We study, design, and prototype AI-mediated systems for aging that emphasize transparency, meaningful control, and alignment with older adults’ values. This includes work on voice assistants and conversational AI, context-aware systems that integrates multimodal sensing, personal context, and explainable reasoning to provide transparent and personalized support as people’s needs and abilities change over time.
Publications: CSCW 2025; TOCHI 2025; CHI 2025; PETRA 2025; Information Research 2025; CSCW 2024; CHI 2022; TOCHI 2021, 2020; CSCW 2019
How do design defaults (a voice, an accent, a skin-tone palette, a GIF) quietly encode age, race, disability, class, or caste?
And when AI systems speak for people, what stereotypes persist beneath seemingly unbiased outputs?
In this project cluster, we examine how everyday design and data practices produce representational harm across AI systems, visual communication, and algorithmic media towards designing responsible, community-centered tools.
Publications: ASSETS 2025; CSCW 2025; Web4All 2025; BCSHCI 2025; CUI 2021
What happens to our stories, memories, and data after we die? How do we want to be remembered, and who gets to decide?
To design thoughtful tools for digital legacy and remembrance, we learn from older adults, who often bring lived experience with end-of-life planning, loss, and the purposeful curation of personal histories. We examine how systems might support people in shaping how they are remembered, while addressing the risks, uncertainty, and emotional labor that end-of-life data planning can involve.
Publications: DIS 2025, CHI 2026