Course: Law 5719, 3cr
Schedule: Mondays and Wednesdays 10:30-11:45am, Pitt Barco Law Building G20
Kevin D. Ashley, Professor of Law and Intelligent Systems, University of Pittsburgh
Jaromir Savelka, Data Scientist, Reed Smith LLP/Gravity Stack LLC, and PhD Candidate in Intelligent Systems, University of Pittsburgh
Technological advances are affecting the legal profession and enable innovation by experts proficient in both law and AI technology. This joint course, co-taught by instructors from the University of Pittsburgh School of Law and the School of Computing and Information, provides a hands-on practical introduction to the fields of artificial intelligence and law, machine learning, and natural language processing. The course focuses on how they are being applied to support the work of legal professionals, researchers, and administrators, such as extracting semantic information from legal documents and using it to solve legal problems. Meanwhile, LegalTech companies and startups have been tapping into the industry’s need to make large-scale document analysis tasks more efficient, and to use predictive analytics for better decision making. This course is intended to bring interested students with different backgrounds together into a collaborative classroom setting to learn about the technologies at the intersection of law and AI through lectures, class discussion of relevant material, and data analysis assignments, as well as to gain practical experience through collaborative project work. Topics focus on applying machine learning and natural language processing to legal data. Students should have a strong interest in gaining practical experience with legal analytics and tackling the challenges posed by legal analytics tasks and data.
The course will cover the following topics:
After completing this course, and depending on students’ focus in the course project, they will have gained:
The course will be a mixture of lectures and group discussions of assigned reading, for which students are required to submit short abstract hand-ins. There will also be four programming assignments. In the second half of the semester, students will form teams to work on a final project. The course ends with project presentations and a final report. There will be no midterm or final exam.
This course is designed for students with strong interest in the application of advanced analytics and AI in the practice of Law. Some background in Law, experience in programming (especially with the Python language), basic statistics, or probability would be beneficial but it is not assumed. If you are interested in taking the course and are unsure whether you are eligible or are sufficiently prepared, please contact the instructors.