Lessons Learned from Failures of Data-Driven Systems in Society.

Catalog description

This course provides a holistic, interdisciplinary research toolkit for understanding the contact point between data and society. It will explore science and technology studies (STS), AI ethics, and social theory, while learning from legal scholars, historians, and computer scientists. It examines how different approaches involve distinct normative assumptions, blind spots, and even value judgments about technology and society. The course is focused on developing skills for finding, reading, and synthesizing research across disciplines, and for effectively translating knowledge between contexts - especially between technical and social perspectives on datafication, algorithms, and AI. No technical background is required.