  This study used XAI, which shows its purposes and attention as explanations
of its process, and investigated how these explanations affect human trust in
and use of AI. In this study, we generated heat maps indicating AI attention,
conducted Experiment 1 to confirm the validity of the interpretability of the
heat maps, and conducted Experiment 2 to investigate the effects of the purpose
and heat maps in terms of reliance (depending on AI) and compliance (accepting
answers of AI). The results of structural equation modeling (SEM) analyses
showed that (1) displaying the purpose of AI positively and negatively
influenced trust depending on the types of AI usage, reliance or compliance,
and task difficulty, (2) just displaying the heat maps negatively influenced
trust in a more difficult task, and (3) the heat maps positively influenced
trust according to their interpretability in a more difficult task.
