AI Governance: Identifying and Mitigating Risks in the Design and Development of AI Solutions
Location: Pittsburgh
Semester Offered: Spring
Cross listed Courses:
| Course Number | Department | Units |
|---|---|---|
| 17-416 | Software and Societal Systems Department | 6 |
| 17-716 | Software and Societal Systems Department | 9 |
| 19-416 | Engineering and Public Policy | 6 |
| 19-716 | Engineering and Public Policy | 9 |
With AI and ML finding their way into an increasingly broad range of products and services, it is important to identify and mitigate the risks associated with the adoption of these technologies. This course reviews the different types of risks associated with AI and discusses the methodologies and techniques available to identify and mitigate these risks. The course introduces students to the ethical frameworks available to identify and analyze risks. It also examines best practices emerging from both government and industry efforts in this area. This includes looking at new regulations, such as the EU AI Act, as well as emerging frameworks such as the one developed by NIST. The course also examines frameworks, developed by leading companies and how these frameworks combine both technical and non-technical approaches. It further discusses changes that need to be enacted by organizations to adopt more systematic approaches to AI governance.
This course combines a mix of technical, policy, and management discussions.
This course is intended for a broad cross-section of students, both advanced undergrads and graduate students, planning to work on the design, development and deployment of AI-based solutions. The course is designed to introduce students to key concepts, challenges, principles, methodologies, techniques, best practices, legal requirements and trends associated with the responsible design, development and deployment of AI technologies.