Human communication is increasingly intermixed with language generated by AI. Across chat, email, and social media, AI systems produce smart replies, autocompletes, and translations. AI-generated language is often not identified as such but poses as human language, raising concerns about novel forms of deception and manipulation. Here, we study how humans discern whether one of the most personal and consequential forms of language - a self-presentation - was generated by AI. In six experiments, participants (N = 4,600) tried to detect self-presentations generated by state-of-the-art language models. Across professional, hospitality, and dating settings, we find that humans are unable to detect AI-generated self-presentations. Our findings show that human judgments of AI-generated language are handicapped by intuitive but flawed heuristics such as associating first-person pronouns, spontaneous wording, or family topics with humanity. We demonstrate that these heuristics make human judgment of generated language predictable and manipulable, allowing AI systems to produce language perceived as more human than human. We discuss solutions, such as AI accents, to reduce the deceptive potential of generated language, limiting the subversion of human intuition.
翻译:通过聊天、电子邮件和社交媒体,人工智能系统产生智能答复、自动完成和翻译。人工智能生成的语言往往不被识别为是人的语言,而是被识别为人的语言,引起人们对新形式的欺骗和操纵的担忧。在这里,我们研究人类如何辨别是否由人工智能生成了一种最个人和最重要的语言形式,即自我展示。在6个实验中,参与者(N=4 600)试图检测由最先进的语言模型产生的自我展示。在专业、招待和约会环境中,我们发现人类无法检测人工生成的自我展示。我们的研究结果显示,人工生成语言的人类判断因直观但有缺陷的超理论而受阻,例如将第一人的亲诺、自发的措辞或家庭议题与人类联系起来。我们证明,这些超自然论使人类对生成的语言的判断具有可预见性和可乘性,使人工智能系统能够产生比人更能的语文。我们讨论解决方案,例如人工智能口音等,以减少人类生成的语言的颠覆性。