In 1984, William Harrington, then a lawyer practicing in Connecticut, penned an article in the Law Library Journal titled “A Brief History of Computer-Assisted Legal Research.” It provides a fabulous history of the rise of Westlaw and Lexis. At the end of the article he discusses the benefits of there being not one, but two legal research platforms. Looking to the future, he closes the article with this scenario, which must have seemed radical at the time:
Someday before long the computer in your office may be wakened at 2:00 a.m. by a signal from a satellite. Down from the satellite will come a stream of information, which your computer will receive and file in the appropriate electronic cubbyholes in its memory. When you arrive at your office in the morning, your computer will have prepared a daily digest for you of information selected according to instructions you have left with the computer. When you want to do research, you will use your own computer to scan the information in its own memory, information that is updated daily and perhaps even more often.
Almost 35 years later, you can conduct legal search on your phone using any of a dozen or more platforms! We’d all be bummed if we had to settle for Mr. Harrington’s vision. But, how much better can legal search technology get?
I don’t want to commit the same kind of undershoot that Mr. Harrington did, and anyone who knows me knows I think AI is only just beginning to transform the life of lawyers and of the law. Yet, there are some inherent limits on what more AI can squeeze out of legal search.
In the first place, today’s legal search technology actually is pretty awesome. Close to a dozen platforms offer fast, easy, effective legal search options using some or all of machine learning, natural language processing, and computational topic modeling. Some, like CaseText’s CARA, and the more recent Eva by ROSS’s, even dispense with the need to enter a “search” by allowing one to drag and drop a draft brief or memo into a portal that identifies more cases like those already cited. And the visualizations Ravel and FastCase provide allow deeper searching based on citation networks. When I enter a traditional Boolean or natural language search I am impatient if it takes more than three seconds to get high quality results, and then I can resort results based on relevance, date, court, etc. Fastcase also has democratized legal search by teaming up with state and local bar associations that make access free with membership. Bottom line: legal search is already super-fast at producing on target results and available to all. How much faster and on target can it be?
One outer limit is that the dataset is finite. It’s growing, but at any search moment it is finite. So it’s not like one platform can claim to have more federal cases or state statutes than another. In other words, the platforms are not competing based on datasets, they are competing based on how they help us search through the finite dataset.
Another limit is that typically lawyers have fairly specific searches in mind, so most of the dataset is irrelevant to any search. A good search platform will weed out the noise and zero in on cases, statutes, and other materials on target to the specific inquiry. The existing platforms are already quite good at doing both, and doing it fast.
So, what’s left to improve on? Well, it turns out that the same search entered into the various platforms does not yield the same “top ten” cases in terms of relevance. Law professor Susan Nevelow Mart conducted such a test and reported her results and assessments in a thoughtful article published in the March 2018 ABA Journal. It is well worth the read, showing as the bottom line that, much like the different results one might get for the same music genre across Pandora, Spotify, and Apple Music, the different platforms have unique algorithms that push different cases to the top of the list. She also showed they all basically return the same list of cases—it’s the “top” hits that differ starkly. It also turned out, however, that many of the cases in each platform’s “top ten” were actually not relevant to the search once evaluated by a human.
So, there is room for improvement–still more AI can do to improve legal search if the goal is to have that top ten list contain the most relevant cases. Let the games begin!
Resilience theory has become a dominant framework across many disciplines, from engineering to ecology. Resilience is formally deﬁned as “The capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure and feedbacks, and therefore identity, that is, the capacity to change in order to maintain the same identity” (Folke et al. 2010). In the theoretical model, “engineering” resilience refers to building in hard barriers to disturbances, such as a concrete seawall to fight off big storms, whereas “ecological” resilience refers to methods that bend more but bounce back, such as enhancing coastal wetlands to take the brunt of the storm.
