Applied Natural Language Processing for Law Practice

40 Pages Posted: 8 Nov 2019 Last revised: 10 Nov 2019

Date Written: October 27, 2019

Abstract

Scholars, lawyers, and commentators are now 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. Indeed, the Internet, email, and databases like Westlaw and Lexis have been altering legal practice for decades. Further, the technology at the cutting edge of AI in law practice has been around since the early twentieth century. Indeed, the dynamics of legal technology are defined by the organization and quality of data, rather than innovation.

Despite the evolution of technology across other industries, in many ways the practice of law remains static in its essential functions. 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.

Keywords: machine learning, law, artificial intelligence, natural language processing

Suggested Citation

Haney, Brian Seamus, Applied Natural Language Processing for Law Practice (October 27, 2019). Available at SSRN: https://ssrn.com/abstract=3476351 or http://dx.doi.org/10.2139/ssrn.3476351

Brian Seamus Haney (Contact Author)

Independent ( email )

No Address Available
United States

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