Data, Algorithms, Justice

4.0 credits

This course focuses on a number of questions that arise in the design, development and deployment of machine learning algorithms. Topics include: Bias in algorithms (e.g., how should we measure unfairness in algorithms that determine who gets bail, parole, a job, or a loan? What about bias in health analytics?) Values disagreement and algorithms (e.g., how should self-driving cars or diagnostic algorithms make decisions, given that we disagree about the good?) Algorithms, social media, and public life (e.g., what is the impact of social media algorithms on public discourse and the future of democracy?) Algorithms and the future of work (e.g., how should we structure our society when many basic tasks will be performed by machines? How should we distribute the benefits of machine productivity?)