COSC 89.33 The Dark Side of AI/ML: Machine Learning Security, Privacy, Fairness, and Interpretability

The goal of this course is to equip students to responsibly deploy machine learning tools in an unfair and adversarial world. We will survey the vulnerabilities of mainstream machine learning models and algorithms to manipulation, privacy leakage, and unfairness. We will then assess the conditions under which we can understand, interpret, or measure our models’ predictions with respect to each of these vulnerabilities. Finally, we will address the feasibility and limitations of appropriate countermeasures. Our course will build towards a final project assignment where students are given the opportunity to develop their own research projects in this emerging field.

Degree Requirement Attributes

Dist:TAS

The Timetable of Class Meetings contains the most up-to-date information about a course. It includes not only the meeting time and instructor, but also its official distributive and/or world culture designation. This information supersedes any information you may see elsewhere, to include what may appear in this ORC/Catalog or on a department/program website. Note that course attributes may change term to term therefore those in effect are those (only) during the term in which you enroll in the course.

Department-Specific Course Categories

Computer Science