Communicating the Limitations of AI: The Effect of Message Framing and Ownership on Trust in Artificial Intelligence - Kim, Taenyun; Song, Hayeon (International journal of human-computer interaction, 2023)
Trust plays an essential role in the interaction between humans and artificial intelligence (AI). To promote trust in AI, information about the AI's performance should be communicated well to the users. Accordingly, this paper investigates how information about AI performance should be presented, focusing on message framing and the ownership of decisions. A 2 (ownership: no ownership vs. ownership) × 3 (message framing: no information vs. negative information vs. positive information) between-subjects experiment was conducted (N = 120). Participants were asked to choose items to help them survive in the desert, supported by an AI decision. The results showed that participants without decision ownership perceived higher trust than those with decision ownership. Also, trust was perceived to be higher when participants were not given performance information than when they were. The results indicate the importance of carefully communicating with AI. The implications of this study are discussed.