Units:

12

Description:

This course provides an interdisciplinary introduction to the key principles and topics in responsible AI, including bias, fairness, interpretability, explainability, privacy, robustness, and safety. Students will develop an understanding of these topics from multiple stakeholder perspectives. The course will cover key methods in responsible AI, drawing on machine learning, statistics, and economics. It will also examine emerging frameworks in AI policy and regulation. Students should have taken an introductory machine learning course or equivalent.

Last Modified: 2026-02-24 12:02PM

Current session:

This course is currently being offered.

Semesters offered:

• Spring 2026