Can a Chatbot Help
Someone Feel Better Safely ?
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Lecture overview:
Can an AI chatbot help people feel better? If so,
what other effects does it have on them? These two questions are interconnected. AI systems assist by building rapport, encouraging self-disclosure, and nudging individuals toward positive change. However, these same abilities can be risky, especially when the person interacting with the chatbot is vulnerable. The potential for effectiveness and harm stems from a single mechanism rather than two separate ones, which is why they cannot be managed independently.
This talk is based on years of experience in designing conversational agents focused on self-disclosure,
well-being, and behavior change. It also references recent research measuring the lasting impacts of conversations with AI—specifically how these interactions can shift individuals' self-perceptions and what they are willing to express. Much of this change occurs subtly during regular use, presenting both opportunities for prevention and hard-to-detect risks.
The key question is not whether these systems will be used for mental well-being; they already are. Instead, we must consider the terms under which they are used, the evidence supporting their effectiveness, and whose well-being and agency should be prioritized as measures of success.
Event details:
Date: 29 December 2026 (Wednesday)
Time: 15:00 to 16:30
Venue: Tung Wah College, King's Park Campus, 2/F Lecture Theatre (LT1) and Zoom
*This workshop will be conducted in english.
About the speaker:
Yi-Chieh (EJ) Lee is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS) School of Computing. He is deputy Director of the NUS Centre for Computational Social Science and Humanities (CSSH) and leads the AI4SG Lab.
His research spans human-computer interaction, human-centered AI, and computational social science. He focuses on how conversational AI shapes people’s well-being, beliefs, and sense of agency, and how it can be designed to serve social good.
Recent projects address mental illness stigma, learning with AI, support for older adults, and harms in human-AI relationships. His work appears at venues including CHI, CSCW, ACL, and AAAI, and in journals such as Nature Computational Science and npj Digital Medicine. It has received a CHI Best Paper Award and multiple research paper awards.
His research is supported by Google, Google DeepMind, Avature, and Singapore’s Ministry of Education. He holds a PhD in Computer Science from the University of Illinois Urbana-Champaign.
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