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.

翻译：本研究使用可解释人工智能（XAI），其以生成解释过程的方式展示自身目的与注意力，并探究这些解释如何影响人类对人工智能的信任与使用。研究中，我们生成了指示AI注意力的热力图，通过实验1确认热力图可解释性的有效性，并通过实验2考察目的与热力图对依赖（依赖于AI）和服从（接受AI答案）的影响。结构方程模型（SEM）分析结果显示：（1）根据AI使用类型（依赖或服从）及任务难度，展示AI目的对信任既有正面也有负面影响；（2）在较难任务中，仅展示热力图会负面影响信任；（3）在较难任务中，热力图根据其可解释性对信任产生正面影响。