Andrew Sellars

3 credits

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.

4 credits

THIS CLASS IS RESTRICTED to students who have formally applied to and been accepted to the Technology Law Clinic. In the Clinic, students will represent MIT and BU students who are working on innovative research and ventures, counseling clients on issues including data privacy, intellectual property, computer crimes, cybersecurity, media law, and regulatory compliance. Students draft and negotiate agreements, design compliance programs, advise on the legality of innovative products and services, respond to cease-and-desist threats, and help clients anticipate and prepare for legal disputes, including pre-litigation support. Limited opportunities in litigation may be available. PRE/CO-REQUISITE: a course in one of the following three areas: (1) intellectual property (either an IP survey course or other core IP course such as patent, copyright, or trademark); (2) privacy law (including Privacy (JD 822)); or (3) cybersecurity. NOTE: The Technology Law Clinic counts toward the 6 credit Experiential Learning requirement. GRADING NOTICE: This course does not offer the CR/NC/H option.

2 credits

THIS CLASS IS RESTRICTED to students who have formally applied to and been accepted to the Technology Law Clinic. This is the fall classroom component to the Technology Law Clinic. The seminar introduces students to the lawyering skills relevant to a modern technology law practice, including effective counseling of innovation clients The seminar also introduces a variety of legal issues that arise in research and innovation environments, including advanced topics in intellectual property, computer crimes, and data privacy. NOTE: The Technology Law Clinic counts toward the 6 credit Experiential Learning requirement. GRADING NOTICE: This course does not offer the CR/NC/H option.

2 credits

THIS CLASS IS RESTRICTED to students who have formally applied to and been accepted to the Technology Law Clinic. This is the spring classroom component to the Technology Law Clinic. The seminar expands upon the lawyering skills and substantive legal discussions from the first semester, and will focus on questions of national policy as they relate to technology, including national control over technical information, academic privacy and freedom, and emerging cybersecurity regulation. NOTE: The Technology Law Clinic counts toward the 6 credit Experiential Learning requirement. GRADING NOTICE: This course does not offer the CR/NC/H option.