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Applied Natural Language Processing for Law Practice
Abstract
Scholars, lawyers, and commentators are predicting the end of the legal profession, citing specific examples of artificial intelligence (AI) systems out-performing lawyers in certain legal tasks. Yet, technology’s role in the practice of law is nothing new. The Internet, email, and databases like Westlaw and Lexis have been altering legal practice for decades. Despite technology’s evolution across other industries, in many ways the practice of law remains static in its essential functions.
The dynamics of legal technology are defined by the organization and quality of data, rather than innovation. This Article explores the state-of-the-art in AI applications in law practice, offering three main contributions to legal scholarship. First, this Article explores various methods of natural language database generation and normalization. Second, this Article provides the first analysis of two types of machine learning models in law practice, deep reinforcement learning and the Transformer. Third, this Article introduces a novel natural language processing algorithm for legal writing.
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Brian S. Haney, Applied Natural Language Processing for Law Practice, 2020 B.C. INTELL. PROP. & TECH. F. (2020), available at SSRN: https://ssrn.com/abstract=3476351