There is a saying that whoever invented the ship also invented the shipwreck. The point is that new technologies can have their pros and cons, and some of both can be entirely unexpected. Technological innovations thus have always been a challenge for law—how can we facilitate the good while regulating away the bad, especially when we don’t have a full grasp on all of the goods and bads? But that also means technological innovation leads to legal innovation, and opportunity for lawyers to open up new fields of expertise. So, whoever invented the ship also opened the door for lawyers to invent shipwreck law!
The second major category of my student bar journal articles in the Law 2050 class was all about inventing the next shipwrecks with new technology and how law might respond. Like the topic of the first category of articles I covered—the sharing economy—student papers covered varied topics in thoughtful and insightful ways.
I could have used “dronewrecks” for my title, because a healthy number of papers looked at how we are going to take advantage of drones in various commercial applications without running into obvious problems like them crashing into homes and each other (and people). There is interest in applying drones for newsgathering, television and film production, law surveillance, and commercial delivery. A brewery in Minnesota used drones to deliver cases of beer to people ice fishing, until the FAA shut that down. Ah yes, the FAA—the agency is working on regulations for drones, which they refer to as “unmanned aircraft systems,” which the industry fears will be quite constraining of the new technology. States are entering the field as well. My students predicted a slow, incremental approach to easing in of drones under aviation regulation.
The same is true for the close cousins of drones—driverless cars and crewless cargo ships. Driverless cars, which some students covered last year, seem to be moving slowly toward market with regulation moving cautiously to let that happen. But crewless cargo ships? Well, why not? The EU and Rolls Royce are developing the technology, which raises all sorts of pros (lower labor costs, less environmental waste, no crew safety concerns) as well as interesting questions (job losses, cyber-piracy, runaway ships). Both the International Marine Organization and the insurance industry will have plenty of interest in how this develops.
Other topics covered in student papers, from tame to most out there, included:
- Bitcoins and other digital payments
- Regulation of 3D handguns
- Smartphone apps that allow the user to upload series of pictures to 3D printers, thus eliminating the need for CAD programs and allowing easy copying of sculptures and other forms
- 3D bioprinting of organs
- Organs on chips
- Commercial spaceflight
- Asteroid mining and other space property claims
- Neural implants
- My personal favorite—personal invisibility devices (don’t think they’re not working on them!)
The point of the assignment, of course, is to push students to think about law’s development in an entrepreneurial way. Although many of these technologies have a home in an established field (e.g., drones in aviation law; 3D printing in IP law), the established field isn’t a perfect fit and no lawyer is more of an expert on what doesn’t fit than anyone else. There’s no reason a recent law school graduate can’t bust into an established field on the crest of a new technology, outlining the challenges and proposing thoughtful legal innovation, to make his or her brand valued. Kudos to my students for taking that objective to heart and producing many excellent papers I’m sure bar journals would be happy to publish!
This will date me, but I remember a day when law was practiced without computer-based Westlaw or Lexis, when legal technology consisted of the five essentials: a land line telephone, Dictaphone, IBM Selectric, light switch, and thermostat. Westlaw and Lexis were, from the late 1970s until 1986, accessed only via phone modem. I recall using the modem in law school, and then at my firm in the mid-1980s experienced the miracle of using a computer to run simple searches. Life after that was not the same.
So this is not the first time legal practice has faced “disruptive technology.” But what exactly does that mean—disruptive technology? And how do we apply a metric to “disruptiveness”?
As many readers will know, the origins of the term stem from Harvard Business School Professor Clayton Christensen’s theory of disruptive and sustaining innovations. A disruptive innovation helps create a new market or industry and eventually disrupts an existing market or industry. In contrast, a sustaining innovation does not create new markets or industries but rather evolves existing ones to achieve better value.
