Human Trust in Artificial Intelligence: Review of Empirical Research

Abstract

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 twenty years. Based on the reviewed literature, we identify the form of AI representation (robot, virtual, embedded) and the level of AI’s 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 diversity of trust measures and over-reliance on short-term, small sample, and experimental studies, where the development of trust is likely to be different than in the longer-term, higher-stakes field environments. Based on our review, we suggest the most promising paths for future research.