Few business trends are as simultaneously revered, derided, appreciated or ignored as that of big data. Used (somewhat flippantly) to describe large, complex data sets that resist traditional data processing applications, big data represents both a beginning and end for many professional industries ill- prepared to harness big data’s myriad benefits and value. This opening conversation lays the framework for our program by addressing four key questions and concerns:
What is big data?
Why should we use it?
Where does it lie within a business organization?
How do we identify ROI and value in big data investment?
Moderator: John Fernandez – US Chief Innovation Officer and Partner Dentons; Global Chair, NextLaw Labs
Justin Ergler – Director, Alternative Fee Intelligence and Analytics, GlaxoSmithKline Daniel Martin Katz – Associate Professor of Law, Illinois Institute of Technology Chicago-Kent College of Law; Chief Strategy Officer, LexPredict Michael S. Klastava – Vice President, Global Head of Legal Data & Analytics, American International Group, Inc. Christopher Zorn – Liberal Arts Research Professor of Political Science and Sociology, The Pennsylvania State University; Principal, Quantitative Analysis, Lawyer Metrics
Pretty useful summary which is something we try to teach our students in our Legal Analytics Course (which could really be called Machine Learning for Lawyers). BTW – For those of you who emailed us, we promise to fill out the balance of the set of free, online Legal Analytics course materials in the coming months.
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.