Applied Legal Analytics & Artificial Intelligence

Catalog description

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 Carnegie Mellon Universitys Language Technologies Institute, provides a hands-on practical introduction to the fields of artificial intelligence and law, machine learning, and natural language processing as 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 industrys 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 students of law and technical disciplines together into a collaborative classroom setting to learn about the technologies at the intersection of law and AI through lectures and programming exercises, as well as gain practical experience through collaborative project work. Topics in focus include machine learning and natural language applied to legal data, computational models of legal reasoning, and selected legal issues that relate to AI technologies. Students should come from either a (pre-) law background with a strong interest in gaining practical experience with legal analytics, or from a technical discipline with a equally strong interest in tackling the challenges posed by legal analytics tasks and data. Course Website: https://luimagroup.github.io/appliedlegalanalytics/