Ten years after the Great Recession swept through the economy like a big storm, we can ask, how resilient was the legal services industry and how resilient is it today? This gets us deeper into what goes into resilience. There are five attributes, with some trade-offs at play:
- Reliability: The parts of the system have to perform as expected, and the system has to perform if a part fails
- Efficiency: The system should minimize waste and perform as expected even in times of resource scarcity
- Scalability: The system can perform as expected even as its scale increases or decreases
- Modularity: The system can rearrange and replace its parts to respond to disturbance
- Evolvability: The system can make changes necessary to perform as expected over long time frames
Engineering resilience is often associated with boosting reliability and efficiency, whereas ecological resilience is often more about working on scalability, modularity, and evolvability. You can quickly see where some of the trade-offs could complicate matters. For example, to build scalable and modular features in a system may require redundancy of parts, which may not always promote efficiency. Optimal efficiency would build in just the right amount of redundancy to keep the system resilient, but knowing how much that is can be a challenge.
Looking back on it, I’d say the legal services industry was pretty resilient to the Great Recession. So-called Big Law is back on the rise when measured by revenues and profits, albeit still less so than before the recession. And the emergence of significant new forms of legal services providers, such as United Lex and Integreon, and an array of new technology solutions suggests that the legal services industry is building modularity and scalability in order to evolve. And there are other positive signs, such as increasing employment and increasing law school applicants. Bottom line: contrary to all the “death of lawyers” rhetoric at the beginning of this decade, it didn’t happen—the industry was resilient. Yes, it has changed, but change to some degree is a hallmark of evolvability, an essential ingredient of resilience. The question is whether it has maintained the same identity, and I would say for them most part, it has.
But how resilient is it still? What if another recession even half as bad as 2008 hit the economy in two years? The concern may be that the legal services industry, and Big Law in particular, has been so driven by the efficiency goal that it has dispensed with too much redundancy to take another head on blow like that. A concrete seawall may provide more immediate protection than a coastal wetland, but when it blows out, it’s ugly. In short, keep an eye on continuing to build scalability, modularity, and evolvability too.
When we started the Program on Law & Innovation here at Vanderbilt Law School five years ago, we launched with two courses: Legal Project Management, taught by PoLI Coordinator and Adjunct Professor Larry Bridgesmith, and my Law 2050 class that surveys the post-normal times in the legal industry. With a strong commitment to delivering vital curricular content to our students, I am happy to report that we have now built out to ten courses, five of which are in the PoLI “core” course set plus five more advanced and specialized courses firmly within the PoLI space:
- Law 2050
- Legal Project Management
- Legal Problem Solving (taught by Cat Moon, our new Director of Innovation)
- Law as a Business
- Legal Practice Technology
- Blockchain and Smart Contracts
- Robots, AI, and Law
- Role of In-House Counsel
- Disruptive Technologies and Law
- Corporate Legal Risk Management
With this diverse and deep set of course offerings, we aim for PoLI to equip our graduates to dive into the “river” of change in the legal industry and see it as an opportunity, not a threat.
As I put the finishing touches on my Law 2050 class syllabus for this fall semester, I am struck by two impressions. The first is the tremendous generosity my guest speakers have shown in the past, devoting their time and energy to providing perspective and insight to the students, and this year is no exception. So far the following have agreed to donate their time, roughly in order of appearance:
- Zach Fardon – King & Spalding
- Joan Fife – Winston & Strawn
- Jeff Grantham – Maynard Cooper
- Anna Barry – Jounce Therapeutics
- Michelle Kennedy – Nashville Predators
- Craig Weinstock – National Oilwell Varco
- Larry Bridgesmith – Adjunct Professor and PoLI Coordinator
- Caitlin Moon – Adjunct Professor and PoLI Innovation Design Director
- John Murdock – Bradley Arant
- Nancy Hyer – Vanderbilt Owen School
- Randy Michels & Kevin Hartley, Trust Tree
- Ray LaDrier – Locke Lord
- George Lamb – Baker Botts
- John Lutz – Vanderbilt Vice Chancellor for IT
- Patrick Cavanaugh – Blank Rome
- Kito K. Huggins – Weil, Gotshal & Manges
- Daniel Reed – United Lex
- Diedre Gray – Post Holdings
The second impression is how the framing of the course has changed. When I started the course in 2013, the theme was very much about how much was changing in the legal industry compared to pre-2008. The average 3L student in the 2013 class was 26, meaning they were 21 in 2008 and lived in very real time as young adults through the Great Recession. They experienced the before and after contrast very closely, and, while not doing so as lawyers, easily connected with that theme in the class. The metaphor I used was that pre-2008, the legal industry was like a lake, whereas post-2008 it was more like a river and nobody knew where it was leading. The river was scary.
