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Big Data Meets Big Law

December 27, 2012

Another organization investigating quantitative legal prediction is the Harlan Institute, a non-profit organization that promotes interest in and education about the Supreme Court.

It grew out of what started as more of a lark by Josh Blackman, a law student and self-professed Supreme Court nerd, who in 2009 launched a web-based fantasy league for predicting Supreme Court decisions (see "Place Your Bets" for more on the league). Called Fantasy SCOTUS, the site has built up a database of crowd-sourced opinions and analyses of many Supreme Court cases.

In an academic paper published in the Northwestern Journal of Technology & Intellectual Property [Vol. 10, p. 125, 2012], Blackman and co-authors suggest that Fantasy SCOTUS could combine the crowd-sourced data with data from publicly available court filings, then use an algorithm and decision engine to make predictions: "It would be quite conceivable for a bot to crawl through all of the filings in Pacer . . . and develop a comprehensive database of all aspects of how each court works."

Conceivable for a bot to do all that crawling, that is, but not necessarily easy. The one startup that is perhaps closest to achieving the promise of quantitative legal prediction, Lex Machina, has spent 10 years trying to build and organize an effective database in just one legal specialty.

The company, which was spun out of Stanford University's IP Litigation Clearinghouse, focuses on patent litigation. That's a high-value, high-cost area for corporations. Intellectual property often materially contributes to the value of a corporation, and therefore companies spend lots of money to protect and procure it. In fact, IP litigation costs are almost 62% higher than other matters and the average cost of taking a patent case to trial can hit $5 million per patent, according to a report by the Federal Judicial Center.

Lex Machina has cleaned up and organized the data in the IP Litigation Clearinghouse so that algorithms could operate on it, says Joshua Walker, co-founder and executive vice president of law and business development at Lex Machina. The database holds information from 128,000 IP cases, 134,000 attorney records, 1,399 judges, 63,000 law firms and 64,042 parties, spanning the last decade. Walker estimates that it has taken a team of engineers and lawyers some 100,000 hours to properly categorize, tag and code the information. Even putting legal rulings in the right categories was a huge challenge. The team found that the outcome coding by the administrative office of the U.S. courts was incorrect more than half the time, says Walker.

As part of its charter, Lex Machina runs and hosts the data for a "public interest" version of IP Litigation Clearinghouse, which is free to academicians, public interest researchers, judges, policymakers, and the media. Lex Machina makes revenue by advising commercial clients, who pay a fee for the insights gleaned from the database. (It also supplements the database with data on clients' legal matters.) But "the last mile of analysis," is still being done by humans rather than computers, says Walker. "Over time, we're going to automate all of it." Eventually, Walker believes this technology will have a big impact on how corporations value, manage and protect IP.

"My hypothesis is that this will . . . revolutionize how corporate finance looks at litigation," he says. "We've done a number of use cases where we've said,'Here are the settlement patterns and win rates for these companies.' "

If Walker is right, then someday a certain amount of lawyering may be reduced to simple actuary formulas. "Insurance companies do this all the time," he says. "It's just never been easy to do for complex, high-stakes litigation."

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