“Do You Need the Sage’s Tea or the Friend’s Cola” Exploring the Differential Healing Effects of Generative AI Conversational Styles

Xinheng Song, Haiwen Song, Bingjie Gao, Qijun Gao, Wenting Li, Linci Xu, Zhaolin Lu*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

While the preliminary exploration of Generative AI in aiding psychotherapy has already commenced, there has been no research on the intrinsic selection mechanism on the user side during the process of GAI-assisted psychological healing. To address this gap, we experimented with 30 participants using the fine-tuned large language model, assessing emotional responses through heart rate variability, facial expressions, and SAM scales. Results show that participants engaging with GAI therapists exhibiting slow response times and rich content experienced higher happiness, while those interacting with faster, brief-content GAI therapists showed greater surprise. Additionally, despite the stress levels initially slightly rising during conversations with GAI therapists, they decrease over time and ultimately lead to an improved emotional state. These findings validate the effectiveness of GAI therapists and provide a basis for applying GAI in different psychotherapy scenarios.

Original languageEnglish
Title of host publicationCHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9798400713958
DOIs
Publication statusPublished - 26 Apr 2025
Externally publishedYes
Event2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025 - Yokohama, Japan
Duration: 26 Apr 20251 May 2025

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025
Country/TerritoryJapan
CityYokohama
Period26/04/251/05/25

Keywords

  • Affective healing
  • Dialogue Styles
  • Facial expression
  • Heart rate variability
  • Human-AI interaction

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