AI Auditing and Governance

(3 Credit Hours) · Undergraduate

As artificial intelligence systems shape organizational and societal outcomes, there is a growing need for professionals who can evaluate, stress-test, and govern these systems responsibly. This course introduces AI auditing, the systematic evaluation of AI systems across the data, model, and deployment lifecycle. Students examine issues such as bias, fairness, transparency, privacy, and robustness using a combination of computational labs and case-based analysis. Through hands-on team-based audits, students develop practical skills in documenting datasets, evaluating models, red-teaming generative AI systems, and translating technical findings into organizational recommendations. The course emphasizes AI as a sociotechnical system and prepares students to contribute to AI governance, risk management, and responsible deployment in real-world settings.