Kursinformation

Machine learning systems increasingly influence high-stakes decisions in areas such as hiring, lending, and criminal justice, raising urgent questions about fairness. This seminar explores how causal inference provides a principled framework for understanding and addressing discrimination in algorithmic decision-making. Participants will receive an introduction to core concepts in causal inference and their applications to fairness, followed by an in-depth critical discussion of an assigned research paper. The seminar aims to equip students with the tools to rigorously analyze fairness claims and evaluate the assumptions underlying different approaches to algorithmic fairness

Importierter Kurs aus dem LSF