Fall 2020 • Course
Fairness and Privacy: Perspectives of Law and Probability
Prerequisites: Admission is by permission of instructors; applicants should submit letters of inquiry with CVs to Joseph Cunningham (email@example.com) by April 28, 2020.
Exam Type: No Exam
From old problems like affirmative action to newer ones like the turn to algorithms in criminal justice and credit, law and private actions use group traits to influence or determine the treatment of individuals. When do these practices run afoul of conceptions of fairness in law or in computer science and statistics? When do alternatives even exist? New approaches to data analysis quantify and control individual privacy loss while revealing information about larger groups. When do these concepts run afoul of conceptions of privacy in law? What elements of legal and quantitative reasoning exacerbate or resolve such issues, and how can people with training in one field better collaborate with those from other disciplines? This intensive seminar will bring together advanced students in computer science, statistics, law, and government to tackle these and related questions. Offered concurrently by HLS and SEAS, with interwoven tracks emphasizing, respectively, law and computer science, the tracks will meet jointly and separately.