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Quantitative Legal Prediction – or – How I Learned to Stop Worrying and Start Preparing for the Data Driven Future of the Legal Services Industry


Daniel Martin Katz


Michigan State University - College of Law

December 11, 2012

Emory Law Journal, Vol. 62, 2013

Abstract:     
Do I have a case? What is our likely exposure? How much is this going to cost? What will happen if we leave this particular provision out of this contract? How can we best staff this particular legal matter? These are core questions asked by sophisticated clients such as general counsels as well as consumers at the retail level. Whether generated by a mental model or a sophisticated algorithm, prediction is a core component of the guidance that lawyers offer. Indeed, it is by generating informed answers to these types of questions that many lawyers earn their respective wage.

Every single day lawyers and law firms are providing predictions to their clients regarding their prospects in litigation and the cost associated with its pursuit (defense). How are these predictions being generated? Precisely what data or model is being leveraged? Could a subset of these predictions be improved by access to outcome data in a large number of 'similar' cases. Simply put, the answer is yes. Quantitative legal prediction already plays a significant role in certain practice areas and this role is likely increase as greater access to appropriate legal data becomes available.

This article is dedicated to highlighting the coming age of Quantitative Legal Prediction with hopes that practicing lawyers, law students and law schools will take heed and prepare to survive (thrive) in this new ordering. Simply put, most lawyers, law schools and law students are going to have to do more to prepare for the data driven future of this industry. In other words, welcome to Law's Information Revolution and yeah - there is going to be math on the exam.

Number of Pages in PDF File: 58

Keywords: big data, law, prediction, quantitative legal prediction, legal services, machine learning, algorithmic justice, legal prediction

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Date posted: December 12, 2012 ; Last revised: June 3, 2013

Suggested Citation

Katz, Daniel Martin, Quantitative Legal Prediction – or – How I Learned to Stop Worrying and Start Preparing for the Data Driven Future of the Legal Services Industry (December 11, 2012). Emory Law Journal, Vol. 62, 2013. Available at SSRN: http://ssrn.com/abstract=2187752

Contact Information

Daniel Martin Katz (Contact Author)
Michigan State University - College of Law ( email )
318 Law College Building
East Lansing, MI 48824-1300
United States
HOME PAGE: http://computationallegalstudies.com/
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