This course aims to introduce the concept of race into discussions of fairness in machine learning. Participants will learn to translate critical race theory and social scientific discourses into terms understandable to machine learning practitioners. The teaching method includes presentations and small-group activities. This course is intended for machine learning practitioners interested in exploring the intersection of race and fairness in algorithmic decision-making.
Toward a Theory of Race for Fairness in Machine Learning
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
FAT* 2019 Translation Tutorial: Toward a Theory of Race for Fairness in Machine Learning
Taught by
ACM FAccT Conference
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