My Crystal Ball: Legal Grappling with How to Adopt Predictive Technology
Richard Susskind writes that through predictive technology, 'we might gain insight into the greatest legal risks that specific sectors face.' But a number of barriers still stand before widespread adoption.
October 17, 2017 at 05:27 PM
9 minute read
Four years ago, Richard Susskind published the first edition of “Tomorrow's Lawyers: An Introduction to Your Future.” With the rapid changes in the legal profession, tomorrow is now today.
The second edition of “Tomorrow's Lawyers” focuses more sharply on how artificial intelligence, alternative business structures, low-cost law firm service centers, legal tech startups and evolving in-house roles are changing the way legal services are delivered and how law schools are educating students to meet those changes.
To that end, ALM during October is publishing excerpts across several of our brands from the second edition to spark thought and conversation about the industry's future among the legal profession's leaders. ALM editors and reporters have solicited reactions—positive and negative—to Susskind's ideas from law firm chairs, top legal educators, general counsel, law students and industry analysts to get their take.
The book's section on artificial intelligence, discussed below, can be found here.
Here's a prediction: The legal world is still a long way from getting its hands around legal predictions. But it's not because of the technology available, but rather how that technology is being applied practically in the modern legal practice.
Richard Susskind's book “Tomorrow's Lawyers” explores in part the future of using data to make predictions, a revolution already underway at many law firms and legal departments. Susskind notes:
Much legal work involves prediction, whether of the likelihood of winning a case or negotiating a settlement, or of a deal being abandoned or completed. The data held within law firms' systems, along with publicly accessible data, will no doubt form the basis of future predictions in relation to such issues. More than this, by aggregating data sets, we will soon be able to find out what legal issues and concerns are troubling particular communities; by analysing the work of regulators, we may be able to predict compliance outcomes in entirely novel ways; and by collecting huge bodies of commercial contracts and exchanges of emails, we might gain insight into the greatest legal risks that specific sectors face.
This rise in analytic thinking has been underway for years, and LTN has covered it from the beginning. But over the past year, there's one refrain that has occurred with more frequency: the idea of change management. Having the data is great, but how exactly can law departments leverage it in a way that both benefits and is intuitive to attorneys?
|Adopting the Change
It's not as easy as you may think. In his book, Susskind references the work of scientist, technologist and Chicago-Kent law professor Daniel Katz, writing, “[A]s the work of Daniel Katz is showing in relation to the US Supreme Court, computational statistics (crudely, algorithms working on large bodies of data) can often yield more accurate predictions of the likely behaviour of courts than the predictions of lawyers engaged in traditional legal research and reasoning.”
Speaking with LTN last week, though, Katz says that even if the data is there, the problem for many legal organizations looking to utilize this data is one of monetization.
“Even if I'm 5 percent better than you are, that only takes me so far if I can't find a way to monetize that. For example, I'm a law firm, and you're a law firm. Let's stipulate that I'm 5 percent better at predicting than you are. What does that do for me?” Katz asks. He posits that 5 percent better may only be notable in an industry that relies heavily on the legal department for everyday work product, such as insurance or finance.
He later adds, “In regular service delivery, it only matters if the client cares, if they're really focused on it and can make an intelligent evaluation. Otherwise, it's very unclear whether it does a whole lot to me, actually.”
That then begs the question: What exactly makes a client care? Understanding can help, but many attorneys still don't understand how exactly current predictive models function, and the gains from current models are not great enough to abandon long-held anecdotal beliefs. Mark Michels, a director in the Discovery practice of Deloitte Transactions and Business Analytics, said this lack of understanding can lead to a “lack of confidence in their predictive capabilities.” But there is hope that this can change.
“We saw that with predictive coding, where it took time for it to be adopted broadly,” he explained. “Dissecting algorithms to understand how they worked wasn't really an option for most users. Over time, as confidence in the results grew, the relevant community began to embrace the technology. I expect that we may see the same pattern with other predictive technologies.”
