Text Analytics in Legal Practice: Opportunities and Challenges

Recent developments in text analytics offer new tools for legal practice. Legal text analytics employ natural language processing (NLP), statistics, and machine learning (ML) to automatically extract semantic information from archives of case decisions, contracts, or statutes. By automatically identifying the meaning of certain kinds of textual information, new apps are improving legal information retrieval. Increasingly, these techniques will identify argument-related information in legal decisions raising the possibility of ever more effectively matching documents’ substantive concepts and argument roles with those required to solve users’ particular legal problems. Eventually, the extracted information could connect Artificial Intelligence (AI) models of legal reasoning and argument directly with legal texts in predicting and explaining case outcomes. Some currently available legal apps employ or combine three text analytic techniques: machine learning, network diagrams, and question answering. This talk surveys the apps, illustrates how they intelligently combine NLP, ML, and citation networks, and evaluates how well the text analytic techniques can answer legal questions given certain inherent limitations in the technology. The talk concludes with some recommendations for the legal profession in adopting and integrating the new technologies into legal practice and education.

Presenter biography

Professor Kevin D. Ashley is an expert on computer modeling of legal reasoning and cyberspace legal issues. In 2002 he was selected as a Fellow of the American Association of Artificial Intelligence “for significant contributions in computationally modeling case-based and analogical reasoning in law and practical ethics.” He has reported his research in conference proceedings of the American Association for Artificial Intelligence, the International Association for Artificial Intelligence and Law, and the Foundation for Legal Knowledge Systems (JURIX). He has also published in journals such as Jurimetrics, the International Journal of Artificial Intelligence in Education, and Artificial Intelligence and Law, the journal of record in the field of AI and Law, of which he is a co-editor in chief. Professor Ashley has been a principal investigator of a number of National Science Foundation grants to study reasoning with cases in law and professional ethics. He is also the author of Modeling Legal Argument: Reasoning with Cases and Hypotheticals (MIT Press/Bradford Books, 1990) and of Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age (Cambridge University Press, 2017).

A former National Science Foundation Presidential Young Investigator, Professor Ashley has been a visiting scientist at the IBM Thomas J. Watson Research Center, a Senior Visiting Fellow at the Institute for Advanced Studies of the University of Bologna where he is a frequent visiting professor of the Faculty of Law, and a former President of the International Association of Artificial Intelligence and Law. In addition to his appointment at the School of Law, Professor Ashley is a senior scientist at the Learning Research and Development Center, an adjunct professor of computer science, and a faculty member of the Graduate Program in Intelligent Systems of the University of Pittsburgh.