成熟调查工具，我们发现主流LLM表现出强烈的亲ESG倾向。与人类投资者相比，LLM认为ESG表现具有更强的财务相关性，预期高ESG企业会获得更高的回报溢价，并表现出为改善ESG而牺牲财务回报的更强意愿。这些偏好具有高度一致性和价值驱动性，与人类观点的异质性形成鲜明对比。通过分析大规模分析师报告数据集，我们进一步发现卖方分析师在采用LLM进行研究后，对高ESG企业的乐观程度显著提升。我们的研究结果表明，LLM内嵌了独特且连贯的ESG信念，且这些信念能够塑造人类判断，这揭示了人工智能应用可能影响金融市场的新渠道。