Socially Assistive Robots as Storytellers that Elicit Empathy

Author:

Spitale Micol1ORCID,Okamoto Sarah2,Gupta Mahima2,Xi Hao2,Matarić Maja J.2

Affiliation:

1. Politecnico di Milano, Italy and University of Southern California, Los Angeles, California, United States

2. University of Southern California, Los Angeles, California, United States

Abstract

Empathy is the ability to share someone else’s feelings or experiences; it influences how people interact and relate. Socially assistive robots (SAR) are a promising means of conveying and eliciting empathy toward facilitating human-robot interaction. This work examines factors that influence the amount of empathy elicited by a SAR storyteller and users’ perceptions of that robot. We conducted an empirical mixed-design study (N=46) using an autonomous SAR storyteller that told three stories, each with a different human or robot target of empathy. The robot storyteller used the first-person narrative voice (1PNV) with half of the participants and the third-person narrative voice (3PNV) with the other half. We found that the SAR storyteller elicited significantly more empathy when the story target of empathy matched the SAR narrator, i.e., was also a robot. Additionally, the 1PNV robot elicited significantly more empathy and was perceived as more human-like, easy to interact with, and trustworthy than the 3PNV robot. Finally, participants who empathized more with the robot displayed facial expressions consistent with the emotional story content. These insights inform the design of SAR storytellers capable of eliciting empathy toward creating compelling and effective human-robot interactions.

Funder

EIT Digital

National Science Foundation Expedition in Computing

University of Southern California

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

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