Last week Bill Henderson, Bruce MacEwen and Daniel Martin Katz convened the first Forum on Legal Evolution – a small invitation only forum – for leaders from across the legal supply chain (General Counsels, Law Firms, Legal Technologists, Legal Media, Legal Educators, etc.). It was a good mix of members of the AM 200, GC’s of large companies, strategically important technology providers, etc. The primary focus of this first forum was three-fold: (1) change management and the diffusion of innovation, (2) process engineering and process improvement and (3) big data, legal analytics and machine learning in law practice (katz+bommartio slides are available here).
The report offers a number of predictions including those quoted above and “by 2018, legal IT courses will be required for the graduates of at least 20 U.S. Tier 1 and Tier 2 law schools.”
While that would be sensible idea given the emerging opportunities in the legal market, I doubt that this will happen by 2018. Indeed, I would predict that somewhere between {0-2} law schools will make such the move of making such content mandatory by 2018. The ability to teach such a course is almost never a recognized hiring priority or hiring qualification that institutions are seeking (see hereherehere, etc.). Instead, law schools and faculty hiring committees typically focus on hiring for existing or perceived institutional needs. Even when institutions focus on the so called “best athlete” model of hiring … legal technology, etc. typically does not constitute a relevant dimension of the question. In other words, as I said in my MIT School of Law slide deck (and paper) the best athlete model depends upon what sport we are playing.
I am proud to be one of the few tenure track faculty members who actually teaches such courses inside a law school environment (legal technology / legal information engineering, quantitative methods, e-discovery, entrepruenerial lawyering, legal analytics, etc.) Among the existing institutions, there are strong and weaker version of the above courses. However, minus a few notable exceptions, most institutions do not have faculty members with the technical chops that are necessary to effectively teach such course(s).
The intersection of law+technology is one of the growth sectors within legal and as such it is a very exciting time to work in this area. Arbitrage opportunities are temporal in nature and given the highly competitive environment among law schools, it does not bother me if other law schools do not make this a priority. It allows those of us who are so inclined to build relationships with the leading folks in this emerging industry sub-sector before it lands on the radar of others.
Here is an introductory slide deck from “Legal Analytics” which is a course that Mike Bommarito and I are teaching this semester. Relevant legal applications include predictive coding in e-discovery (i.e. classification), early case assessment and overall case prediction, pricing and staff forecasting, prediction of judicial behavior, etc.
As I have written in my recent article in Emory Law Journal – we are moving into an era of data driven law practice. This course is a direct response to demands from relevant industry stakeholders. For a large number of prediction tasks … humans + machines > humans or machines working alone.
We believe this is the first ever Machine Learning Course offered to law students and it our goal to help develop the first wave of human capital trained to thrive as this this new data driven era takes hold. Richard Susskind likes to highlight this famous quote from Wayne Gretzky … “A good hockey player plays where the puck is. A great hockey player plays where the puck is going to be.”
This is a pretty important breakthrough for biologically inspired computing. During my doctoral studies at Michigan, I was a NSF-IGERT fellow at the University of Michigan Center for the Study of Complex Systems. I had the great pleasure of spending time lots of time with John Holland whose work on genetic algorithms is one of many efforts to implement biological principles into computing.
Take a look at this list of legal startups on Angel List – 414 and counting. I am happy to count many of these companies as #ReInventLaw Speakers / Attendees. While many of these companies may not succeed in the long run – these companies tend to cluster around certain ideas. It is my belief that many of those ideas will ultimately prevail. For more thoughts check out Bob Ambrogi’s post “A Time of Unprecedented Innovation in Legal Technology.” I agree with most of his thoughts on the matter.
Click through on the image above to access video. I think this is among the more approachable discussions of the topic. For more check out this bonus video and the full article here.
It is a wrap for #ReInventLaw NYC 2014. We finished up with just over 800 folks in attendance for this free, public facing event at the Cooper Union (~725 at the peak of the day according to the security guards who were keeping the count). As the conference co-organizer, I want to thank all of our speakers for speaking, all of our sponsors for sponsoring and all of our attendees for attending!
There are many interesting changes underway within the legal industry. Many of the participants (both speakers and attendees) are part of the innovator / early adopter segment. It was great to connect with everyone. I hope to continue the conversation. More importantly, I look forward to working together to help build the future …
(1) The Supreme Court’s increasing reliance upon its own decisions over the 1800-1830 window.
(2) The important role of maritime/admiralty law in the early years of the Supreme Court’s citation network. At least with respect to the Supreme Court’s citation network, these maritime decisions are the root of the Supreme Court’s jurisprudence.
The Development of Structure in the SCOTUS Citation Network
The visualization offered above is the largest weakly connected component of the citation network of the United States Supreme Court (1800-1829). Each time slice visualizes the aggregate network as of the year in question.
In our paper entitled Distance Measures for Dynamic Citation Networks, we offer some thoughts on the early SCOTUS citation network. In reviewing the visual above note ….“[T]he Court’s early citation practices indicate a general absence of references to its own prior decisions. While the court did invoke well-established legal concepts, those concepts were often originally developed in alternative domains or jurisdictions. At some level, the lack of self-reference and corresponding reliance upon external sources is not terribly surprising. Namely, there often did not exist a set of established Supreme Court precedents for the class of disputes which reached the high court. Thus, it was necessary for the jurisprudence of the United States Supreme Court, seen through the prism of its case-to-case citation network, to transition through a loading phase. During this loading phase, the largest weakly connected component of the graph generally lacked any meaningful clustering. However, this sparsely connected graph would soon give way, and by the early 1820’s, the largest weakly connected component displayed detectable structure.”
What are the elements of the network?
What are the labels?
To help orient the end-user, the visualization highlights several important decisions of the United States Supreme Court offered within the relevant time period:
Why do cases not always enter the visualization when they are decided?
As we are interested in the core set of cases, we are only visualizing the largest weakly connected componentof the United States Supreme Court citation network. Cases are not added until they are linked to the LWCC. For example, Marbury v. Madison is not added to the visualization until a few years after it is decided.
How do I best view the visualization?
Given this is a high-definition video, it may take few seconds to load. We believe that it is worth the wait. In our view, the video is best consumed (1) Full Screen (2) HD On (3) Scaling Off.
Where can I find related papers?
Here is a non-exhaustive list of related scholarship:
As discussed in a prior post, I will be featuring some of my students who are participating in my law, technology and/or entrepreneurship courses here at MSU Law (access the course list here) — Many of my students are doing interesting and exciting things and so I thought I would take some time to highlight them! For more information about these students or my courses – please feel free to contact me – daniel.martin.katz@gmail.com
Pat Ellis is a 3L at Michigan State University College of Law. He notes “I am especially interested in litigation; eDiscovery, information governance, and compliance; legal informatics and data analytics; legal process engineering and project management; startups and social entrepreneurship.” His course work includes all of these topics.
This high energy completely *free* event that is open to anyone interested in the future of the law including but not limited to law students, practicing lawyers, technologists, venture capitalists, data scientists, legal hackers, government officials, law professors, legal operations professionals, legal entrepreneurs, etc.
The event follows immediately on the heels of LegalTech NYC (which is a 12,000+ person trade show attended by the leading technologists in the legal industry). This will make it easy for LegalTechNYCgoers to attend.
This is an ongoing project with Adam Wyner (Dept. of Computer Science @ University of Aberdeen) and Wim Peters (Dept. of Computer Science + NLP Group @ University of Sheffield) … our very initial pilot project was presented at the 2013 Jurix Conference. Slides are located here and the case study paper for the pilot project is located here. Hoping for more to come on this project in 2014!
