Empathy Toward Artificial Intelligence Versus Human Experiences and the Role of Transparency in Mental Health and Social Support Chatbot Design: Comparative Study
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Abstract
Background: Empathy is a driving force in our connection to others, our mental well-being, and resilience to challenges. With the rise of generative artificial intelligence (AI) systems, mental health chatbots, and AI social support companions, it is important to understand how empathy unfolds toward stories from human versus AI narrators and how transparency plays a role in user emotions. Objective: We aim to understand how empathy shifts across human-written versus AI-written stories, and how these findings inform ethical implications and human-centered design of using mental health chatbots as objects of empathy. Methods: We conducted crowd-sourced studies with 985 participants who each wrote a personal story and then rated empathy toward 2 retrieved stories, where one was written by a language model, and another was written by a human. Our studies varied disclosing whether a story was written by a human or an AI system to see how transparent author information affects empathy toward the narrator. We conducted mixed methods analyses: through statistical tests, we compared user’s self-reported state empathy toward the stories across different conditions. In addition, we qualitatively coded open-ended feedback about reactions to the stories to understand how and why transparency affects empathy toward human versus AI storytellers. Results: We found that participants significantly empathized with human-written over AI-written stories in almost all conditions, regardless of whether they are aware (t196=7.07, P<.001, Cohen d=0.60) or not aware (t298=3.46, P<.001, Cohen d=0.24) that an AI system wrote the story. We also found that participants reported greater willingness to empathize with AI-written stories when there was transparency about the story author (t494=–5.49, P<.001, Cohen d=0.36). Conclusions: Our work sheds light on how empathy toward AI or human narrators is tied to the way the text is presented, thus informing ethical considerations of empathetic artificial social support or mental health chatbots.
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The anthropomorphic design of chatbots and virtual companions encourages users to attribute human-like intentionality and empathy to algorithms.
“the anthropomorphic design of chatbots and virtual companions encourages users to attribute human-like intentionality and empathy to algorithms, a dynamic reminiscent of the “ELIZA effect” described in early human-computer interaction literature [20,21].”
From Delusional Experiences Emerging From AI Chatbot Interactions or “AI Psychosis” (2025) · cites this paper as [20]
The Introduction says commercial chatbots adopt identities or experiences and that human-like appearance and behavior can lead users to form empathic relationships with AI agents. It does not establish that users attribute human-like intentionality or empathy to the algorithms themselves. The Discussion (Principal Results) also cautions that more anthropomorphic representation may not increase trust in the storytelling setting studied. (LLM, conf=0.83)
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- Authors
- Shen, J., DiPaola, D., Ali, S., Sap, M., Park, H. W., & Breazeal, C.
- Affiliations
- MIT Media Lab (US)
- Carnegie Mellon University (US)
- Corresponding author
- Shen, Jocelyn
- Venue
- JMIR Mental Health
- Publisher
- JMIR Publications Inc.
- Published
- 2024-09-25
- Volume
- 11
- Pages
- e62679
- ISSN
- 2368-7959 (ISSN-L)
- PMC
- PMC11464935
- OpenAlex
- W4402155818
- Cited by
- 92
- References
- 42
- Citations by year
- 2026: 60 · 2025: 32
- FWCI
- 43.36
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Mental Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Science Foundation (2141064)
- Ministry of Science and ICT, South Korea (2020-0-00842)
- Institute for Information and Communications Technology Promotion (2020-0-00842)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- AI-generated text, transparency, mental health chatbots, author disclosure, generative AI, human-centered design, AI ethics, user emotions
- MeSH terms
- Adult, Artificial Intelligence, Empathy, Female, Humans, Male, Mental Health, Middle Aged, Social Support, Narration, Young Adult
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