Data Protection in Data-Driven Systems

Contemporary AI systems are characterized by extensive personal data collection despite the increasing societal costs associated with such practices. To prevent harm, data protection regulations specify various principles for respectfully processing user data, such as purpose limitation, data minimization, or the need to establish a valid basis for data processing, such as consent or legitimate interest. Yet, practical implementations of these principles in data-driven systems leave much to be desired. This talk will delve into the computational and human factors contributing to lax data protection implementations and uncover ways research can contribute to improved data governance online.

Asia Biega is a computer scientist and a tenure-track faculty member at the Max Planck Institute for Security and Privacy (MPI-SP) where she leads the interdisciplinary Responsible Computing group. In her research, Asia studies questions at the intersection of computing & society, particularly in the context of data-driven systems. She often collaborates with scholars in law, philosophy, and social sciences, draws from her industry experience at Microsoft and Google, and shares her expertise with policymakers, data protection authorities, artists, industry, and NGOs. She has served as an external expert for the European Commission and the General Co-Chair of ACM FAccT 2025, the biggest academic conference focusing on the societal impacts of computing. Her work has been recognized with Council of Europe’s Rodota Award for innovative research in data protection, SaTML Notable Reviewer Award, and the GI-DBIS Dissertation Award of the German Informatics Society. Before joining MPI-SP, Asia was a postdoctoral researcher at Microsoft Research Montréal, and before that, she completed her PhD. at the MPI for Informatics and the Saarbrücken Graduate School of Computer Science.