The University of Pittsburgh School of Law seeks a co-instructor for Applied Legal Data Analytics & AI (which will be led by Professor Kevin Ashley).

Course Description: APPLIED LEGAL DATA ANALYTICS & AI – Spring 2024

Technological advances are affecting the legal profession. While it is hard to predict the changes that machine learning and natural language processing will bring, legal professionals certainly will need to understand the new techniques and how to use and evaluate them. This joint course, co-taught by instructors from the University of Pittsburgh School of Law and Carnegie Mellon University's Language Technologies Institute, provides a hands-on practical introduction to the fields of artificial intelligence, machine learning, and natural language processing as they are being applied to support the work of legal professionals, researchers, and administrators. Researchers in the field of Artificial Intelligence and Law (AI & Law) have been applying recent advances in natural language processing and machine learning to extract semantic information from legal documents and to use it to solve legal problems. Meanwhile, the commercial legal tech sector is thriving. Companies and startups have been tapping into the legal industry's need to make large-scale document analysis tasks more efficient and to use predictive analytics for better decision-making. This course will help law students gain literacy with these technologies and learn how to apply them to the kinds of legal problems they have studied or will encounter in practice. This course not only teaches law students about the new tools but enables students to gain practical experience using them under close mentorship and in project-based collaboration with students from computer science backgrounds who want to learn about the law. Lecture sessions will alternate with working sessions where instructors assist groups with projects.

Salary: $1,500

Qualifications: Juris Doctor degree; graduate-level teaching experience preferred; 5 years or more of practical experience preferred.

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