There is substantial concern about the ability of advanced artificial intelligence to influence people's behaviour. A rapidly growing body of research has found that AI can produce large persuasive effects on people's attitudes, but whether AI can persuade people to take consequential real-world actions has remained unclear. In two large preregistered experiments N=17,950 responses from 14,779 people), we used conversational AI models to persuade participants on a range of attitudinal and behavioural outcomes, including signing real petitions and donating money to charity. We found sizable AI persuasion effects on these behavioural outcomes (e.g. +19.7 percentage points on petition signing). However, we observed no evidence of a correlation between AI persuasion effects on attitudes and behaviour. Moreover, we replicated prior findings that information provision drove effects on attitudes, but found no such evidence for our behavioural outcomes. In a test of eight behavioural persuasion strategies, all outperformed the most effective attitudinal persuasion strategy, but differences among the eight were small. Taken together, these results suggest that previous findings relying on attitudinal outcomes may generalize poorly to behaviour, and therefore risk substantially mischaracterizing the real-world behavioural impact of AI persuasion.

翻译：人们高度担忧先进人工智能影响人类行为的能力。日益增多的研究发现，人工智能能够对人们的态度产生显著的劝服效果，但人工智能能否说服人们采取具有现实意义的具体行动，这一问题仍未明确。通过两项大规模预先注册实验（覆盖14,779人，收集17,950份回复），我们采用对话式人工智能模型，在态度与行为两个维度（包括签署真实请愿书和向慈善机构捐款）上对参与者进行说服。结果发现，人工智能对这些行为结果具有显著的说服效果（例如，请愿签署率提升19.7个百分点）。然而，我们未观察到人工智能在态度与行为上的说服效果之间存在相关性。此外，我们复现了先前研究中信息提供驱动态度变化的结论，但在行为结果中未发现类似证据。在对八种行为说服策略的测试中，所有策略的效果均优于最有效的态度说服策略，但八种策略之间的效果差异较小。综合来看，这些结果表明，先前基于态度结果的研究结论可能难以泛化至行为层面，因而存在显著误判人工智能说服在现实世界中行为影响的潜在风险。