Enhancing Empathic Reasoning of Large Language Models Based on Psychotherapy Models for AI-assisted Social Support

• Published in: 인지과학 Vol. 35; no. 1; pp. 23 - 48
• Main Authors: Yoon Kyung Lee(이윤경), Inju Lee(이인주), Minjung Shin(신민정), Seoyeon Bae(배서연), Sowon Hahn(한소원)
• Format: Journal Article
• Language: English
• Published: 한국인지과학회 01.03.2024
• Subjects: 인지과학; AI-assisted Social Support; 자연어처리; 인지적 AI; Natural Language Processing; 인공지능 기반 사회적 지지; Empathy; Cognitive AI; AI Alignment; Large Language Models; 대형언어모형; 공감
• ISSN: 1226-4067
• DOI: 10.19066/cogsci.2024.35.1.002

Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches—Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)—each leading to different patterns of interpreting clients’ mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model’s different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI. KCI Citation Count: 0