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Takeaways from the Emerging Legal Technology Forum

On September 20, Thomson Reuters and MaRS LegalX presented the Emerging Legal Technology Forum to a filled auditorium in the MaRS Discovery District. The purpose of the forum was to examine how technology is currently being used within law firms, how contract and document automation is changing transactional practice, the design change requirements to leverage technology to improve delivery of legal services, and the power in leveraging legal data analytics.

The day began with Aron Solomon and Jason Moyse of LegalX welcoming everyone to the event and discussing what we, as attendees, could expect from the forum. During the introduction, Marvin Minsky, a Professor from MIT, was quoted for saying “you don’t understand anything until you learn it more than one way” – a quote which I believe accurately summarizes the discussions of the forum.

The quote is particularly suitable as much of the forum focused on the stagnant nature of the legal field. In other words, because the legal market is operating in a precedential, non-evolutionary scheme, without a focus on how technology can be used to improve it, those currently directing the legal field “don’t understand it” because they have only learned it the traditional way. As such, the forum discussions focused on how the implementation of technology – a new way of learning – could solve many of the issues arising in the legal field.

Daniel Katz, Associate Professor of Law at Illinois Institute of Technology Chicago-Kent College of Law, was the keynote speaker and discussed how we might re-make the legal profession through an understanding of risk. In this discussion, Katz stated that a great lawyer will price risk, and in order to accurately price risk one must be able to predict outcomes. Being able to price risk makes for a great lawyer, as a proper prediction of risk will lower legal fees for clients. To explain this concept, Katz gave the example of a lawyer spending multiple hours amending a single clause of a contract which may cost a client, say, $1,000 in labour fees. However, if one were to determine the “price” of the risk associated with a contract without the amended clause, one might realize that the maximum liability for the client is $100. As such, a great lawyer would properly price the risk, and conclude that it would be in the best interest of the client to not amend the clause.

Accordingly, Katz argued that to revolutionize law we need to be able to predict outcomes in order to price risk, and to do so we need to keep the artisan features of the law, but add scientific functions. There are three ways to predict any outcome – experts, crowds, and algorithms – and the combination of the three will always outperform an independent prediction method.

Further examples of how technology can be used to improve the legal market were then discussed by expert-filled panels from all areas of the legal profession. The panels provided a balanced, in-depth, and at times passionate, debate about topics such as contract automation, design thinking, and data analytics. From each panel, the attendees were exposed to examples of technologies that have either succeeded or failed in the legal market, as well as insights into the technological desires of progressive law firms and clients.

Although the topics discussed by each panel were centred on various forms of technology which could improve the legal field, many of the questions posed by the audience focused on the implementation and application of such technologies. It seemed that many attendees saw the potential of the technology, but could not foresee what would influence the legal market to adopt these technologies.

However, any doubts were soon erased by Fred Headon, Assistant General Counsel at Air Canada. During the contract automation panel, Headon straightforwardly stated that clients will force law firms to evolve. He stated that a company like Air Canada will expect a law firm to be able to implement the same technology they do. Furthermore, he added that a client that can make airplanes fly would not understand an inability to automate a contract, and such a client would therefore find a law firm willing and able to cut costs accordingly.

Overall, the Emerging Legal Technology Forum was an amazing event full of insightful ideas about how we might see the legal market change in the years to come. However, it was not only the speakers who made this forum such a success. The lunch break and reception were full of lively discussions on the topics of the day. Furthermore, many of the attendees took advantage of the event’s Twitter page by sharing their thoughts of the event with the hashtag #trlegalx.

 

Denver Bandstra is a JD Candidate at Osgoode Hall Law School.

 

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One Response

  1. Great article Denver. There are several legal tech startups working on statistical and predictive models that are data-driven to help price legal services and litigation risk. PredictGov (http://predictgov.com/) helps lawyers and lawmakers predict whether a particular piece of legislation will become law. Docket Alarm (https://www.docketalarm.com/) is designed to look at the potential outcomes for litigation, including the particular profile for settlement. In the intellectual property field, Lex Machina (https://lexmachina.com/) provides analytics that are helpful for assessing risk.

    It is a great value proposition to be able to identify, predict and price risk. For enterprise clients, it means not only cutting costs but also guiding strategic business decisions. For smaller clients, risk pricing helps focus limited resources on the most important legal matters. For law firms, these predictions offer strategic information about opposing parties.

    To objectively price risk, a significant number of data points are required from a variety of different activities. Katz makes a great point that it’s critical for law firms and organizations to capture data about their practices. This type of work is particularly unglamorous (the New York Times referred to it as ‘Data Janitor’ work — http://www.nytimes.com/2014/08/18/technology/for-big-data-scientists-hurdle-to-insights-is-janitor-work.html?_r=1), but it is critically important to enable predictive actions in the future, including both procedural predictions and substantive legal predictions.

    I have been studying this semester at CodeX at Stanford. If you’re interested in more information about legal tech community, check out the CodeX Youtube channel: https://www.youtube.com/playlist?list=PL48E61C121CAD0E1B

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