This cross-cutting and interdisciplinary course, taught alongside a graduate-level course with BU's new faculty of Computing and Data Sciences, investigates the role that algorithms and automated decision-making systems play in law and society. The course connects legal and technical concepts of transparency, fairness, bias, privacy, and trust, though a series of case studies that present recent applications of technology to legal and regulatory situations and explore the challenges in regulating algorithms. Legal concepts explored will include evidence and expert witnesses, anti-discrimination law concepts of disparate impact and disparate treatment, sectoral information privacy regimes, and public access and transparency laws. Technical concepts explored will include artificial intelligence and machine learning, secure multi-party computation, differential privacy, and zero-knowledge proofs. Grades will be based on a series of assignments that correspond with each case study, to be completed collaboratively in mixed teams of law and computing/data science students. No prior technology experience is required. GRADING NOTICE: This class will not offer the CR/NC/H option.

Note that this information may change at any time. Please visit the Student Link for the most up-to-date course information.