Teaching AI Ethics and Governance to the Next Generation of Engineers and Designers

Ethics has long been treated as something you add to an engineering or design curriculum: a guest lecture, a module in the final semester, a case study that appears once and is never revisited. Generative AI will make that approach impossible to sustain. The technical and societal stakes will keep rising, and the tools will become more embedded in everyday student work, so ethics will have to move from the side of the curriculum into its center.

At AAC&U's Conference on AI and Higher Education, I will share my learnings based on teaching in this manner since fall of 2023. The session is built around a simple premise: ethical reasoning must be woven through classwork and program design, not bolted on at the end. We can ask students to consider how a system’s technical choices, its social context, and its accountability structures shape one another.

Over the past few years I have taught students about generative and, increasingly, agentic AI four times. The courses span graduate and undergraduate students, engineering, design, and policy disciplines, and classrooms in the United States and Germany. Some were taught solo and some were co-taught. Because the technology, and the policy and social conversation around it, changed so quickly, each iteration had to be substantially rebuilt.

What I'm sharing

I will present the contents of this project in more detail, including the course designs, what changed between iterations, and what I learned about where students struggled and where they engaged most. I am especially interested in the tension between giving students access to powerful tools and making sure they still do the reasoning themselves.

I'd welcome conversation with others working through the same questions, whether you are changing one course or a whole program.