Much of the commentary on new legal technologies has focused on the disruptive side of the equation, whereas many have a sustaining quality as well. Overall, however, I don’t find that dichotomy very useful for purposes of understanding and teaching how the new wave of legal technology will affect the practice of law and thereby affect the demand for lawyers. So this fall in my Law 2050 class my students and I disaggregated “disruptive” and “sustaining” to get more under the hood of how new technology platforms like Lex Machina, Legal Zoom, Ravel Law, and Neota Logic will change the way law is practiced. (We did so purely intuitively without dipping deeply into Christensen’s detailed theory or other business theory and commentary on the topic—so he and my colleagues at Vanderbilt’s Owen Graduate School of Business Management might cringe at what follows.) Modifying somewhat the typology we developed in class, below I use the introduction of Westlaw and the current play of Lex Machina to explain our typology and impact scoring system.
What is disruptive (and sustaining) about disruptive legal technology?
One way of thinking about how new technologies change the world is to ask a “technology native”—a person who has only known life with the technology—what his or her world would be like if the technology disappeared. For example, while I actually was able to get by years ago without Google (I am a Google “technology immigrant”), I can’t imagine my world without Google now, but I can remember one. So just think about a Google native—someone who has never seen life without Google! Ironically, with Westlaw and Lexis this is becoming increasingly less scary, as Google alone has supplanted them as the first search engine of choice for many legal searches. But let’s envision Westlaw and Lexis coming on line in the 1980s or disappearing in the 2010s and ask, so what, who cares, and why? In what ways is the world of lawyering different with or without them? I come up with five effects, each of which has a 20-point impact scale:
Quality enhancing impact: In the do it better, faster, and cheaper trilogy dominating the legal industry today, quality enhancing technology works on the delivery of better service. For example, Westlaw and Lexis vastly improved the accuracy of search results, such as “find cases from the federal courts in the Fifth Circuit that say X and Y but not Z.” Sure, a lawyer could have run key number headings in the books and read through legal encyclopedias, but the miss rate simply went down when Westlaw and Lexis came on line. So to, with its deep database of IP cases and filings and assessable research design, does Lex Machina improve accuracy of searches about IP litigation, though at present it does not run broad substantive research searches. Scores: Westlaw and Lexis 18 (like Russian skating judge, leaving room for some later contenders); Lex Machina 12
Efficiency enhancing impact: Anyone who has ever run key numbers in hard copy digests or Shepardized a case using the books will appreciate the efficiency enhancement Westlaw and Lexis provided—the “do it faster” component of today’s client demands. Similarly, although one could use the brute force of Westlaw or Lexis searches to assemble the results of a Lex Machina search about the IP litigation profile of a judge or patent, it’s a heck of a lot faster using Lex Machina. Scores: Westlaw and Lexis 18; Lex Machina 18.
Demand displacement effect: Assume a world in which the number and scope of client driven legal searches does not change. In that case, the introduction of a new legal technology that has quality and efficiency enhancement effects is likely to displace demand for service in some sectors of the legal industry if the technology is a cost-effective competitor. For example, Westlaw and Lexis allowed better and faster legal searches, but unless priced to be cost-competitive with the old lawyer-intensive ways of doing legal searches, they won’t penetrate the market. Bottom line, there are fewer billable hours to go around. Given the success of Westlaw and Lexis in establishing their markets, one has to assign them the potential for this displacement effect. It’s much harder to tell with Lex Machina, because it’s not clear what the demand was for the information its type of searches provides prior to its availability. Scores: Westlaw and Lexis: 15; Lex Machina 8
Transformative effect: The opposite side of the coin is the potential a new technology has to open up new markets for legal tasks not previously possible or valued. For example, other than paying for a bespoke lawyer’s judgment about the profile of a particular court for IP litigation, I find it hard to believe many clients would have paid lawyers to perform the kinds of hyper-detailed big data litigation information searches Lex Machina makes possible about lawyers, courts, and patents. Even more so, some of the search techniques Westlaw and Lexis made possible would have been virtually impossible to replicate the old fashioned way with the books. To the extent these new capacities are valued—e.g., they lead to better litigation prediction and outcomes—they will increase demand for service. Hence the transformative effect can work to offset the displacement effect, meaning a new legal technology might increase the pool of billable hours. Scores: Westlaw and Lexis 15, Lex Machina 12
Destructive effect: All of the above discussion has assumed it will be lawyers using the new technology, which clearly will not always be the case—the new technology might reduce or eliminate the need for a lawyer at the helm. Some new technologies will provide user interfaces that do not require an attorney to operate. The rise of paralegals conducting research on Westlaw and Lexis is an example. Even more destructive are technologies like predictive coding, used in e-discovery to vastly reduce the need for lawyers, and online interfaces such as Legal Zoom, which sidesteps the Main Street lawyer altogether. My sense is that Westlaw and Lexis did not have so much destructive effect outside of pushing some work down to paralegals, and the same will hold true for Lex Machina. Scores: Westlaw and Lexis: 8; Lex Machina 8.
