Is Your Law Firm Ready for Artificial Intelligence?
Many lawyers consider themselves anything but tech savvy. They may hear the term artificial intelligence and have nightmares of robots replacing their jobs in the not-too-distant future.
But don’t be intimidated by the burgeoning legal technology market, experts say. After all, attorneys are already well acclimated to voice-activated AI, such as Apple’s Siri, Amazon’s Alexa, and Microsoft’s Cortana.
“Artificial intelligence is sort of the shiny new label re-applied to many technologies that have been around for some time,” said Maura R. Grossman, a New York solo who chairs the artificial intelligence subcommittee for the New York State Bar Association’s Committee on Technology and the Legal Profession.
For instance, some lawyers are already adept at using sophisticated search and analytics technologies for electronic discovery (commonly referred to in the industry as technology-assisted review (TAR) or predictive coding) to enhance their litigation practice.
Is your firm ready to automate repetitive tasks but unsure where to start? Legal experts have weighed in on what you should consider.
Evaluate Your Practice
“Just because the firm down the street is using something and it is right for them doesn’t mean it will be right for you,” said Grossman, who is also a research professor at the University of Waterloo in Ontario, Canada. “Rather than rushing out to buy something simply because it’s AI, you should implement a thorough vetting process. Evaluate your own practice and think about what things you can automate and what tools will save you time and money. That will vary for different types of practices.”
Once you have decided on the specific needs of your practice, do your due diligence and properly test the products in the market, Grossman advised. She said that not all products are ready for immediate use, off-the-shelf, without proper training and customization.
Grossman said next ask yourself: “What is the use case for this product? How much time will it save? What will it cost to purchase and train?”
“If everyone at the firm is a dinosaur that is resistant to change, you can bring the best technology to the table, but if you can’t get anyone to adopt it, it will not be effective,” said Grossman. “The cultural and training hurdles can be huge.”
Grossman advised speaking to a provider in your practice area and requesting a proof of concept for a few weeks to see how the tool performs in your work environment, rather than simply viewing a display or a demo from the vendor that may not be sufficiently similar to your use case. Try out two or three different products and compare the results, she said.
Like any technology, the licensing agreements may not be cheap. You want to make sure you are making the right decision before you sign on the dotted line, she said. While longer term licensing arrangements will often be cheaper, you may not want to lock yourself in to a long-term contract immediately, only to regret it six months later when the technology has advanced. Longer term licenses can range anywhere from three-to-ten years.
“Make sure you love the tool and are entitled to upgrades before you sign on for that long,” said Grossman.
TAR for e-discovery in large, document-intensive litigation was the first AI application to hit the legal industry. This allowed the mundane and time-consuming task of document review to be performed, at least in part, by a machine rather than by scores of lawyers.
Computer programs have developed to the point that lawyers can teach them to adapt when exposed to new data or patterns. This rapidly evolving technology enables computers to perform tasks once thought to be exclusive to people. Proponents say this allows lawyers sufficiently comfortable with AI to reach sound conclusions more cheaply, more accurately and faster than a lawyer could do on his or her own.
Many of the newer research tools, for example, do not require the same syntax and Boolean connectors previously needed to do legal research on Westlaw or Lexis, Grossman explained. Tools now allow users to ask natural language questions the same way you’d ask Siri or Cortana a question. You can ask what a particular law is in a certain state and it will come back with an answer. You could then say “what about Nebraska” or “compare this to Kansas” and get the results.
Grossman recently moderated a NYSBA Continuing Legal Education webinar entitled “The Growing Use of Artificial Intelligence Applications 2018.” On the panel were Scott Reents, lead attorney for data analytics at Cravath, Swaine & Moore, and Dan Meyers, a former litigator and current president of consulting and information governance with TransPerfect Legal Solutions.
Reents and Meyers likened the attorney use of predictive analytic software in their practice to Moneyball, the analytic-driven era in baseball, as depicted in the 2011 film of the same name that garnered six Academy Award nominations.
The panelists explained that the old school baseball scout would largely go on gut feelings in their assessments of a certain player when predicting future performance. Many lawyers, for example, have those same gut feelings when it comes to the judges they appear before in court, especially after doing so numerous times.
“But your 10-to-15 cases over a couple years are just the tip of the iceberg of that judge’s overall experiences,” said Meyers.
Now there is software enabling a lawyer to have every decision made by that judge at their fingertips instantaneously. But not only that, you can break the predictive analytics down to such detail as to find out whether the judge is more apt to grant a certain kind of motion or bail before or after lunch. These types of tools are also available for in-house counsel to assess who they may want to retain as a lawyer.
Don’t Forget Corporate Lawyers
Noah Waisberg, CEO and co-founder of Kira Systems, which utilizes proprietary machine learning technology to simplify review and analysis of complex documents, says corporate lawyers were the forgotten demographic when it came to legal technology. Initial applications benefited litigators.
Waisberg began his career as a corporate lawyer in mergers and acquisitions at Weil, Gotshal & Manges. In that job, he said he spent vast amounts of time reviewing contracts for corporate transactions. He said the task is repetitive and because lawyers typically do not enjoy doing it, they are prone to mistakes.
So Waisberg co-founded a company that allows AI to help with monotonous document reviews. He claims this allows lawyers to extract data out of large pools of contracts faster and more accurately in anywhere from 20 to 90 percent less time. This allows firms to take on projects that would otherwise be too big for them to handle due to staff limitations. Now a majority of the 30 largest law firms in the world do business with his company, he said.
“When you look at most big firms, there are more corporate lawyers, transaction lawyers than any other type of lawyers,” said Waisberg. “They are a forgotten but huge group of lawyers and a large task for many of them is reviewing contracts.”