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Exploring the Effect of Robotic Embodiment and Empathetic Tone of LLMs on Empathy Elicitation

Published: March 26, 2025 | arXiv ID: 2503.20518v1

By: Liza Darwesh , Jaspreet Singh , Marin Marian and more

Potential Business Impact:

Robots can't make you care about others.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

This study investigates the elicitation of empathy toward a third party through interaction with social agents. Participants engaged with either a physical robot or a voice-enabled chatbot, both driven by a large language model (LLM) programmed to exhibit either an empathetic tone or remain neutral. The interaction is focused on a fictional character, Katie Banks, who is in a challenging situation and in need of financial donations. The willingness to help Katie, measured by the number of hours participants were willing to volunteer, along with their perceptions of the agent, were assessed for 60 participants. Results indicate that neither robotic embodiment nor empathetic tone significantly influenced participants' willingness to volunteer. While the LLM effectively simulated human empathy, fostering genuine empathetic responses in participants proved challenging.

Page Count
10 pages

Category
Computer Science:
Human-Computer Interaction