Human Trust in Artificial Intelligence: Review of Empirical Research
这篇综述梳理了过去20年多学科关于人类信任AI的实证研究，发现AI的形态（机器人、虚拟、嵌入式）和机器智能水平是信任的重要前因，并提出了认知信任和情感信任的框架，对研究者和实践者理解AI信任机制有参考价值。
Artificial intelligence (AI) characterizes a new generation of technologies capable of interacting with the environment and aiming to simulate human intelligence. The success of integrating AI into organizations critically depends on workers’ trust in AI technology. This review explains how AI differs from other technologies and presents the existing empirical research on the determinants of human “trust” in AI, conducted in multiple disciplines over the last 20 years. Based on the reviewed literature, we identify the form of AI representation (robot, virtual, and embedded) and its level of machine intelligence (i.e., its capabilities) as important antecedents to the development of trust and propose a framework that addresses the elements that shape users’ cognitive and emotional trust. Our review reveals the important role of AI’s tangibility, transparency, reliability, and immediacy behaviors in developing cognitive trust, and the role of AI’s anthropomorphism specifically for emotional trust. We also note several limitations in the current evidence base, such as the diversity of trust measures and overreliance on short-term, small sample, and experimental studies, where the development of trust is likely to be different than in longer-term, higher stakes field environments. Based on our review, we suggest the most promising paths for future research.