It was a pleasure to participate in the Fourth Annual ASU-Arkfeld E-Discovery and Digital Evidence Conference. The conference featured a wide variety of speakers from the bench, law firms, in-house and the legal technology space. The conference was sponsored by the Center for Law, Science & Innovation @ Arizona State Law.
I am excited to announce that I am leaving MSU to join the Chicago-Kent College of Law where I have accepted a lateral offer starting this summer.
It is has been a good run here at MSU Law and wish my MSU colleagues all the best.
The opportunity to be part of one of the long standing and premier law+tech programs is extremely exciting and I look forward to doing great things with my new colleagues at Chicago Kent. As noted in the press release, I am excited to “assume a key leadership role in the law school’s ongoing initiative to build the preeminent law and technology program in the country!”
More to come starting this summer …
This intro class is designed to train students to efficiently manage, collect, explore, analyze, and communicate in a legal profession that is increasingly being driven by data.
Our goal is to imbue our students with the capability to understand the process of extracting actionable knowledge from data, to distinguish themselves in legal proceedings involving data or analysis, and assist in firm and in-house management, including billing, case forecasting, process improvement, resource management, and financial operations.
This course assumes prior knowledge of statistics, such as might be obtained in Quantitative Methods for Lawyers or through advanced undergraduate curricula. This class is not for everyone; for many, it will prove to be challenging. With that warning, we encourage you to consider your interest and career aspirations against the unique experience and value of this class. To our knowledge, this is the only existing class that teaches these quantitative skills to lawyers and law students.
Still in beta – we will be adding much more to this site as we move forward!
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.”
While its performance is sometimes problematic for some extremely large data problems, R (with R studio frontend) is the data science language du jour for many small to medium data problems. Among other things, R is great because it is open source, hyper customizable with thousands of packages available to be loaded for a specific problem.
While Python and SQL are also important parts of the overall data science toolkit, we use R as our preferred language in both Quantitative Methods for Lawyers (3 credits) as well as in our Legal Analytics course (2 credits). We have found that students who are diligent can make amazing strides in a relatively short amount of time. For example, see this final project by Pat Ellis from last year’s course.
Here are some introductory resources that we have developed to get folks started: Loading R and R Studio
R Boot Camp – Part 1 – Loading Datasets and Basic Data Exploration
Data Cleaning and Additional Resources
R Boot Camp – Part 2 – Statistical Tests Using R
Basic Data Visualization in R
Scatter Plots, Covariance, Correlation Using R
Intro to Regression Analysis Using R
Over the balance of the 2014-2015 academic year, Mike and I will be introducing a variety of new things to the quantitative sequence including dplyR, etc. … more to come …
While our primary home will remain here MSU Law, Mike Bommarito and I are excited to be joining up with the good folks at CodeX – Stanford Center for Legal Informatics. Based upon our shared interests, we plan to work together on some joint research activities with some of the many talented individuals in the Stanford CodeX ecosystem. I will be joining CodeX as an External Affiliated Faculty and Mike will be joining as a CodeX Fellow. We are very excited to push forward together in the short, medium and long term!
This past Thursday Ron Dolin and I spole on a panel at the 19th Annual Thomson Reuters Legal Executive Institute Law Firm Leaders Forum. Above are Ron’s slides which many of you might find interesting. Below is a modified version of my presentation Five Observations Regarding Technology and the Legal Industry (which I gave at the LegalWeek Corporate Counsel Forum last month).
Thanks to Ralph Baxter (Chairman Emeritus @ Orrick) for inviting me to present to this extremely accomplished group of AMLaw 200 managing partners.