With each year since then, however, the reset button effect of the Great Recession has become more remote to the students. Yes, they are entering the profession in the midst of change just as were the 2013 students, but they don’t generally use pre-2008 as a reference point for anything, much less for their conception of what the legal industry is about. In short, they don’t care about what the legal industry lake looked like pre-2008—they want to jump into the river! I see the course as more about giving them a raft to navigate it.
The same has been true of my guest speakers, who in 2013 were very much tuned into the shock to the system the Great Recession caused and still reeling from it. They remembered swimming in the calm lake. With each year, the mood has been less “what just happened, take me back to the lake” to more of a focus on change management and seeing opportunities as they raft down the river.
Of course, it’s still the case that nobody knows where the river is leading!
As I plan and prepare for the Third Annual AI & Law Workshop, scheduled for April 19-20 here at Vanderbilt Law School (details to follow), I thought back to last year’s workshop and my 2×2 matrix of the AI & Law space. I broke it down based on the “AI for Law” and “Law for AI” distinction on one axis and the “Theory and Research” and “Practice and Experience” split on the other. In retrospect, after a year of editing the SSRN Law eJournal on Artificial Intelligence – Law, Policy, and Ethics, I have unpacked it to more fully represent the breadth and depth of the AI & Law world. Here’s my shot at it, with examples of the content and types of questions that fit in each box:
|THE AI and LAW MATRIX||AI for Lawyers
Applications of AI within legal practice
|AI for Legal Administration
Applications of AI in the work of courts and agencies
|Law for AI
Legal regimes governing the use and impacts of AI
|AI for Law for AI
Employing AI to implement Law for AI regimes
How do we conceptualize AI in this space?
|When is AI “practicing law”?||Can AI “judge”?
Can AI design standards better than agencies?
|Does machine learning “discriminate” within the meaning constitutional and civil rights laws?||Can AI make AI obey the law?|
What are the moral implications and ethical duties?
|What duties do lawyers have when incorporating (or not) AI in practice?||Is it ethically sound to turn over decisions such as bail and agency enforcement to AI?||How transparent should government be when it uses AI to monitor?||Is it morally acceptable to turn regulation of AI over to AI|
What are the societal goals and tradeoffs?
|What level of AI knowledge should lawyers be required to have?||Do we want to promote or contain AI in criminal law administration—e.g., setting bail?||What concerns are there regarding using AI to develop “threat scores” and “citizen scores”?||Who decides what AI applications to regulate with other AI?|
How do we design legal instruments and institutions?
|Who is liable for AI’s role in malpractice?||How will machine learning be admitted as evidence in the court room—under Daubert or a new standard?||Is a government produced “citizen score” an invasion of privacy? A violation of due process? Of equal protection?||How could we design mandatory AI monitoring and reporting of use of AI in private employment decisions?|
What are the practical implications?
|How will lawyers actually use and evaluate others’ use of AI?||How will we deal with different levels of access to AI by parties?||Do agencies have the capacity to design and administer regulatory AI?||How will AI be deployed on top of AI as a technical matter?|
What is the track record?
|How far have smart contracts gained traction in commercial transactions?||Is there evidence that use of AI in probation is more or less discriminatory than human judges acting alone?||Have anti-discrimination laws been effective in regulating uses of AI in housing, lending, and other private decisions||Is there evidence from AI development that the “black box” of machine learning can be “interrogated”?|
I plan to float this at the workshop and again at our Summit on Law & Innovation, which my colleagues Larry Bridgesmith and Cat Moon are organizing for April 30, and I also welcome comments.