Total Impact Scores: Westlaw and Lexis 74; Lex Machina 58.
Of course, this is all meant to be a bit provocative and poke some at the overuse and misuse of the “disruptive technology” theme in our current legal world. As I said, it is not informed by formal business theory, nor do I have any empirical evidence to back up my scores. But the categories of effects seem on point and relevant to the discourse on impacts of new legal technologies, and the scores strike me as decent ballpark estimates. At the very least, I’ll have a model the students can use to dissect the legal technologies they choose to study in next fall’s Law 2050 class!
My Law 2050 energy has been devoted the past month to grading a pile of fabulous papers my students compiled on a broad variety of topics and planning some exciting new developments here at Vanderbilt. More on the latter, later. For now, some observations on several trends in law based on the student papers.
The major writing assignment in the law 2050 class requires students to identify an “inside law” or “outside law” trend and cover it in a blog post, client alert latter, and bar journal article. The purpose is twofold: (1) expose them to writing styles their future employers are likely to expect them to use for professional development and (2) encourage entrepreneurial thinking about how to “jump on” emerging themes and opportunities.
As I have mentioned before, the breadth of “outside law” topics was impressive. Three major themes dominated, however: (1) regulating the so-called sharing economy; (2) weird new technologies; and (3) personal data privacy. Taking them one at a time, this post covers the sharing economy, a snarl of legal issues that ought to keep plenty of lawyers busy for the foreseeable future.
The engine of the sharing economy, no surprise, is the internet and its capacity to link people. Sharing economy companies leverage this capacity to match supply and demand primarily for services, the big three so far being rides (e.g., Uber), rooms (e.g., Airbnb), and odd jobs and errands (e.g., TaskRabbit).
Two opposing narratives have dominated the debate over how to receive the sharing economy. In one, sharing economy companies project themselves as innovative middlemen who merely use smart phone technology to hook up willing service providers with those in need of a ride, place to stay, or broken pipe fixed. In the other narrative, regulated companies in the traditional economy who see the sharing economy as completion accuse its participants of illegally and unfairly skirting rules and regulations running the gamut from licensing to taxes to employment. Which is it? It seems like a little of both to me, which is what has made the sharing economy a regulatory challenge.
The rhetoric of the sharing economy began with its name, because it is not at all about sharing—it’s about charging for services. When ride-share companies ramped up around the nation, for example, they took the position that it was simply about using phones and their smart software to match people who needed a ride with people who for whatever reason felt like driving people around—any exchange of money from passenger to driver was a “donation.” But now with surge pricing and capitalized values in the billions, the sharing economy looks much more like a business model. The other preposterous premise of the sharing economy was that it is quaint and benign, presenting no concerns that should catch the eye of regulation.
