Artificial Intelligence (AI) Industries Interview Legal Technologies

Blue J Legal: Predicting Litigation Outcomes Through Machine Learning

Blue J Legal: Predicting Litigation Outcomes Through Machine Learning 27/11/2017
Blue J Legal Predicting Litigation Outcomes Through Machine Learning

Photo Credit: Le Moal Olivier/123RF

This post is part of our Future of Law series which interviews the leading founders and executives who are on the front lines of the industry to get a better understanding of what problems the industry is facing, what trends are taking place, and what the future looks like.

The following is an interview we recently had with Benjamin Alarie, Co-Founder and CEO of Blue J Legal.


1. What’s the history of Blue J Legal? Where and how did you begin?

BA: About three years ago I became completely fascinated by what is going to be happening in the law over the course of the next several decades. It all started innocently enough in December 2014. As associate dean at the University of Toronto Faculty of Law, I was sitting at my desk at the law school. The dean’s assistant, Judith, called. She asked me, “are you free next week? There’s an event happening at the computer science department. The dean can’t make it. You’re the associate dean, so you’re the next one on my list.”

I checked and I was available and so I found myself the following week at the computer science building on St George Street. I served on a panel of judges who were being asked to select the best team of undergraduate CS students to advance to the finals of something that IBM was billing as the IBM Watson challenge. All of the University of Toronto teams had focused on developing different tools based on Watson that would help with legal issues. One team had developed the idea for something in family law. Another had tackled immigration law as the target domain. A few teams had identified “legal research” as the general problem that they would aim to address using Watson.

I was fascinated and immediately thought of tax as being an area of law that would be suitable for using artificial intelligence and machine learning. I approached the instructors after the event and asked if they would be willing to work with me to offer a seminar course that would explore the use of AI and machine learning in tax. They agreed, so long as I did all the work. That was fair since it was my idea after all. Afterwards, as I walked back across campus to the law school, my mind turned to what other faculty members at the law school would be interested in AI and the law and, more problematically, how I might be able to get them interested in Canadian income tax law.

Two friends and law professor colleagues with stats backgrounds and interests in judicial decision-making got interested, so we offered an ad hoc seminar course on tax law and AI. By the end of the semester, we had developed an admittedly pretty terrible prototype of the software but had lots of ideas about ways that we might be able to improve the training approach for the AI and ideas about how to expand its scope. So at the end of the semester, we disclosed our invention to the university and incorporated Blue J Legal, with the university becoming a non-voting minority shareholder in the company. Our first product is Tax Foresight, an AI platform that predicts outcomes in frequently litigated tax issues. It is currently being marketed in Canada by Thomson Reuters.

2. What specific problem does Blue J Legal solve? How do you solve it?

BA: We use machine learning models to predict litigation outcomes. Lawyers, accountants, and government departments use our software to figure out how to best comply with and administer the tax system.

3. What’s the future of law?

Prediction #1: AI will be a game changer in the law as consequential as the invention of the Gutenberg printing press in 1440.

Prediction #2: We will soon see an accelerating rate of complexity in the law, as AI-guide refinements get codified.

Prediction #3: Eventually the law will be so complex as to be nearly inscrutable to anyone not using computational assistance (it will be like looking at the source code for an O/S).

Blue J Legal

4. What are the top 3 technologies trends you’re seeing in the legal industry?

Trend #1: eDiscovery is becoming very mature and widespread.

Trend #2: Firms are using algorithms to adjust their billing practices.

Trend #3: Lawyers are increasingly relying on predictive systems to inform their advice to clients.

Blue J Legal

5. Why is the legal industry ripe for disruption?

BA: Computing power is increasing exponentially and this is having repercussions across all industries. Law is not immune. 

About Benjamin Alarie

Benjamin is CEO of Blue J Legal and holds the Osler Chair in Business Law at the Faculty of Law at the University of Toronto. Before joining the University of Toronto as a full-time professor in 2004, he completed graduate work in economics at the University of Toronto, graduate work in law at the Yale Law School and was a law clerk for Madam Justice Louise Arbour at the Supreme Court of Canada. He has dozens of academic publications, including several editions of a leading text on tax law, Canadian Income Tax Law. He is a past-president of the Canadian Law and Economics Association and served as Associate Dean of the Faculty of Law at the University of Toronto from 2011-2015. In 2015, Benjamin co-founded Blue J Legal with two other professors from the University of Toronto to bring artificial intelligence and machine learning to the law.

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