Can Robots Be Lawyers? Computers, Lawyers, And The Practice Of Law
University of North Carolina School of Law
At this year's SALT New York conference, Jean Hynes, the CEO of Wellington Management, took to the stage to discuss the role of active management in today's investment environment. Hynes succeeded Brendan Swords as the CEO of Wellington at the end of June after nearly 30 years at the firm. Wellington is one of the Read More
Massachusetts Institute of Technology (MIT) – Department of Urban Studies & Planning
December 30, 2015
We assess frequently-advanced arguments that automation will soon replace much of the work currently performed by lawyers. Our assessment addresses three core weaknesses in the existing literature: (i) a failure to engage with technical details to appreciate the capacities and limits of existing and emerging software; (ii) an absence of data on how lawyers divide their time among various tasks, only some of which can be automated; and (iii) inadequate consideration of whether algorithmic performance of a task conforms to the values, ideals and challenges of the legal profession.
Combining a detailed technical analysis with a unique data set on time allocation in large law firms, we estimate that automation has an impact on the demand for lawyers’ time that while measureable, is far less significant than popular accounts suggest. We then argue that the existing literature’s narrow focus on employment effects should be broadened to include the many ways in which computers are changing (as opposed to replacing) the work of lawyers. We show that the relevant evaluative and normative inquiries must begin with the ways in which computers perform various lawyering tasks differently than humans. These differences inform the desirability of automating various aspects of legal practice, while also shedding light on the core values of legal professionalism.
Can Robots Be Lawyers? Computers, Lawyers, And The Practice Of Law – Introduction
On March 14, 2011, a New York Times headline read: “Armies of Expensive Lawyers, Replaced by Cheaper Software.”1 In the article, Times technology reporter John Markoff described how computers, capable of identifying relevant words and phrases, were displacing large numbers of lawyers in discovery practice. The article posed a warning to lawyers as it sought to make a broader point: computers could replace humans in a highly educated, whitecollar occupation.
The warning is now common wisdom. Richard and Daniel Susskind argue that lawyers, among other professionals, face a future in which “increasingly capable machines, autonomously or with non-specialist users, will take on many of the tasks that are currently the realm of the professions.” Law professors John McGinnis and Russ Pearce contend that “the disruptive effect of machine intelligence” will “trigger the end of lawyers’ monopoly.” Other commentators predict that “[i]n the not-too-distant future, artificial intelligence systems will have the ability to reduce answering a legal question to the simplicity of performing a search,” and that “[o]nce we have fully artificial intelligence enhanced programs like LegalZoom, there will be no need for lawyers, aside from the highly specialized and expensive large-law-firm variety.”
Proponents of these arguments cite specific examples of computers performing lawyers’ jobs. Predictive coding, the subject of Markoff’s article, is a machine learning application that automates document classification in discovery practice. Ross Intelligence, a legal application of IBM’s Watson, advertises the ability to provide concise answers to natural language legal questions. LegalZoom, RocketLawyer, and other online legal service providers produce basic wills, divorce agreements, contracts and incorporation papers without a lawyer’s involvement.8 These technologies challenge the traditionalist view that lawyering is irreducibly human and force us to recognize that computers are changing the way law is practiced. Alone, however, they do not prove the imminent and widespread displacement of lawyers by computers. Much of the existing literature jumps to this conclusion and in doing so, foregoes the opportunity for a more nuanced and careful analysis.
In particular, the existing popular and scholarly literature suffers from three core weaknesses, which we seek to address. First, it fails to engage with technical details. We appreciate why—specifics blur the headlines and may be uninteresting to lay readers. But the details are critical for understanding the kinds of lawyering tasks that computers can and cannot perform. The details explain, for example, why document review in discovery practice is more amenable to automation than in corporate due diligence work, and why the automation of Associated Press sports stories does not suggest the imminent automation of legal brief-writing. We therefore offer a detailed review of salient legal technologies based on a set of unstructured interviews with computer scientists, legal technology developers, and practicing lawyers. We anchor our review in the present and near-term future since descriptions of artificial intelligence in a more distant future defy either proof or refutation.
Second, existing work is unmoored from data on how lawyers spend and bill their time. For example, scholars suggest that the automation of document review is displacing large numbers of junior associates without reference to the amount of time junior associates previously spent on document review. Absent such data, their conclusions remain mere speculation. We seek to offer more reliable employment predictions, grounded in lawyer time usage data provided by Huron Legal’s consulting arm, Sky Analytics.
Finally, the existing literature fails to take seriously the values, ideals, and challenges of legal professionalism. Most scholars maintain that “professionalism” is mere cover for lawyer protectionism, and that the public interest is best served by commoditizing and computerizing as many legal services as possible. Doing so, they contend, will lower costs and increase access.
Table 1: Percent of Invoiced Hours Spent on Various Tasks, Grouped by Estimated Extent of Computer Penetration
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