This course prepares engineers to reason about and design responsible AI systems by examining ethical issues. Students will study the ethical use of data, including human subjects, human data, and privacy; analyze what can go wrong in AI systems through structured discussions of AI risks; and build an ethical framework grounded in philosophical foundations and algorithmic fairness. The course then turns to societal impacts of AI, including effects on employment and the future of work, community impact and community engagement, factuality and misinformation, and emotional harms to users. In the final portion of the course, students will examine how ethical AI principles are translated into practice through theory of change, institutions, partnerships, and policy. Through a semester-long group research project on a topic of their choice, students will apply these concepts to real-world challenges. In addition to ethical analysis, this course emphasizes how ethical principles can be operationalized through design choices and institutional mechanisms. This is a discussion-based class with numerous readings, discussion, and debates.
Course Objectives: Upon completion of this course, students will be able to:
Relevant Courses at Hopkins: This course has some overlap with "AI Ethics and Social Impact" (offered in the fall semesters) (EN.601.770), though it is less advanced.
Thank you to Monica Lopez-Gonzalez for having taught earlier versions of this class, Yulia Tsvetkov for sharing class materials, and Daniel Khashabi for sharing the course website template!
