The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health Support

• Main Authors: Song, Inhwa, Pendse, Sachin R, Kumar, Neha, De Choudhury, Munmun
• Format: Journal Article
• Language: English
• Published: 25-01-2024
• Subjects: Computer Science - Artificial Intelligence; Computer Science - Computers and Society; Computer Science - Human-Computer Interaction
• DOI: 10.48550/arxiv.2401.14362

People experiencing severe distress increasingly use Large Language Model
(LLM) chatbots as mental health support tools. Discussions on social media have
described how engagements were lifesaving for some, but evidence suggests that
general-purpose LLM chatbots also have notable risks that could endanger the
welfare of users if not designed responsibly. In this study, we investigate the
lived experiences of people who have used LLM chatbots for mental health
support. We build on interviews with 21 individuals from globally diverse
backgrounds to analyze how users create unique support roles for their
chatbots, fill in gaps in everyday care, and navigate associated cultural
limitations when seeking support from chatbots. We ground our analysis in
psychotherapy literature around effective support, and introduce the concept of
therapeutic alignment, or aligning AI with therapeutic values for mental health
contexts. Our study offers recommendations for how designers can approach the
ethical and effective use of LLM chatbots and other AI mental health support
tools in mental health care.