The sharing narrative fell apart pretty fast, however, and the rhetoric shifted to fending off the regulatory wolves. Questions raised about the ride-room-errand trio have been so obvious, however, it’s clear the inventors of the sharing economy decided just to go forward without asking permission and wait to see what hit the fan, when, and where. After all, it’s no accident that we regulated rides, rooms, and errands for hire, and for good reason—just check into the history of taxis in major cities in the early 1900s and you’ll find plenty of horror stories. Even a short typology of legal and regulatory issues these new upstarts present is chock full of issues:
- business licensing and taxes: Must Uber or its drivers be licensed as a taxi; must Airbnb or its “landlords” pay hotel taxes
- employment status: Are Uber’s drivers and TaskRabbit’s tasklers independent contractors or employees?; Who payes TaskRabbit’s tasker employment taxes?
- health & safety regulation: Are Airbnb accommodations subject to health regulations and the ADA
- insurance and liability: Who is liable when an Airbnb “tenant” burns down the apartment or an Uber driver assaults a passenger or drives into a building?
- zoning: What if local zoning does not allow hotels in a particular area–can Airbnb operate there?
- private contracts: What is homeowner association bylaws or an apartment lease restrict rentals and sublets?
On the other hand, it’s just as clear that the regulatory system has gone far beyond managing the problems presented by unrestricted ride, room, and errands providers to become part of the problem, protecting the taxis, hotels, and other services industries as much if not more than it protects consumers. Surely the regulated companies do deserve some protection in return for bearing the burden of regulation, such as the fixed rates taxis must charge regardless of demand. But if I can get an Uber driver at a busy downtown location in one minute, have him or her drive me safely back to my reasonably-priced Airbnb apartment I rented for the weekend late the prior week, and get someone over quickly to clean up the place before I turn in the key, what’s wrong with that? It’s hard to get that from the traditional regulated economy. And if the traditional regulated economy isn’t meeting demand, it’s worth taking a step back to ask how to improve the system.
So we have a regulatory conundrum on our hands: consumers love the sharing economy, but want some acceptable level of security and protection; entrenched regulated providers in the traditional economy such as taxis and hotels hate the sharing economy, but can’t deliver its same level of convenience because of regulation; government sees licensing fee and tax revenue slipping away, and can’t please both consumers and the regulated industries.
At the two extremes, one approach would be to unflinchingly apply all the status quo rules of the traditional regulated economy to the sharing economy, which would largely eliminate it, and the other would be to simply turn a blind eye and let tort law sort out the provider-customer relations in the sharing economy, which will cut deep into the stability of the regulated ride, room, and errands providers of the traditional economy. For a while it looked as if the live and let live model was prevailing, as companies like Uber and Airbnb shot into hipster prominence. More recently, however, the sharing economy has taken serious hits, such as Uber’s complete ban in Nevada and fines in San Francisco and Airbnb’s tangles with New York, to name just a few.
A compromise would be to think hard about innovative regulation for the sharing economy. Eric Biber and I, for example, have suggested using a general permitting approach to segregate different segments of sharing economy markets in terms of level of activity and corresponding level of regulation. Or, as Shrai Shapiro has suggested, intermediate forms of regulation, fees, and licensing could be used to open markets to the sharing economy in limited ways. Nashville, for example, recently allowed Uber to operate at the City’s airport, but subjected it to registration, insurance, inspection, and background check requirements.
Either way, its clear that the sharing economy is not going away, but neither are consumer protection regulation, licensing fees, and taxes. The legal issues remain numerous and unresolved. I was glad to see several of my students take hold of this theme and delve deeply and insightfully into its future.
