legal tech law machine learning artificial intelligence legal singularity

The Path to the Legal Singularity

August 24, 2018 | by Lisa Cumming

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This is Part One of a new series based on the TEDx talk, Transcending Books: What’s Next For Law and Society, given by Blue J Legal's CEO, Benjamin Alarie. 

When Benjamin Alarie, co-founder and CEO of Blue J Legal, first entered law school at the University of Toronto in 1999, he was given an assignment that asked him to conduct research using only printed sources. This “paper chase” in the law school library took several hours.

Fast-forward two weeks and Alarie was sitting in a computer lab in the same law school library, accessing all of those paper sources online. “My mind was blown,” says Alarie. “It was so much easier to find what we were looking for than chasing through the stacks, fighting over books.”

Now that legal research databases are at their disposal, law students today may not recognize this form of research that Alarie speaks of, spending hours upon hours looking through paper sources. Senior lawyers today probably do remember this research method, but wouldn’t recognize it in their own practice.

“We reached peak law book in the North American legal system in about the year 1999,” Alarie says, speaking about how that moment in time was the turning point for lawyers and law students in how they conducted legal research.

Alarie recently gave a TEDx talk, Transcending Books: What’s Next For Law and Society, where he explored how advanced tools, like Blue J Legal’s Tax Foresight and Employment Foresight, are stepping stones to eliminating legal uncertainty.

The introduction of artificial intelligence to legal research has allowed lawyers who utilize these new tools to not only conduct their legal research faster, but also gain additional insights into their clients’ cases.

In his TEDx talk, Alarie outlines in a five-step process how the development of legal tech is unfolding, and where it’s going.

Step One: Recording

The first step involves the translation of legal information from paper to digital formats.

Starting in the 1960s and 1970s, courts began to undertake this process of digitizing materials that used to just be in books, says Alarie. Nowadays, many judgements from courts and most new legislation is stored as digital files.

“Stage one is still ongoing, by the way. There are huge projects digitizing the past repository of primary and secondary literature in law,” he says.

Step Two: Linking and Dissemination

According to Alarie, the next step after translation is dissemination, or making that translated information — current and historic — accessible anywhere and available in real-time.

Big steps in this movement include the introduction of Lexis (now LexisNexis) in 1973 and the 1988 decision by the Judicial Conference of the United States to use PACER (Public Access to Court Electronic Records).

But simply making materials available isn’t enough, says Alarie. “Yes, you can find information more quickly and, you can find it from anywhere, but it’s relatively uncreative since words have migrated from pages of books on to screens.”

With great access to information come great problems with managing that information. So, how can lawyers not lose themselves in this sea of widely accessible and available information?

The answer is artificial intelligence.

Step Three: Synthesizing

The application of artificial intelligence to legal research is the third step of this five-step process, and it’s the stage that Blue J Legal is in now with Tax Foresight and Employment Foresight.

The software uses court judgments as training data for algorithms that predict outcomes of many different types of tax and employment law disputes with up to 94% accuracy.

“It’s a very, very powerful approach to predicting legal outcomes.” Alarie says.

Rather than have a lawyer sit with a handful of leading cases on a topic in an attempt to try to reason how a court may apply the precedents in the client’s situation, this software generates predictions based on all of the past cases that involve similar disputes.

Alarie says that over the next several years this application of artificial intelligence to legal research is going to happen across all areas of the law, globally.

“Our vision is to bring absolute clarity to every area of the law, everywhere and on demand.”  

Step Four: Reforming the Law

Stage four, which we haven’t hit yet, involves a big clean up of the law after artificial intelligence has been applied to it. At this stage, humans will notice deeply troubling inconsistencies.

Alarie says that when the “stage three” of legal technology matures, it will become apparent that the legal system is in need of significant and perhaps painful reform. This step is where society uses this improved understanding of the law and its consequences to work to build a version of our legal system where access is equitably distributed and the judgments are more consistent.

“I think it’s going to kick off a very serious look at law reforms in a number of dimensions,” he says.

Step Five: The Legal Singularity

The last step in this process, step five, has to do with the eradication of uncertainty within law. This stage Alarie refers to as the “the legal singularity.”

The legal singularity is the point where the legal system turns into a “self-referential system” that is able to generate its own answers to certain legal questions on demand. In the legal singularity, uncertainty in the law is eliminated and the legal system becomes “more transparent, more accessible, more fair, and more just.”

The future of the law belongs to computing, says Alarie. This changing legal sphere will usher in dramatic changes for every aspect of practice in every area of law. These changes have the potential to dramatically reshape how lawyers interact with the law on a fundamental level, ultimately pushing the legal system to function extraordinarily well, virtually automatically.  

Tags: legal tech law machine learning artificial intelligence legal singularity


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