Legal Text Analytics and its Role in AI and Law
Traditionally, the field of AI and Law has focused on representing legal knowledge in ways that computers can use to perform legal reasoning, or something like it, with legally intelligible results. Today, the research paradigm in AI and Law has largely shifted to applying new machine learning (ML) and natural language processing techniques to legal texts. These text analytic techniques use statistical means to extract semantic information from archives of legal case decisions, contracts, or statutes. Although for some time ML models have been predicting outcomes of cases directly from textual descriptions of the facts, they cannot yet explain their predictions or support them with arguments.
This talk will briefly explain some basic mechanisms of text analytics and their application in legal practice and describe some recent research efforts to tease additional elements of meaning from legal text, including concepts and argument structures. These methods can improve legal information retrieval, may eventually enable ML models to explain and justify their results, and contribute new methods in empirical legal research.
Date and Time
- Date: 19 May 2022
- Time: 08:00 PM to 09:30 PM
- All times are (UTC-05:00) Eastern Time (US & Canada)
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Kevin D. Ashley
Kevin D. Ashley is a professor of Law and an adjunct professor of Computer Science at University of Pittsburgh. He received his law degree from Harvard University and his PhD in Computer Science from the University of Massachusetts at Amherst. Kevin is also a senior scientist at the Learning Research and Development Center, and a faculty member of the Graduate Program in Intelligent Systems of the University of Pittsburgh. 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." Kevin is a former President of the International Association of Artificial Intelligence and Law, and he is currently co-editor in chief of the journal Artificial Intelligence and Law. He is the author of a 2017 book, Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age.