Asia J. Biega

Date: February 23rd, 2026

Time: 16:00 (CET)

Title:  The Promise and Perils of Consent-Credit-Compensation in Generative AI

Abstract: Since the emergence of generative AI, creative workers have voiced concerns about career-based harms stemming from this technology. A recurring issue is that generative AI models are trained on their creative output without consent, credit, or compensation. The "3Cs framework"—Consent, Credit, and Compensation—has emerged as a proposed governance approach for responsible training of GenAI. This talk presents findings from our recent study with creative workers that explores the complexities of implementing this framework for GenAI data governance. Building on these insights, I examine the consent dimension more closely, discussing what lessons for genAI can be learned from another domain: consent to personal data processing under the GDPR.

About the Presenter:  Dr. 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. Her research explores the intersection of computing and society, with a focus on tech governance & regulation, social responsibility, and digital well-being. She is a principal investigator in the CASA Cluster of Excellence and the FINDHR consortium, and has collaborated widely across disciplines and sectors. She has served as an external expert for the European Commission, and the General Co-Chair of FAccT 2025, the biggest academic conference focusing on the societal impacts of computing. She now sits on the FAccT Executive Committee. Her work has been recognized with Council of Europe’s Rodota Award for innovative research in data protection, Annual Privacy Forum's Best Paper Award, SaTML Notable Reviewer Award, the GI-DBIS Dissertation Award of the German Informatics Society, and she has been named one of the 2025 “100 Brilliant Women in AI Ethics”.

learn more about the presenter at: https://asiabiega.github.io/