Classes are over here at Vanderbilt Law School, and I am happy to say that the second edition of my Law 2050 class was chock full of great guest speakers—21 in all. Because they make up such a key component of the class, I want to thank them all again. This year’s roster included the following presentations and speakers, in order of appearance:
Law Firm Leaders Panel: Andy Bayman (King & Spalding), John Grenier (Bradley Arant), and Todd Rolapp (Bass Berry Sims)
In-House Counsel Panel: Mike McCarthy (Quantumscape), Celia Catlett (Texas Roadhouse), and Sara Finley (CVS/Caremark)
Law Firm Globalization and Consolidation: Steve Mahon and Mark Ruehlmann (Squire Patton Boggs)
Introduction to Legal Project Management: Larry Bridgesmith (ERM Legal Solutions and Program Coordinator, Vanderbilt Program on Law and Innovation)
Introduction to E-discovery and Information Technolog: Marc Jenkins (Cicayda and Vanderbilt Law Adjunct)
Alternatives to Big Law Panel: Annie Passino (Southern Environmental Law Center), Austin Payne, (Tennessee Department of Environment and Conservation), and Alex Scarbrough Fisher (Thompson Burton)
Demonstration of Lex Machina: Jeremy Mulder (Lex Machina)
Introduction to and Workshop on Neota Logic: Kevin Mulcahy (Neota Logic)
The Technological Future: John Lutz (Vanderbilt Vice Chancellor for Information Technology)
Demonstration of Casetext: Jake Heller (Casetext)
Lean Law: John Murdoch (Bradley Arant) and Prof. Nancy Hyer (Vanderbilt Owen School of Business)
Law Firm Economics: Patrick Cavanaugh (Blank Rome) and Walt Burton (Thompson Burton)
Thank you all—the class would not be what it is for the students without your involvement!
I see many references to the legal industry finding itself in a “new normal,” most prominently as the title of Patrick Lamb’s and Paul Lippe’s thoughtful ABA Journal column, but also in plenty of other places. I have used the term frequently myself. But what’s “normal” about the “new normal” in law? After all, normal means “conforming to a standard; usual, typical, or expected.” My sense is that there is a lot going on in legal practice these days that is unusual, atypical, and unexpected. So, not normal.
An alrternative description—one I will use henceforth—is that the legal industry is in Post-Normal Times. The concept of Post-Normal Times was developed in 2010 by scientist Ziauddin Sardar to describe the turbulent and changing times we are living in. He based his idea on the work of Silvio Funtowicz and Jerome Ravetz, who in the early 1990s challenged conventional science with their model of Post-Normal Science as a methodology of inquiry that is appropriate for cases where “facts are uncertain, values in dispute, stakes high and decisions urgent.” This graph illustrates their focus on two variables—decision stakes and systems uncertainties—defining the environment for using Post-Normal Science as a methodology:
Applied science and other traditional problem-solving strategies do not work well in the context of long-term issues where there is less available information than is desired by stakeholders. Post-Normal Science advocates creating an “extended peer community” consisting of all those affected by an issue who are prepared to enter into dialogue on it.
Building on that theme, Sardar defines Post-Normal Times as “an in-between period where old orthodoxies are dying, new ones have yet to be born, and very few things seem to make sense.” He elaborates on the nature of Post-Normal Times:
All that was ‘normal’ has now evaporated…. To have any notion of a viable future, we must grasp the significance of this period of transition which is characterised by three c’s: complexity, chaos and contradictions. These forces propel and sustain postnormal times leading to uncertainty and different types of ignorance that make decision-making problematic and increase risks to individuals, society and the planet. Postnormal times demands, this paper argues, that we abandon the ideas of ‘control and management’, and rethink the cherished notions of progress, modernisation and efficiency. The way forward must be based on virtues of humility, modesty and accountability, the indispensible requirement of living with uncertainty, complexity and ignorance. We will have to imagine ourselves out of postnormal times and into a new age of normalcy—with an ethical compass and a broad spectrum of imaginations from the rich diversity of human cultures.
Ziauddin Sardar, “Welcome to postnormal times,” Futures 42(2010) 435-444.
That sounds a lot more like the legal industry’s current predicament than “new normal” conveys. If so, are humility, modesty, and accountability at least part of the answer for law’s imagining itself out of postnormal times and into a new age of normalcy?
