When: Friday, January 30, 3:00 PM
Where: Tyler 055

Abstract
As AI systems are increasingly introduced into our everyday lives and high-stakes domains, it’s critical that decisions around their use, design, and governance center the specific contexts and communities they affect. My research explores participatory approaches that support community control, domain specificity, and local agency in AI design and governance. I’ll first discuss challenges to incorporating meaningful participation into general-purpose foundation models, highlighting an overarching tension between local agency and scale, and proposing more domain-specific opportunities for participatory development and governance. Building on this, I’ll share findings from a collaborative co-design project with journalists to envision a cooperatively-controlled large language model, surfacing organizational and day-to-day tensions that such an endeavor would need to address. Finally, I’ll connect these insights to ongoing work co-producing datasets and AI tools with feminist activists and journalists to challenge harmful narratives in news coverage of gender-based violence and femicide. Across these projects, I aim to draw out possibilities and challenges for a vision of AI that centers community agency and control.

Bio
Dr. Harini Suresh is an Assistant Professor of Computer Science at Brown University, affiliated with the Department of Science, Technology & Society (STS) and the Center for Technological Responsibility, Reimagination, and Redesign (CNTR). She leads the Data in Society Collective (DISCO Lab), which studies how to support individual and collective agency in technology design, use, and refusal. She also helps lead the cross-institutional Counterdata Network project, which collaboratively designs technologies with activists who monitor human rights violations in order to support their work. Before joining Brown, Harini was a postdoctoral researcher at Cornell Tech, examining the limitations of participatory approaches in the era of “general-purpose” AI systems. She completed her PhD, M.Eng. and B.Sc. in Computer Science at MIT.