[Abstract]

Personal Informatics (PI) systems—technologies that interact with people exchanging self-knowledge—have entered a new stage of advancement enabled by Large Language Models (LLMs) as well as increased interest in mental health and well-being. Despite their prevalence, a large body of LLM-infused systems are designed for lay individuals (i.e., young adults) in mind. Designing AIs for marginalized populations in other age groups (e.g., children and older adults) or the neurodivergent (e.g., people with Autism or mental health issues) involves new technical challenges and considerations. In this talk, I introduce my recent research at NAVER AI Lab on LLM-driven PI systems targeted for various marginalized populations and discuss unique challenges and considerations that arise when designing LLM technologies for those people. In particular, I cover an ethnographic study on how the long-term memory of LLM-driven chatbots impacts user engagement of socially isolated older adults, a thought-provoking chatbot for children, and a communication mediation app for parents and minimally verbal autistic children.

[Biography]

Young-Ho Kim is a research scientist at NAVER AI Lab, leading the Human-Computer Interaction research group. Before joining NAVER, he worked as a postdoctoral associate in at the Human-Computer Interaction Lab of the University of Maryland, College Park (2019-2021). Young-Ho is a Human-Computer Interaction researcher working at the intersection of Personal Health Informatics and Artificial Intelligence. Combining his multidisciplinary knowledge in Computer Science and Visual Communication Design, he has designed and developed computing systems for self-tracking that facilitate people to collect and consume their activity and health data in a flexible manner. He has been recently investigating how large language models can further streamline flexible human-data interaction and be accessible to marginalized populations. He has disseminated his research at prestigious HCI and Computer Science venues such as CHI, CSCW, UbiComp, VIS, and DIS.

Young-Ho received a Ph.D. degree in Computer Science and Engineering (2012-2019) and a Bachelor of Fine Arts degree in Visual Communication Design (2007-2011) from Seoul National University. He is a recipient of the Korea International Postdoc Fellowship supported by the National Research Foundation of Korea in 2019, a Best Paper award at ACM CHI 2023, and an Honorable Mention award at ACM CHI 2021. For more details, see his website at http://younghokim.net.