Artificial intelligence is changing the practice of law. Its impact is still mostly behind the scenes – in document analysis or predictive analysis, for instance – rather than in the courtroom, but it is tangible and growing. Law schools are taking note. How should they now evolve, given that their mission is to prepare students to be “future-ready” lawyers? There is no consensus philosophy as of yet; rather, a broad range of ideas are taking root, somewhat experimentally, across the law school community.
One idea that is decidedly not circulating among law schools, and which I will therefore begin by dismissing out of hand, is that of utilizing artificial intelligence to replace professors. Sadly, this is mooted in some sectors as a solution for K12 schools. I won’t try to hide my contempt for this vision; education for me, and for most, will always be about learning from experienced and expert people to think like experienced and expert people, with all of the creativity, empathy, and flexibility that implies. Technologies can facilitate, but not replace, that fundamental act of person-making. For the foreseeable future, law schools will turn on a Socratic relationship between professors and students. Where, then, is artificial intelligence starting to make its mark?
To begin with, the law school curriculum itself is adapting. Many law schools are adding upper level electives in artificial intelligence, machine learning, and tangentially related areas such as cryptocurrencies. These are often highly subscribed, both because students find them intellectually intriguing and because they believe that establishing some background in this area might give them an edge in their professional careers. No doubt this trend will continue to expand, though its rate of expansion is limited to some degree by the availability of qualified instructors.
Some of the foundational law school courses are also evolving in subtle ways as a result of AI, and perhaps over time will evolve in not-so-subtle ways. Intellectual property is a very good example of this. The strange case of Naruto, the crested macaque who snapped a selfie of himself, has opened up a fascinating debate in the legal world around whether one must be human to claim intellectual property rights. Artificial intelligence will only accelerate that debate (an insight for which I’m indebted to Steve Tapia at Seattle University School of Law). Some intellectual property professors are already experimenting with how to introduce non-human formulations of IP into their classes as “thought experiments;” over time, it’s possible to imagine this could develop into broader critiques of the present IP framework.
Beyond the classroom curriculum, many law schools are designing experiential modes of introducing law students to artificial intelligence. At Georgia State University School of Law, for instance, the Legal Analytics and Innovation Initiative gives law students a chance to collaborate closely with computer science and business students at the same university to design complex technologies that solve previously unsolvable legal problems (such as predicting to a high degree of accuracy how a particular judge will rule in cases defined by a large set of parameters). This kind of work not only has the potential to be a flow-through to the legal practitioner space, but could over time become a mechanism for law schools to “spin out” the kinds of revenue-generating start-up businesses that are a common facet of life science departments at research universities. These programs have also been shown (according to the programs’ own statistics) to help law students land jobs at higher rates than the overall student body, no doubt because the intersection of technology and law is a rare and valuable skillset in the eyes of employers.
Moving farther afield, artificial intelligence is also starting to accelerate the power of technology platforms developed by companies like my own to help law students master challenging material or overcome discouragement. In our CasebookConnect platform we’ve been able to utilize new algorithms based on learning science, combined with hundreds of assessment questions expertly authored by Themis Bar Review, to help law faculty analyze early in the 1L year not just which students may be struggling, but which aspect of legal thinking – legal reasoning, problem solving, foundational concepts, or implementation – may be their particular challenge. Barbri’s ISAAC tool does something similar for individual bar exam studiers, using AI to develop a personalized study plan.
Some law schools are even starting to experiment with techniques developed by many undergraduate schools that involve using big data and AI to refine their recruitment processes, as the task of simultaneously filling out enrollment while meeting the ABA’s increasingly strict accreditation standards becomes increasingly challenging. Though they don’t promote this fact widely, today many large undergraduate programs routinely utilize the same digital marketing techniques as large commercial advertising companies such as Google and Amazon to target specific high school students around the country whom they believe would be an ideal match for their recruitment pool. It’s not difficult to imagine more law schools, caught between a rock and a hard place, investing in such approaches.
The deepest impact of AI on law schools in the long run, though, may be in the changing texture of the student body. It’s clear from my conversations with deans that many law schools are becoming more interested in recruiting students from STEM (science, technology, engineering and math) undergraduate degree programs than they have been in the past. Today, fewer than 10 percent of law students, by some estimates, come from a STEM background. This will change as law schools recognize that students from an engineering background (both traditional and mid-career students) could be exceptional scholars, professors, and practitioners in the widening space at the intersection of artificial intelligence and law, and technology and law more generally. This shift in student body make-up is likely to have significant implications for all law students, as students from humanities and those from technology backgrounds will learn from each other’s expertise and ways of thinking.
This dynamic is likely to be mirrored at the institutional level as well. Historically, there have been fairly few areas of collaboration between the law and engineering schools at major research universities, for instance. As the example of Georgia State shows, there’s every reason to believe that this too will change. Law schools are likely to seek to take greater advantage of being part of a diverse academic ecosystem by proliferating interdisciplinary programs. This will both threaten and stimulate law schools’ sense of their mission within the broader educational world.
It’s difficult to predict which of these trends will spread most quickly and pervasively. Most are climatic shifts that will play out only over decades, much as artificial intelligence itself will reveal its true influence on society only over the same timescale. For now, what I can conclude is that law schools are timeless enough in their mission to remain seaworthy as AI is disrupting other communities wholesale, but attuned enough to society as a whole to show clear signs of tacking as the winds of AI rise.
Vikram Savkar, Vice President and General Manager of International and Higher Education Markets
Vikram Savkar is Vice President and General Manager of International and Higher Education Markets at Wolters Kluwer Legal & Regulatory U.S. He is responsible for managing operations of the market leading publisher of textbooks and other learning solutions for law schools in the United States and abroad, as well as the leading global provider of expert solutions in cross-border legal practice areas including intellectual property, cross-border tax, international arbitration, and competition law.