In Machine Learning and Law, Harry Surden of the University of Colorado Law School provides a comprehensive and insightful account of the impact advances in artificial intelligence (AI) have had and likely will have on the practice of law. By AI, of course, Surden means the “soft” kind represented mostly through advancement in machine learning. The point is not that computers are employing human cognitive abilities, but rather that if they can employ algorithms and other computational power to reach answers and decisions like those humans make, and with equal or greater accuracy and speed, it doesn’t matter so much how they get there. Surden’s paper is highly recommended for its clear and cogent explanation of the forms and techniques of machine learning and how they could be applied in legal practice.
Surden quite reasonably recognizes that AI, at least as it stands today and in its likely trajectory for the foreseeable future, can only go so far in displacing the lawyer. As he puts it, “attorneys, for example, routinely combine abstract reasoning and problem solving skills in environments of legal and factual uncertainty.” The thrust of Surden’s paper, therefore, is how AI can facilitate lawyers in exercising those abilities, such as by finding patterns in complex factual and legal data sets that would be difficult for a human to detect, or in enhancing predictive capacity for risk management and litigation outcome assessments.
What Surden is getting at, in short, is that there seems to be little chance in the near future that AI can replicate the “bespoke lawyer.” That term is used throughout the commentary on the “new normal” in legal practice (which is actually a “post normal” given we have not reached any sort of equilibrium). But it is not usually unpacked any further than that, as if we all know intuitively what bespoke lawyering is.
To take a different perspective on bespoke lawyering and the impact of AI, I suggest we turn Surden’s approach around by outlining what is bespoke about bespoke lawyering and then think about how AI can help. In the broadest sense, bespoke lawyering involves a skill set that draws heavily from diverse and deep experience, astute observation, sound judgment, and the ability to make decisions. Some of that can be learned in life, but some is part of a person’s more complex fabric—you either have it or you don’t. If you do have these qualities under your command, however, you have a good shot at attaining that bespoke lawyer status. Here’s a stab at breaking down what such a lawyer does well:
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 made the most progress, with outfits like Lex Machina and LexisNexis’s Verdict & Settlement Analyzer building enormous databases of litigation histories and applying advanced analytics to tease out how a postulated scenario might fare.
Analogical and evaluative legal search: Once that pile of search results comes back from Lexis or Westlaw (or Ravel Law or Case Text), 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 employed to facilitate that process through machine learning. This might not be cost-effective, as often the selection of cases and other materials must be completed quickly and from relatively small sets of results. Also, the strength of fit is often a qualitative judgment, and identifying useful analogies, say between a securities case and an environmental law case, is a nuanced cognitive ability. Nevertheless, if a lawyer were to “train” algorithms over time as he or she engages in years of research in a field, and if all the lawyers in the practice group did the same, AI could very well become a personalized advanced research tool making the research process substantially more efficient and effective.
Risk management: Whereas outcome prediction is usually a one-off call, managing litigation, transaction, and compliance outcomes over time requires a sense of how to identify manage risk. Kiiac’s foray into document benchmarking is an example of how AI might enhance risk management, allowing evaluation of massive transactional regime histories for, say, commercial real estate developers, to detect loss or litigation risk patterns under different contractual terms.
Strategic planning: Lawyers engage extensively in strategic planning for clients. Where to file suit? How hard to negotiate a contract term? Should we to disclose compliance information? 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 (and judging): Judgment about what a client should do, or about how to decide a case when judge, involve senses not easily captured by AI, such as fairness, honesty, equity, and justice. The unique facts of a case may call for departure from the pattern of outcomes based on one of these sensibilities. Yet doctrines do exist to capture some of these qualities, such as equitable estoppel, apportionment of liability, and even departure from sentencing guidelines, and these doctrines exhibit patterns in outcomes that may be useful for lawyers and judges to grasp in granular detail. What is equitable or just, in other words, is not an entirely ad hoc decision. AI could be used to decipher such patterns and suggest how off the mark a judgment under consideration would be.
