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October 19, 2025Journal of Service Research4 citations

Empathetic AI Encounters: Pathways to Prosocial Behavior

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HSHaijiao ShiBeijing Technology and Business UniversityBYBingqing YinCalifornia Polytechnic State UniversityLTLefa TengJiangnan University

Key Points

  • Interactions with high-empathy AI significantly increase individuals' inclination to donate and volunteer.
  • In six experiments, users donated more when engaging with high-empathy AI, enhancing their prosocial actions.
  • Observational learning theory explains that AI's modeled empathy boosts users’ own empathic states, promoting help.
  • AI's human-identifying features strengthen its positive effects on fostering connection and charitable behavior.

Abstract

The latest advancements in artificial intelligence (AI) not only highlight exceptional intelligence quotient but also emphasize remarkable emotional intelligence or emotional quotient. The current research investigates how interactions with empathetic AI affect individuals’ propensity to engage in prosocial behavior. Across six experiments, including a real-time human-AI interaction study and an incentivized behavioral study, we demonstrate that interactions with high- (vs. low-) empathy AI significantly increase individuals’ inclinations to donate, the amount donated, and their intentions to volunteer. Drawing on observational learning theory, we show that this effect occurs because high-empathy AI enhances perceptions of AI humanness. This heightened humanness facilitates empathetic influence, whereby the AI’s modeled empathic behaviors elevate users’ own empathic states, ultimately promoting greater prosocial action. Furthermore, this positive effect of high-empathy AI is strengthened by AI’s human-identification marks (i.e., human name and icon). The research findings offer theory-based, actionable recommendations for effectively leveraging AI in service encounters to promote prosocial behaviors.

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Cite This Study

Shi et al. (2025) studied this question.

synapsesocial.com/papers/68f43f09854d1061a58ac733https://doi.org/10.1177/10946705251380568
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