Why Artificial Intelligence Might Replace Your Lawyer (via OYZ)

“It’s the alignment of tech and economics that is allowing all this stuff to start moving … The real roll-up of all this isn’t robot lawyers, its financialization, with law becoming an applied branch of finance and insurance” says Daniel Martin Katz, professor at Illinois Tech’s Chicago Kent College of Law.

Program Chair and Speaker at the Plenary Presidential Summit @ New York State Bar Association Annual Meeting – Artificial Intelligence and its Impact on the Legal Profession –


I am pleased to serve as a Program Chair and Speaker at the Plenary Presidential Summit @ New York State Bar Association Annual Meeting. Today’s topic will be Artificial Intelligence and its Impact on the Legal Profession.  Joining me on the panel are the following panelists covering the following topics:

What is Artificial Intelligence? What is Machine Learning?
Dera J. Nevin, eDiscovery Counsel, Proskauer

What are Some Applications of Artificial Intelligence, Machine Learning, and Predictive Analytics in Law?

Andrew M.J. Arruda, CEO & Co-Founder, Ross Intelligence
Daniel Martin Katz, J.D., Ph.D., Associate Professor of Law, Illinois Tech – Chicago Kent Law

What are the Labor Market Impacts? More Jobs, Less Jobs, Different Forms of Legal Jobs and Legal Work?
Noah Waisberg, J.D., Co-founder & CEO, Kira Systems

 

A General Approach for Predicting the Behavior of the Supreme Court of the United States (Paper Version 2.01) (Katz, Bommarito & Blackman)

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Long time coming for us but here is Version 2.01 of our #SCOTUS Paper …

We have added three times the number years to the prediction model and now predict out-of-sample nearly two centuries of historical decisions (1816-2015). Then, we compare our results to three separate null models (including one which leverages in-sample information).

Here is the abstract:  Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. Our model leverages the random forest method together with unique feature engineering to predict nearly two centuries of historical decisions (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice and case level under both parametric and non-parametric tests. Over nearly two centuries, we achieve 70.2% accuracy at the case outcome level and 71.9% at the justice vote level. More recently, over the past century, we outperform an in-sample optimized null model by nearly 5%. Our performance is consistent with, and improves on the general level of prediction demonstrated by prior work; however, our model is distinctive because it can be applied out-of-sample to the entire past and future of the Court, not a single term. Our results represent an advance for the science of quantitative legal prediction and portend a range of other potential applications.

LexSemble – A Crowd Sourcing Platform Designed to Help Lawyers Make Better Decisions

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When it comes to prediction – law would benefit from better applying the tools of STEM / Finance / Insurance and so in that spirit — our company recently launched LexSemble and it allows for near frictionless crowd sourcing of predictions in law (and beyond). Many potential applications in law including early (and ongoing) case assessment in litigation, forecasting various sorts of transactional outcomes and predicting the actions of regulators, etc. It also has a range of machine learning capabilities which allow for crowd segmentation, expert weighting, natural language processing on relevant documents, etc.

Learn More: https://lexsemble.com/features.html

Announcing The Fin (Legal) Tech Conference –
@ Illinois Tech – Chicago Kent College of Law
November 4, 2016 (Sign up Today for a Free Ticket)


#FinTech embraces two major themes – characterizing / pricing increasingly exotic forms of risk and removing unnecessary frictions from friction laden financial processes.  #Fin(Legal)Tech is the application of those ideas and technology to a wide range of law related spheres including litigation, transactional work and compliance.

The Law Lab at Illinois Tech – Chicago-Kent College of Law presents its first #Fin(Legal)Tech Conference on November 4, 2016. Continuing its legacy as an academic leader in legal technology and innovation, Chicago-Kent College of Law will bring together a wide-ranging and diverse group of industry leaders for a truly unique conference experience.

Attendees will be able to see rapid-fire and deeply engaging presentations on the following subjects:

Legal Risk, Legal Underwriting & Legal Insurance
Blockchain and Computable Contracts
MicroLaw / Long Tail Legal Markets
New Legal Information Infrastructure
Quantitative Legal Prediction & Legal Analytics
The Frictionless Delivery of Legal Services
Artificial Intelligence and Law

We will be soon announcing the speaker list but tickets are now open so if you want to attend please register for a FREE ticket today!