Legal reform: As I tell my 1L Property students, in almost every case we cover some lawyer was arguing for legal reform—a change in doctrine, a change in statutory interpretation, striking down an agency rule, and so on. And of course legislatures and agencies, when they are functional, are often in the business of changing the law. To some extent arguments for reform go against the grain of existing patterns, although in some cases they pick up on an emerging trend. They also rely heavily on policy bases for law, such as equity, efficiency, and legitimacy. In all cases, though the argument has to be that there is something “broken” about continuing to apply the existing law, or to not invent new law, in the particular case or broader issue in play. AI might be particularly useful as a way of building that argument, such as by demonstrating a pattern of inefficient results from existing doctrine, or detecting strong social objection to an existing law.
Trendspotting: In my view the very best lawyers—the most bespoke—are those ahead of the game—the trendspotters. What is the next wave of litigation? Where is the agency headed with regulation? Which law or doctrine is beginning to get out of synch with social reality? Spotting these trends requires the lawyer to get his or her head outside the law. Here, I think, AI might be most effective in assisting the bespoke lawyer. A plaintiffs 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 on Twitter about a product. Similarly, this approach could be used to inform any of the lawyer functions outlined above.
Handling people: Ultimately, a top lawyer builds personal relationships with colleagues, peers, and clients. AI can’t help you do that, I don’t think, but by helping lawyers do all of the above it may free up time for a game of golf (tennis for me) with a client!
Many, many years ago, when I was practicing environmental law with Fulbright & Jaworski in Austin, I was unfortunate enough to have a number of clients whose needs required that I master the EPA’s utterly convoluted definition of solid and hazardous waste. One summer I assigned a summer associate the task of flowcharting the definition. Over the course of the summer we debugged draft after draft until, finally, we had a handwritten flowchart that flawlessly worked any scenario through the definition step-by-step. It was ten legal-sized, taped-together pages long. It worked, but it wasn’t very practical.
If only we had had Neota Logic back then! Last week, in my Law 2050 class, Kevin Mulcahy, Director of Education for Neota, demoed their product over the course of two classes and a 3-hour evening workshop. Prior to the session I had assigned the class the exercise of flowcharting the copyright law of academic fair use. Each student prepared a flowchart and explained its logic, then six groups collaborated on final work products. I sent the group flowcharts to Kevin so he could use them to explain the Neota platform in a context familiar to the students.
Neota is a software program that allows the user to translate legal (or other) content into a user-friendly interactive application environment, much like Turbo Tax does for tax preparation. Neota allows the content expert to build the app with no coding expertise, with end products that are quite sophisticated in terms of what can be embedded in the app and how smoothly the app walks the user through the compliance logic. Example apps Kevin offered covered topics as varied as songwriter rights to Dodd-Frank compliance.
The first class period Kevin introduced Neota and then walked through each of the group flowcharts to analyze how each one broke down the fair use compliance problem. The core theme was how important it is to develop the output scenarios first. In the fair use exercise, there are several yes/no questions specific to educational uses, and then a multi-factored balancing test applies in the event none of those binary questions leads to a fair use outcome. Like any balancing test, this one yields a range of scenarios from very likely fair use to very likely not fair use. We spent a good deal of time thinking about how to design an app component to capture the balancing test.
In the evening workshop a group of 20 students acted as content experts to guide Kevin through the process of building the fair use app, much in the way a legal expert might work worth a Neota software expert. The most striking learning experience from this session, besides the deep look under Neota’s hood, was how the process of building the app actually sharpened our fair use compliance logic. We tested various approaches for capturing the balancing test and conveying output scenarios with substantive explanations for the user.
The next day the entire class regrouped to go over the workshop product, allowing those who could not make the workshop due to conflicting classes the chance to get a good feel for both the flexibility and precision the Neota software offers. Thinking back to my perfectly accurate but impractical ten-page flowchart of the EPA’s waste definition, I could envision how that and many other tasks that required developing a compliance logic could have been leveraged into apps I could have shared with other attorneys in my firm as well as clients.