Even technology companies themselves are seeing these adoption struggles. Serena Wellen, senior director of research information with LexisNexis, said that while there is “a clear uptick in the number of law firms and in-house departments utilizing analytics,” there remains “still some skepticism concerning predictive analytics” in her view.
“Some lawyers don't immediately grasp how the technologies used in predictive analytics work, so they are understandably wary of the conclusions and have trouble relying on—and staking their reputations on—something they don't entirely understand or feel that they can't control. We are listening to the concerns of these customers, and we are designing our analytics products to be more user-friendly and transparent,” she explains.
And that transparency can help drive conversations to not only help technologies be understood, but ultimately adopted. While the monetary factor is important, Katz explained that even more factors are often at play when adopting these technologies. In the tech industry for example, he said, a chief legal officer may not want to appear like the low-tech, non-value driving part of the business compared with other departments. Popular opinion and word-of-mouth can also help.
“A lot of people in the C-suite didn't care all that much about cyber until we had events,” he said. “Now they care a lot. Circumstances can also drive this, even if it's not dollars and cents.”
|The Future's Bounty
But once that adoption occurs, and today's lawyers become more familiar with using tomorrow's tools, what exactly does the future hold when it comes to legal predictions?
Katz said that it's instructive to look at innovations in other fields, such as financial and insurance technology, for what's next in legal, given how technology has migrating to the legal field historically.
“In some ways, nothing in legal tech is really novel, if from a technical standpoint,” he said. “It's just changing the domain that it's in before. So it's hard to say what the waves are—the waves are just what's going on in tech. Then people have to figure out how to grasp that set of ideas for legal tech.”
And indeed, this migration has begun happening in greater numbers, both from “big players” and from smaller start-ups, Michels pointed out. This means technology companies are paying greater attention to how to specialize pre-existing technologies to legal-specific needs.
“What has been interesting in this regard is that there are specialized research tools emerging. An example of that are solutions that collect specific types of cases and apply analytical tools in an effort to identify potential outcomes based on the jurisdiction or the court where a matter may pending,” he said. “Another area of predictive analysis involves solutions designed to search publicly available data in an effort to provide information regarding potential jurors, parties and witnesses. These 'trial intelligence' systems may also help analyze public sentiment to inform development of litigation strategy.”
LexisNexis' Wellen agreed, making five predictions of what predictive technologies will be able to do in the future:
- Proactively make recommendations of specific legal strategies to employ based on outcomes of similar cases.
- Ask the user questions if the system does not have enough information to make an actionable decision or recommendation.
- Proactively conduct research to find relevant case citations or information that can support or refute the user's arguments or case strategy.
- Recommend other search topics or keywords to pursue based on past searches by a user or the user's colleagues. This is similar to Amazon's recommendation engine.
- Draft case arguments based on input fact patterns or case concepts using verbiage taken from the outcomes of similar, successful cases.
“In their most advanced form, these tools can predict case and legislative outcomes and guide legal case strategies,” Wellen adds.
But guiding legal case strategies is something lawyer-specific—will the technologies of the future even leave any space for lawyers at all? Susskind speculated, “The disruption here is that crucial insights in legal practice and in legal risk management might be generated largely by algorithms operating on large bodies of data without needing to involve mainstream lawyers (unless they choose to collaborate with data scientists).”
But that doesn't need to be true, and the lawyers that embrace these new predictive models might end up better than either technology-averse lawyers or the technology alone. Katz said that one of the most important function of these technologies may in fact be keeping score.
“You don't have to be perfect—when you go across various forms of endeavors, you find that subject matter experts aren't nearly as good as advertised when it comes to forecasting. Area after area, medicine, finance, law, whatever. … The point is, we're not a field that has done a good job at keeping score,” Katz said. “If you have a model, they put that thing on trial for its life. Meanwhile, the existing process they have, they don't even have data on how well they performed when it comes to forecasting.”
“The problem with lawyers is that we all have an idea. Some are right and some are wrong, but we need to bring the tools of science, the tools of finance, to bring to bear on these problems, because then we can actually smoke out who's actually beating the market, so to speak.”
Excerpted with permission from Tomorrow's Lawyers by Richard Susskind. For more information, click here.
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