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Computational Legal Research and the Advocates of the Future

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Document pages: 7 pages

Abstract: Artificial intelligence and machine learning grab headlines these days, and for good reason. Consider the remarkable developments that machine learning has made in the past decade. Many of us have come to expect instantaneous access to all of the world’s knowledge with search engines. Logistics companies use machine learning to optimize supply chains in ways that were unthinkable in years past. Online retailers make suggestions about what consumers might like to buy based on past browsing activity, generating billions in additional revenues annually. Autonomous vehicles are on the road in many jurisdictions and are predicted to be mainstream within the next ten years. In the legal realm, various popular and legal publications include headlines that use sci-fi terms like “robot lawyer” and sensationalize the use of computing power and algorithms in the legal profession. All of this appears to blend reality with science fiction, and to combine software engineering with hype and marketing bluster. Lawyers typically react to media accounts of these developments in one of two, polar opposite ways. Some confidently dismiss the hype around legal technology and take the position that artificial intelligence will never replicate precisely what they can do as advocates and so conclude that there is nothing at all that they should even consider changing about what they do and how they do it. Others are anxious about the advent of machine learning and artificial intelligence and what it might mean for their own work and the future of the profession more generally. This anxiety is fomented by a sense of helplessness: that there is nothing in particular that they feel they can do to prepare themselves for developments that have had and will continue have significant impact on other industries (e.g., transportation). Both reactions are understandable; each has some merit. Neither, however, captures the full story.

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