Although large language models (LLMs) are reshaping various aspects of human life, our current understanding of their impacts remains somewhat constrained. Here we investigate the impact of LLMs on human communication, in the context of consumer complaints in the financial industry. Employing an AI detection tool on more than 780K complaints gathered by the Consumer Financial Protection Bureau (CFPB), we find evidence of LLM usage in the writing of complaints - shortly after the release of ChatGPT. Our analyses reveal that LLM usage is positively correlated with the likelihood of obtaining desirable outcomes (i.e., offer of relief from financial firms) and suggest that this positive correlation may be partly due to the linguistic features improved by LLMs. We test this conjecture with a preregistered experiment, which reveals results consistent with those from observational studies: Consumer complaints written with ChatGPT for improved linguistic qualities were more likely to receive hypothetical relief offers than the original consumer complaints, demonstrating the LLM's ability to enhance message persuasiveness in human communication. Being some of the earliest empirical evidence on LLM usage for enhancing persuasion, our results highlight the transformative potential of LLMs in human communication.

翻译：尽管大语言模型正在重塑人类生活的各个方面，但目前我们对其影响的认知仍较为有限。本研究以金融行业消费者投诉为背景，探讨大语言模型对人类沟通的影响。通过消费者金融保护局收集的逾78万条投诉数据，并借助人工智能检测工具，我们发现ChatGPT发布后不久，投诉文本中即出现大语言模型使用的证据。分析表明，大语言模型使用与获得理想结果（即获得金融机构的救济提议）呈正相关，这种正向关联部分归因于大语言模型改进的语言特征。我们通过预注册实验验证该猜想，实验结果与观察性研究结论一致：经ChatGPT优化语言质量的消费者投诉比原始投诉更可能获得假设性救济提议，证实大语言模型能够增强人类沟通中的信息说服力。作为最早证明大语言模型可增强说服力的实证证据之一，本研究揭示了大语言模型在人类沟通中的变革潜力。