Brendan Johnson (University of Minnesota Law School) and Francis X. Shen (University of Minnesota Law School, Harvard University - Department of Psychiatry) have published "Teaching Law and Artificial Intelligence" on SSRN. Here is the abstract:
In this Essay we present the first detailed analysis of how U.S. law schools are beginning to offer more courses in Law and Artificial Intelligence. Based on a review of 197 law school course catalogs available online, we find that 26% of law schools offer at least one course with significant coverage of Law & AI, and that 13% of schools offer more than one such course. Analysis of the data suggests that Law & AI courses are more likely to be offered at higher ranked law schools.
Based on this analysis, and in light of the growing importance of AI in legal domains, we offer four recommendations. First, for those schools that do not currently offer a course, we advocate for creation of at least one introductory course that directly engages AI issues. For those schools that already have an introductory course, we suggest that AI issues be more broadly engaged throughout the curriculum. Third, to facilitate these two goals, we argue that law schools must continue to improve interdisciplinary partnerships with other university departments and local institutions that can provide expertise in AI and machine learning. Finally, to catalyze law school investment in this area, we suggest that U.S. News and World Report create a new ranking category: Best Law & AI Programs.
The Essay is organized in five parts. After a brief introduction in Part I, we proceed in Part II to introduce our new data-base of current U.S. law school course offerings in Law & AI. We describe the methods we used to search and code courses, and make available for readers a google sheet database providing key details on each course such as instructor, credit hours, and course description. We identify 115 courses for inclusion in the database. Part III discusses the findings gleaned from the database and offers our core recommendations. In Part IV, we present a User’s Guide to Teaching Law & AI, with insights from both professor and student perspectives on what strategies can be used to develop an effective Law & AI course. Part V concludes.
Comments