Nov. 5: Anna Fang

Designing Simulation Systems for Mental Health

Poorly designed interventions or those deployed without adequate safeguards can harm the communities they aim to serve, thus exacerbating existing vulnerabilities and leaving individuals unsupported. This is especially the case for the mental health context, where there is a growing trend of relying on technological interventions; however, the mental health context is also particularly sensitive to change and risks of failure are dire. Thus, enabling safe ways to experiment in the mental health context is vital to allow both individuals and communities to engage with new interventions without risk of their real-world consequences. In this talk, I will discuss my dissertation work on using simulation approaches to support emerging mental health processes through (1) simulating for community outcomes through agent-based modeling for designing matching in online peer support and (2) simulating individual interactions using XR and LLMs to help people practice self-care techniques. By leveraging simulation to create environments where mental health strategies can be safely tested and practiced, this work aims to open new possibilities for designing scalable, user-centered systems that are effective and safe. Lastly, I will review my ongoing and postdoctoral work that extends this agenda towards simulation- and AI-based interventions for value alignment in AI use and self-representation.

ABOUT THE PRESENTER

Anna M. Fang (she/her) is a postdoctoral researcher at the University of Washington in Computer Science & Engineering. She received her Ph.D. from Carnegie Mellon University in the School of Computer Science & Human-Computer Interaction Institute. Anna is a human-computer interaction (HCI) researcher, focused on the design and development of AI, simulation-based, and embodied tools for mental health and social impact applications. Her work has been awarded at CHI and published at top venues in HCI and beyond (e.g., CHI, CSCW, JMIR), and funded as the first two-time Fellow by the Center for Machine Learning & Health at CMU.