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As AI technology continues to evolve, ensuring seamless and productive human-agent interactions becomes increasingly crucial. Empathy and trust are fundamental components in fostering user engagement, collaboration, and the ethical acceptance of agents. This study examines the impact of an agent’s attitude and behavioral modifications on empathy and trust, exploring how these elements interact to shape human perceptions. An agent designed to promote traffic safety reflection was employed as an experimental stimulus. This study implemented a three-factor mixed design, evaluating agent attitude (positive or neutral), behavior modification (present or absent), and temporal effects (before/after modification). A total of 582 participants engaged with the agent, and their responses were analyzed using ANOVA to examine fluctuations in empathy and trust levels. The findings revealed a significant interaction between behavior modification and temporal factors, demonstrating that positive behavioral adjustments contribute to maintaining and enhancing empathy and trust. Moreover, agents exhibiting a consistently positive attitude received significantly higher empathy and trust ratings than neutral ones, highlighting the importance of affective expressiveness in agent design. These findings offer valuable insights into the ethical and strategic deployment of agents in human environments, ensuring their perception as reliable and cooperative partners. By fostering adaptive and emotionally aware intelligent systems, this research contributes to strengthening user trust, reducing biases, and facilitating more effective human-agent collaboration.
Tsumura et al. (Wed,) studied this question.