Lawyer+Tech: Tomorrow’s Bespoke Lawyer

J.B. Ruhl
Tomorrow’s bespoke lawyer will be a lawyer+tech lawyer.

Tomorrow’s bespoke lawyer will be a lawyer+tech lawyer.

iStock

The Post-Normal Times is a column that follows trends in the legal industry, legal technologies, legal innovation, and access to legal services and offers insights into how new lawyers can turn them from agents of change into agents of opportunity. 

My last column examined the potentially disruptive effects of law+tech—the use in legal practice of rapidly advancing data, computation, and machine learning technologies that together are forging the impressive progress of artificial intelligence (AI). AI technologies are nowhere near replacing the abstract reasoning and problem-solving skills of the “bespoke lawyer,” but they will certainly change how lawyers deliver those services. Indeed, over time it may very well be that a lawyer’s ability to tap into the power of law+tech—to go lawyer+tech—will be what sorts the best lawyers from the rest of the pack.

So, what goes into the lawyer+tech package? One way to think about it is to identify what is bespoke about bespoke lawyering and then ask how AI technology could add value. While there is no recipe for bespoke lawyering, the following ingredients are essential.

Outcome prediction. Prediction of litigation, transaction, and compliance outcomes is, of course, what clients want dearly from their lawyers. On this front, AI seems to have great potential. Many services are already building enormous databases of litigation and transaction histories and applying advanced analytics to tease out how a postulated scenario might fare. Lawyers who stay aware of such services and learn how to use their analytic power will have an edge.

Analogical and evaluative legal search. Once the pile of search results comes back, the lawyer’s job is to sort through and find those that best fit the need. Much as it is used in e-discovery, AI could facilitate that process. This might not always be cost-effective, and the strength of fit many times is a qualitative judgment or depends on analogical reasoning. Nevertheless, if a lawyer were to “train” algorithms over time based on past decisions about what cases fit which problems, AI could become a personalized tool making the research process substantially more efficient and effective.

Risk management. Managing litigation, transaction, and compliance outcomes over time requires a sense of how to identify and control risk. AI could help risk management by allowing evaluation of massive transactional regime histories for, say, commercial real estate developers, to detect loss or litigation risk patterns under different contractual terms. This could be an especially useful application of law+tech for in-house legal departments.

Strategic planning. Lawyers engage extensively in strategic planning for clients. Where to file suit? How hard to negotiate a contract term? When to settle and on what terms? Naturally, it would be nice to know how different alternatives have fared in similar situations. Here again, AI could be employed to detect those patterns from massive databases of transactions, litigation, and compliance scenarios.

Judgment. Judgment about what a client should do, or about how to decide a case, can involve senses not easily captured by AI, such as equity and compassion. Yet doctrines such as equitable estoppel, apportionment of liability exist to capture some of these qualities, and their application exhibits patterns that may be useful for lawyers and judges to grasp in more granular detail. AI could be used to decipher such patterns and suggest how off a judgment under consideration would be from the norm.

Legal reform. As I tell my 1L Property students, in almost every case we cover, a lawyer was arguing for legal reform—a change in doctrine, a change in statutory interpretation, striking down an agency rule, and so on. Ultimately, the argument for reform is that there is something “broken” about applying the existing law. The power of AI to analyze enormous databases could help build that argument, such as by demonstrating a pattern of inefficient results from existing doctrine or detecting a surge of strong objections to existing law in social media.

Trendspotting. Clients also want their lawyers to stay ahead of the game. What is the next wave of litigation? What issues are moving onto agency agendas? Spotting these trends requires the lawyer to peer outside the law box, and AI can help the lawyer see more once there. A plaintiff firm, for example, might use AI to monitor social media to identify trends highly associated with the advent of new litigation claims, such as people complaining about a product.

I’m not suggesting that lawyers get advanced degrees in computer science (though it couldn’t hurt). Rather, the lawyer+tech model involves staying aware of the trends and tools of law+tech and, if not using them directly, knowing how to find someone who can. It may be that law firms will employ AI technologists on staff, or will retain AI services from law+tech consulting firms. Either way, failure to tap into the power of law+tech will only be to a lawyer’s detriment. Tomorrow’s bespoke lawyer will be a lawyer+tech lawyer.

Entity:
Topic:

J.B. Ruhl

J.B. Ruhl is the David Daniels Allen Distinguished Chair of Law and Director of the Program on Law & Innovation at Vanderbilt University.