Hod et al. on Data Science Meets Law in the Classroom

Shlomi Hod (Boston University), Karni Chagal-Feferkorn (University of Ottawa Common Law Section), Niva Elkin-Koren (Tel-Aviv University – Faculty of Law), and Avigdor Gal (Technion-Israel Institute of Technology) have posted “Data Science Meets Law” (65 Communications of the ACM, 2022) on SSRN. Here is the abstract:

Engaging lawyers and data scientists in multi-disciplinary dialogue may result in the design of better AI systems. Combining the joint input of these two disciplines as early as possible in the life cycle of AI systems may help in properly embedding human values in these systems and in minimizing their risks of unintended harms.

Lawyers and data scientists, however, often think of the other discipline as “speaking a different language”, and facilitating dialogue between them is not always trivial.

This paper describes a “hands on” course taught to both law and data science students in academic institutions in the U.S., Europe and Israel. The unique format of the course, which is based on students working in small mixed groups, enables meaningful dialogue between the disciplines and is intended to contribute to the design of “responsible AI” systems.

In the paper we share the pedagogic principles that guided us as well as insights on how to foster multi disciplinary dialogue between law and data science students.