As is evidenced by the associated AI, Ethics and Society conference, we now take as given the need for ethics education in the AI and general CS curricula. The anticipated surge in AI ethics education will force the field to reckon with delineating and then evaluating learner outcomes to determine what is working and improve what is not. We argue for a more descriptive than normative focus of this ethics education, and propose the development of assessments that can measure descriptive ethical thinking about AI. Such an assessment tool for measuring ethical reasoning capacity in CS contexts must be designed to produce reliable scores for which there is established validity evidence concerning their interpretation and use.

The national push for CS departments to teach students to think about ethical implications of their work raises critical questions about how we approach this pedagogically. In contrast to the typical assessments of CS ethical thinking, which have focused on a student's ability to operate successfully within one kind of normative paradigm, our research group advocates for teaching ethics as an ongoing practice that incorporates multiple normative frameworks and an emphasis on the descriptive element of ethical reflection. In this special session, we will discuss the differences between normative and descriptive ethics, practice describing ethical dilemmas, and work together on developing assessment capabilities for descriptive ethical thinking for CS.