Designing AI That Matters: Rethinking Human–AI Interaction through Impact, Governance, and Literacy

Bio: Motahhare Eslami is an assistant professor at the School of Computer Science, Human-Computer Interaction Institute (HCII), and Software and Societal Systems Department (S3D), at Carnegie Mellon University. She earned her Ph.D. in Computer Science at the University of Illinois at Urbana-Champaign. Motahhare’s research is broadly in Human-Computer Interaction, Artificial Intelligence, and Social Computing. Her research aims to shift the landscape of Responsible AI from one that acts on behalf of users to one that is built with and by them. Motahhare is named one of the 100 Brilliant Women in AI Ethics, and her work has been recognized with multiple awards at top-tier ACM and AAAI conferences. Motahhare’s research has been covered in mainstream media such as Time, The Washington Post, Huffington Post, the BBC, Fortune, Quartz, and WIRED. Motahhare has received the Google Research Scholar Award, the Microsoft AI & Society Fellowship, and the Google Academic Research Award for Society-Centered AI. Her research is supported by NSF (Fairness in AI, Future of Work, and AI Institute), Amazon, Google, Microsoft, Meta, Cisco, IBM and CMU’s Block Center for Technology and Society.

Abstract: As AI becomes increasingly embedded in the fabric of everyday life, its technical architectures and social consequences can no longer be treated separately–they must be designed and studied together. The central question is how to design, engineer, and govern AI systems that advance performance while serving human goals, values, and capacities. This talk starts from rethinking what kind of AI we aim for, then how we hold it accountable, and finally how people gain the capacity to do so. Across these dimensions, I present research that integrates system design, empirical studies, and participatory methods to reimagine human–AI interaction as shared stewardship.
I begin by examining what it means for an AI system to be impactful rather than merely impressive—how algorithms, models, and interfaces can be developed and evaluated to address stakeholders’ real needs in domains such as healthcare. Designing for impact, however, also requires ensuring that systems remain aligned with those needs once deployed—raising questions of accountability and oversight: how everyday users, civic actors, and affected communities can play a role in governing AI systems. Through participatory audits, community oversight, and user-led infrastructures, I show how democratic accountability can scale when power and responsibility are shared—enabling users and communities to identify and act on AI failures. Finally, I turn to the question of capacity: how diverse publics—from youth to professionals to policymakers—can build the literacies, tools, and reasoning needed to be engaged in interpreting, questioning, and shaping AI systems. Together, these threads outline a vision of human–AI interaction as shared stewardship: designing and developing AI systems where technical rigor, social responsibility, and public empowerment advance together.

This seminar is both online and in-person:
Zoom Link