My Law 2050 students clearly got a lot out of the immersion in using Neota to attack a compliance logic problem. I can’t thank Kevin and Neota enough for the time he invested in preparing for and delivering what was an excellent hands-on and instructive workshop. By the way, the EPA now has an online decision tool for navigating through the waste definition. I think they might want to get in touch with Neota!
This week my Law 2050 class has been all about Lex Machina, and to quote one student at the end of the two sessions: “I can’t imagine being a patent law firm and not wanting to purchase that!” [Note: I have no connection whatsoever with Lex Machina other than having them appear in my class, nor, I believe, did this student.] That sentiment was widely shared.
I contacted Lex Machina early in the semester to explore how I could give the class a deep dive in their technology. Jeremy Mulder, Lex Machina’s Director of Customer Success, worked closely with me to make the site available to the students, design an exercise for us to complete in one class, and guide us through the site and the company’s vision over a JoinMe link the next day.
First, the Lex Machina product is a truly awesome example of turning Big Data into a useful, user-friendly legal analytics product. The depth and breadth of data contained in the site, particularly for patent law, was astounding. For example, pick any federal district judge and within a few seconds the site provides an array of data, including outcomes at granular levels, patents handled, time to case termination, lawyers appearing in the court, and many more. The site display and navigation is a breeze. The class started to tackle the questions together at the beginning of the first class, and within about 10 minutes, with no instructions from Lex Machina, we had begun to navigate the site with ease and, over time, learned how to tap into one after the other of analytic tools. The site is a model for other law+tech developers.
Second, as the exercise progressed I began to wonder how I would describe Lex Machina within the “disruptive technology” space. Disruption comes in many forms, and whether good or bad depends on the beholder. Lex Machina strikes me as disruptive primarily by providing an additive function—it makes possible what a lawyer could not have imagined he or she could do, at least without a tremendous amount of effort, time, and cost. It adds a tool, but it does not necessarily replace lawyers, or suck away billable hours, or “commoditize” a lawyering function; indeed, by giving lawyers more power over how to analyze patent law’s expanse, it may do just the opposite. More on the “disaggregation” of the disruptive legal technology concept into more descriptive and refined categories in an upcoming post.
The October 2014 issue of The American Lawyer includes its annual rundown of the Global 100 – the top 100 law firms around the world based on revenue – and I must say there’s quite a bit of legal spend going on out there! My ballpark estimate of the total revenue of the top 100 firms is close to $100 billion. Profits per partner at the Global 100 averaged $1.61 million in 2013, which is up (yes, up) 5.3 percent over 2012 (which was up 0.7 percent over 2011), with 70 firms averaging over $1 million. As expected, US firms took the biggest share of profits. Interestingly, some of the largest firms in the world in terms of revenue and/or lawyers fall below the $1 million PPP mark, including Jones Day, K&L Gates, Norton Rose Fulbright, Squire Sanders, CMS Legal, and Dentons. In some cases that may be a tradeoff between stability and profit, and in some cases the verein structure could result in uneven PPP across the firm’s offices.
As one might expect, the lion’s share of all that legal spend goes to firms with their largest number of attorneys based in the US. Of the top 50 firms in the world, 42 find their largest number of attorneys in the US. For the top 100 firms the number is 78, with the UK a distant second. In some cases, however, the US share, while the largest for the firm, is still relatively low. Overall, though, over 97,000 of the lawyers working for the Global 100 work in the US. The UK comes in a distant second with 6900 and China is third with just over 2500. But the number of lawyers working for AmLaw 200 firms in offices outside of the US, and the number of offices outside the US, has expanded steadily since 1998, primarily into the UK, but also significantly into China, Germany, France, Australia, and Canada.
The bottom line: Global Big Law seems to be doing just fine and spreading its wings. Is news of its death premature?