PUBPOL 5725

Ethics in Data, Data Science, and AI for Public Policy

Course Description

Course information provided by the 2026-2027 Catalog.

This graduate-level course is designed for students pursuing leadership or managerial roles in organizations across the public, private, and nonprofit sectors involved with shaping or making data science and technology. Special attention will be paid to ethical concerns associated with data science, including biases, privacy, surveillance, discrimination, transparency, accountability, and implications for artificial intelligence. This course is designed for students in the Jeb E. Brooks School of Public Policy MS in Data Science for Public Policy program. Other students may only enroll with permission of the instructor. As a graduate level course, students are expected to have thoroughly read all materials prior to class and be well-prepared to discuss readings and cases with colleagues. (MPA-DA, MPA-DATSCI, MPA-ECONPL, MPA-SCITEC, MPA-TPA)

Enrollment Information Enrollment limited to: graduate and professional students.

Last 4 Terms Offered (None)

Learning Outcomes

• Analyze the lifecycle of a data science project, identify ethical concerns that might emerge at each stage of the project, and recommend measures for addressing these concerns.
• Apply best practices in data ethics in drafting an original data privacy policy directive memo for an organization.
• Discuss the pace of technological development in data science and regulatory policy governing this space.

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