Supercharging Patent Lawyers With AI
Professor Mark Lemley is quoted on the development of Lex Machina, a company that could revolutionize IP law research, in IEEE Spectrum.
In a low-rise building in Menlo Park, Calif., just upstairs from a Mexican restaurant and a nail salon, a Stanford University spin-off is crunching data in ways that could shake the foundations of the legal profession.
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.
“Law is horribly inefficient,” says Mark Lemley, a professor at Stanford Law School, director of the Stanford Program in Law, Science & Technology, and cofounder of the company. “And in some ways, it is inefficient by design.” After all, lawyers get paid by the hour, so inefficiency is rewarded, says Lemley. And some are rewarded richly: Top lawyers charge north of US $1000 per hour.
We’re the moneyball of IP litigation,” says Josh Becker, Lex Machina’s CEO. Bespectacled and unassuming, he looks more like a professor than a savvy Silicon Valley player. With law and MBA degrees from Stanford, he served as press secretary for a Pennsylvania congresswoman, worked at the Internet start-up EarthWeb/DICE and at Netscape, and founded a venture capital firm before turning his attention to Lex Machina.
That approach is basically what Lex Machina is doing for law. But while baseball is known for its reliance on statistics, Becker says, law has long been a profession that is more art than science. “Some people went to law school to avoid data,” he quips.
Lex Machina aims to change that. According to the company, its database covers more than 130 000 U.S. IP and antitrust cases dating back to the year 2000, including information on more than 1400 judges, 340 000 litigants, 100 000 attorneys, and 30 000 law firms. At present, it covers only the United States, but it may eventually include international patent cases as well.
So how does Lex Machina do what it does? It started with documents—millions of pages of legal documents that, in theory at least, are available to anyone, free of charge. In practice, though, before Lex Machina came along, there was no easy way to collectively consider that vast body of information. Figuring out how to extract relevant data from countless files and then building a comprehensive database took years of dedicated effort on the part of Lex Machina’s small and eclectic team. Among its 18 employees are 6 people with law degrees, 6 with computer science degrees, and 1 who has both.
The company began as an academic research project called the Intellectual Property Litigation Clearinghouse, launched by Lemley in 2006 as a collaboration between Stanford’s law school and its computer science department. As Lemley explained during an interview on the sunny terrace of Stanford Law’s William H. Neukom Building, “The industry was having all these debates about how to fix the patent system, and none of them were based on actual evidence.”
Lemley hoped that a law database would foster decisions based on fact rather than assumption. The tech industry was enthusiastic about the project, as evidenced by more than $3.5 million in donations from companies like Apple, Cisco, and Microsoft, as well as several law firms, the Kauffman Foundation, and Stanford Law School. Lemley recruited Joshua Walker, a cofounder of CodeX: The Stanford Center for Legal Informatics. Walker in turn hired George Gregory, then a Stanford graduate student with expertise in natural-language processing and machine learning.
It’s not just about the bottom line, though. Lex Machina gives its data, at no charge, to courts, government agencies, academic institutions, and media outlets. That’s an important part of fulfilling the mission of Lemley’s original research project: improving the legal system.
“In the short term, people will think more intelligently about whether to file suit or when they get sued, how to react: What lawyer should they hire? Should they settle the case early?” says Lemley. Ultimately, he says, people will be able to make informed decisions, not just in individual lawsuits but also in shaping policy and in bringing badly needed reform to the patent system. “My hope is that once everyone has access to the data, some number of lawsuits will go away.”