Along with my three wonderful co-authors—Eric Biber of UC-Berkeley Law, Sarah Light of Penn’s Wharton School Legal Studies Department, and Jim Salzman of UCLA Law—I was pleased recently to have published Regulating Business Innovation as Policy Disruption in the Vanderbilt Law Review. As its title suggests, the article explores instances of “disruptive business innovation” to sort out why some (e.g., Uber and Airbnb) explode into policy disruptions and others (e.g., Netflix and Swiffer) do not. After all, both Uber and Netflix upended incumbent industries, so why is Uber facing legal snarls all over the globe and Netflix destroyed Blockbuster with nary a legal scratch?
Reading about the lawsuit Legal Force recently filed against Legal Zoom (and the California, Arizona, and Texas bars) in California, claiming it is engaged in unauthorized practice of law in its online trademark documents service, I was stuck by an irony about our article: with four law professors as co-authors, we included not a single example from the legal industry! Legal Zoom is the obvious example we could have used, but the problem runs deeper and threatens the access to justice movement.
But first, some background on what we mean by policy disruption. Over in the business school world, there is a raging debate over the merits of Clayton Christensen’s theory of disruptive business innovation. The basic idea is that by using a technological or business model innovation (or both), an innovator can quietly eat away at the “low end” of an incumbent industry’s customer base—the customers who would pay less to get less but don’t have that option under the incumbent industry’s model. Over time, though, the innovator improves its product quality and penetrates deeper into the market before the incumbents wake up, by which time it is too late. Legal Zoom is a great example: it started out doing limited, routine legal tasks and now does a lot more, including feeding work to a network of lawyers, with annual revenue upward of $200 million.
In the article, we do not try to resolve the debate over whether the business theory of innovative business disruption is useful or not—that’s for the business profs to decide. Our point is that, as far as we can tell, the impact of regulation response never plays a role in that debate, but regulation may have everything to do with whether a business innovation succeeds or not. So we developed a theory for thinking about when business disruption raises a policy disruption under the existing regulatory regime applied to the incumbents–a disconnect that could attract regulators’ attention. There are four types of business innovation policy disruptions:
- End Runs – the innovator argues it is sufficiently different from the incumbents to avoid being subject to the incumbent regulatory regime
- Exemptions – the innovator argues it fits an exemption in the incumbent regulatory regime
- Gaps – the innovator is engaging in an activity that fits no existing regulatory regime but presents policy concerns like those that led to the incumbent regulatory regime
- Solutions – the innovator is subject to the existing regime, but if left alone would help solve the problem that led to the regulation of the incumbents in the first place
Legal Zoom is a clear example of an End Run—the company argues it is not engaging in unauthorized practice of law but comes about as close to the line as one can imagine, which has ruffled the feathers of lawyers and state bars around the nation since the company started in 2001. The Legal Force lawsuit claims Legal Zoom has crossed the line and is unfairly cutting into Legal Force’s business as a law firm specializing in trademark practice. We would identify this as a clear policy disruption problem—the incumbent (Legal Force) argues that the innovator (Legal Zoom) presents the same policy concerns that led to the regulation of the incumbent and thus should be subject to the same regulatory regime in order to avoid giving it an unfair market advantage, but Legal Zoom argues it is not practicing law so is not subject to the regulations.
We argue in the article that in such situations regulators have four choices:
- Block – prohibit the innovator model altogether
- OldReg – apply the incumbent regulatory regime as is and see how it fares
- NewReg – invent new regulations for the innovator model (and possibly the incumbents)
- Free Pass – leave the innovator alone and let the market chips fall where they may
As the ABA Journal has covered extensively, so far the Legal Zoom battle in the US has for the most part been between advocates of OldReg versus advocates of Free Pass, although some states, such as North Carolina, have adopted NewReg approaches. By contrast, in the UK, their embrace of a NewReg approach to legal practice has allowed Legal Zoom far more latitude.
