IEEE Spectrum has a lengthy profile about the magic going down at Lex Machina.
Here, a small group of patent lawyers and computer scientists is applying the latest in machine learning and natural-language processing to reams of documents related to intellectual property lawsuits. The result is a massive statistical database on IP litigation like nothing the world has seen before. Which attorney has the best track record in defending against semiconductor-related infringement claims? Has a particular judge ruled on cases involving patent trolls, and if so, what was the outcome? Which companies tend to go to trial, and which settle out of court? By offering up such information, the database provides corporate lawyers, law firms, and government agencies with hard numbers that will reduce the guesswork, as well as the enormous expense, of patent litigation. In short, the company is building a “law machine,” from which comes its name:Lex Machina.
Plus a quote from Dan Katz:
Lex Machina is in the vanguard of an emerging field known as legal analytics, according to Daniel Martin Katz, an associate professor of law at Michigan State University who writes the blog Computational Legal Studies and advocates overhauling the practice of law through technology. Practitioners of legal analytics statistically parse the practice of law in search of data that can be used to augment, or in some cases replace, the more qualitative judgment of human lawyers.
“Humans are limited. People haven’t seen 10 000 cases or 100 000 cases—a human can’t hold that kind of information,” Katz says.
But Lex Machina can. For an annual subscription fee of around $50 000, its customers get access to 13 years of U.S. IP litigation. Just like the sabermetrics described in Moneyball, Lex Machina’s database can aid in the formulation of broad strategy as well as the selection of players, says Becker. The company’s stats reveal, among other things, which attorneys do the best against a particular patent troll, how much time and money it typically takes to fight a troll versus settling out of court, and even which judge you’d want to hear your case. The data might tell a company being sued that its peers have been settling similar lawsuits early, thereby saving money. Even if a company believes it’s in the right, says Becker, a prolonged legal battle and “fighting to the death” may not make good business sense.
“There’s been a quiet transition going on in the legal world,” Katz says. And that transition will shake up the legal profession. “Human reasoning, at least some part of it, is going to be replaced by machine-based prediction.” If Lex Machina succeeds, there will eventually be fewer frivolous lawsuits—and maybe fewer lawyers too.
More great reporting from Tam Herbert. Relatedly, check out this article from FastCompany about the application of Watson to medical purposes.