As AI technology develops, trust in AI agents is becoming more important for more AI applications in human society. Possible ways to improve the trust relationship include empathy, success-failure series, and capability (performance). Appropriate trust is less likely to cause deviations between actual and ideal performance. In this study, we focus on the agent's empathy and success-failure series to increase trust in AI agents. We experimentally examine the effect of empathy from agent to person on changes in trust over time. The experiment was conducted with a two-factor mixed design: empathy (available, not available) and success-failure series (phase 1 to phase 5). An analysis of variance (ANOVA) was conducted using data from 198 participants. The results showed an interaction between the empathy factor and the success-failure series factor, with trust in the agent stabilizing when empathy was present. This result supports our hypothesis. This study shows that designing AI agents to be empathetic is an important factor for trust and helps humans build appropriate trust relationships with AI agents.

翻译：随着人工智能技术的发展，对于人工智能体在人类社会中的更多应用而言，对其的信任正变得愈发重要。改善信任关系的可能途径包括共情、成功-失败序列以及能力（表现）。适当的信任能够降低实际表现与理想表现之间的偏差。本研究聚焦于智能体的共情能力和成功-失败序列，以提升对人工智能体的信任。我们通过实验考察了智能体对人类的共情如何随时间影响信任的变化。实验采用双因素混合设计：共情（有、无）和成功-失败序列（阶段1至阶段5）。基于198名参与者的数据进行了方差分析。结果显示，共情因素与成功-失败序列因素之间存在交互作用，当共情存在时，对智能体的信任趋于稳定。这一结果支持了我们的假设。本研究表明，将人工智能体设计为具有共情能力是影响信任的重要因素，并有助于人类与人工智能体建立适当的信任关系。