Abstract
This colloquium will explore the participatory design of a cross-institutional graduate curriculum and exchange program focused on equitable AI. This collaboration, funded by the Sloan Foundation, establishes a curriculum focused on the intersections of equity and AI through a participatory model. Specifically, this project aims to establish a curriculum that supports Historically Underrepresented and Minoritized (HURM) students and establish a programmatic approach rooted in inclusion and coalitional values. To that end, our colloquium offers ruminations on five key terms that we have explored throughout the grant: Equitable AI: What do we mean when we say equitable AI? How can students understand the relationship between equity and AI? Curricular Models: What curricular models enable institutions to teach equitable AI? Participatory Design/Participatory AI: What kinds of platforms, procedures, and community guidelines do we use to build programs through participatory design? Coalitional Trust: What do students need to trust faculty and establish community across different institutions, particularly when one is a predominately white institution and the other is a historically black college and university? Transdisciplinary Research: How do we enable cross-institutional, transdisciplinary research? What kinds of exchange programs allow for this kind of work? This colloquium will include faculty and student presenters from across disciplines (computer science, engineering, education, philosophy and rhetoric) and will be organized around these themes, with members of the team offering 5-7 minute ignite talks that, taken together, offer insight into the data, decisions, and outcomes of the research project, where outcomes are both experiences and deliverables.
Presenters
Kristen MooreAssociate Dean for Equity and Inclusion, School of Engineering and Applied Sciences, University at Buffalo, New York, United States
Details
Presentation Type
Theme
2026 Special Focus—Human-Centered AI Transformations
KEYWORDS
Equitable AI, Participatory Design, Coalitional Models, Transdisciplinary Research