As I argue in a forthcoming installment of my Post Normal Times column in ABA’s The Young Lawyer magazine, I don’t see much future for the limiting this ongoing debate to the OldReg vs. Free Pass options. Neither do the DOJ and FTC, which argued in support of the North Carolina reform. There is mounting pressure to harness advanced technologies through innovative business models as a way to improve access to legal solutions for low- and middle-income individuals and small businesses, who simply cannot afford traditional legal services delivery. Other legal innovation upstarts, like the ticket resolution app TIKD, are getting stymied by the relentless battle with OldReg forces. As the DOJ and FTC argued:
“the practice of law” should mean activities for which specialized legal knowledge and training is demonstrably necessary to protect consumers and an attorney-client relationship is present. Overbroad scope-of-practice and unauthorized-practice-of-law policies can restrict competition between licensed attorneys and non-attorney providers of legal services, increasing the prices consumers must pay for legal services, and reducing consumers’ choices. … Such products may also help increase access to legal services by providing consumers additional options for addressing their legal situations. The Agencies also recognize that such interactive software products may raise legitimate consumer protection issues. The Agencies recommend that any consumer protections, such as requiring disclosures, be narrowly tailored to avoid unnecessarily inhibiting competition and new ways of delivering legal services that may benefit consumers.
Put bluntly, if the legal profession is serious about improving access to justice, we are going to have to get serious about designing a NewReg model that both allows legal industry innovations to thrive and protects consumers and the public.
The fifth year of my Law Practice 2050 class is a wrap and it was wonderful working with the students and guest speakers. I’ll give a shout-out to the speakers soon—for now I want to highlight the tremendously creative topics my students bit off for their “skate to where the law is going” project. The project requires them to build a future scenario around an emerging technological, social, economic, or other trend, anticipate the legal issues it will generate, and then explore the theme in three different writing projects—a blog post, a client alert letter, and a bar journal article. The idea is that when the show up at their first post, they need to do more than show up—they need to brand and build their expertise. What better way to do so than on an issue for which there are no existing experts!
It has amazed me how quickly topics my students chose five years ago have ramped up into real legal practice fields (think cryptocurrencies, 3D printing, drones, and fitness tracker data, all of which were just breaking five years ago), and how much even those have changed and generated new applications and thus new legal angles. So, if you are looking for where billable hours will emerge over the next five years, look at this year’s project topics:
- Quantum computing
- Brain-to-computer and brain-to-brain neural links
- Microchip implants for employees
- Automated shipping vessels
- Cyborg enhancements
- Cryptocurrencies for small business
- Initial coin offerings
- CRISPER gene editing
- Smart contract oracles
- Preimplantation genetic diagnosis
- Synthetic food
- Lab-grown in vitro meat
- Augmented reality
- Virtual reality
- 3D food printing
- Autonomous aerial vehicles
- Germline editing
- Life-extending nanotechnology
- Twitter bots
- Implanted medical drug release chips
- Cannabis law
- Data driven threat scores
- AI displacement of jobs
- Voice activated digital assistants
- MOF water capture technologies
- Implanted video recording devices
- High-tech deep sea mineral extraction
- Opening of Arctic shipping lanes
- Stimulus and biomarker detection devices
- Fitness tracker employee data
- Service animals and the ADA
- Mega-scale ecological engineering
Several topics were more directly related to legal practice:
- Emojis in the courtroom
- Alternative legal finance
- Brain scans as evidence of state of mind
- Unauthorized practice of law liberalization
Some of these topics already are generating legal work and legal practice challenges, but not at large scales; others have yet to translate to the legal space, but that is soon to come; some seem too outlandish to ever generate billable hours or legal practice concerns, but they will.
And one thing is for sure—reading these final bar journal articles will beat grading exams!
The slow pace of my posts on Law 2050 lately has a lot to do with the fast pace of Skopos Labs, the legal-tech start-up I mentioned in my last post (Yikes–that was in June!). I am happy to report that after a busy summer, with John Nay leading an excellent data analytics team, our first product will be included as part of the newly-launched Wolters Kluwer service–the Federal Developments Knowledge Center. Read all about it here: http://wolterskluwer.com/company/newsroom/news/2017/09/wolters-kluwer-introduces-ai-powered-predictive-analytics-to-federal-developments-knowledge-center.html.
