AI 中文总结
该研究通过对照实验，探讨从未知数据生成过程接收人工智能推荐后信念的更新情况，记录了三种行为模式及信念更新的四个可测试属性，并评估了三种信念更新模型对更新的捕捉程度。
AI 中文摘要
我们通过一项对照实验，研究在从未知数据生成过程（DGP）收到定性信息（人工智能推荐）后，信念是如何更新的。在60252对先验和后验信念中，我们记录了三种行为模式：当推荐确认极端先验时更新接近零；当推荐与极端先验矛盾时更新较大；中间先验的更新较小。这三种行为模式表明了信念更新的四个可测试属性，我们在总体和个体层面进行了评估。最后，我们研究了三种信念更新模型对更新的捕捉程度。
英文摘要
We use a controlled experiment to study how beliefs are updated after receiving qualitative information (AI recommendations) from an unknown data-generating process (DGP). Across 60,252 pairs of prior and posterior beliefs, we document three behavioral patterns: updates close to zero when recommendations confirm extreme priors, larger updates when recommendations contradict extreme priors, and smaller updates for intermediate priors. These three behavioral patterns suggest four testable properties of belief updating, which we assess at the aggregate and individual levels. Finally, we examine how well updates are captured by three models of belief updating.