The quick version:
Collaboration with Skopos Labs, Inc. will enable practitioners to predict the likelihood of bills becoming law
NEW YORK, Sept. 14, 2017 — Wolters Kluwer Legal & Regulatory U.S. announced today the introduction of a powerful new predictive analytics package as an augmentation to its highly regarded Federal Developments Knowledge Center. The analytics are powered by artificial intelligence (AI) tools developed in collaboration with Skopos Labs Inc., a software company specializing in predictive analytics. The new features are the latest in what has been a continual stream of innovation and harnessing of analytics and AI across several Wolters Kluwer product lines.
Working on this has been fun, but it has sucked up a lot of my other fun time, such as posting here. Seeing some daylight with this recent Skopos development announced, I plan to get back at it. In particular, my Law 2050 class is well underway and this year’s slate of guest speakers is tremendous–I am thankful to them all. More to follow!
Almost one year ago I posted about a new predictive analytics effort spearheaded by Vanderbilt PhD student (now Dr.) John Nay. To say the least, a lot has happened since then! Along with Oliver Goodenough of Vermont Law School, John and I co-founded a start-up, Skopos Labs, to take John’s sophisticated analytics into legal and other markets. Skopos is a German linguistic theory of translation focusing on the importance of translating from a source text to a target audience. That is what Skopos Labs does through its predictive analytics. As an example, Science magazine’s daily newsletter covered our work on legislative text, in which the analytics can very accurately assess the probability of a bill introduced in Congress ultimately being enacted. We’re delighted to have been showcased by Science! More to follow.
One of the high points of each year in our Program on Law & Innovation is the “pitch event” in Adjunct Professor Marc Jenkins’ Technology in Legal Practice class. One of the major projects in the class involves students forming teams that pair with area legal aid organizations to build problem-solving apps improving access to justice. Now wrapping up its third year, the class and the students are firing on all pistons, building prototypes or live versions of some very meaningful apps that can help traditionally underserved populations who cannot affordably navigate our utterly complex legal system. Marc has worked closely with the legal aid organizations to develop strong bonds with the students, and also has opened ties with Vanderbilt’s Computer Science Department and our new entrepreneurship center, The Wond’ry, to leverage their expertise in building out the apps. Here’s just a quick summary of the students’ impressive accomplishment this year, describing for each team the organization, work product, and app authoring platform:
- LGBT Legal Relief Fund: This new organization has been flooded with requests for help. The student team worked with the developers at KIM to build a workflow management app.
- Legal Aid Society: The team built a mobile app prototype, which they named Clean Slate, to guide a person through the incredibly complicated criminal record expungement eligibility process. They used the JustinMind Mobile App prototyping tool.
- Tennessee Justice for Our Neighbors: Using an app authoring platform designed by Vanderbilt CS undergrad student Ashley Peck (very impressive!), this team developed a prototype of what they call the Childcare Contingency Plan for undocumented immigrants hoping to contingency plan for their children in case the parents are detained or deported.
- Tennessee Justice Center: This student team designed an app for the Sales Force platform that walks families through the SNAP (food stamps) eligibility criteria. They reduced 1000 pages of ridiculously complicated agency “guidance” to an interview consisting of 30 – 60 questions (depending on answers).
- Nashville Arts and Business Council: This team picked up from a previous year’s team that used Neota Logic to design an interview aspiring musicians (we have a few here in Nashville!) can use to make business entity formation decisions appropriate to their plans. The team essentially beta tested the existing app, leading to improved wording and more accurate outcomes.
- Legal Aid Society: This team also continued working on a mobile website app started by a prior team, built using the same authoring program designed by Ashley Peck, to guide the user through the often bewildering debt collection process.
- Legal Aid Society: Using the A2J author platform, this team designed a web-based computer app they call Mission Expungement, for the criminal records expungement process directed specifically at the Nashville jurisdiction.