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Thoughts on
Legal
Prediction
and Legal
Metrics
Metrics that Matter
Law Department Operations Meeting
@ computationalcomputationallegalstudies.comprofessor daniel martin katz
Sponsored By:
Association of Corporate Counsel
Huron Legal Consulting
Arc from
~
Quantitative
Legal
Prediction
The Age of
Quantitative Legal Prediction
2011
2011
The Age of
Quantitative Legal Prediction
2012
The Age of
Quantitative Legal Prediction
2012
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
Assistant Professor of Law 
Michigan State University
2013
The Science of Prediction
Prediction is
much harder
than backward
looking
measures
Implicit
Prediction is
taking place all
of the time
Humans
+
Machines
Humans
or
Machines
>
Two Key Ideas
About
Prediction
(1) Inverse Problem
(2) System Dynamics
Hypothesis Testing
is the Core of
Mainstream Science
Deduction
Popperian
Falsification
Partial or
Complete Induction
Is the Alternative
In Case You
Did not Know
This is an
Inductive
Age
This is the Age of Aspirational Spelling
(Is Spelling 1.0 Thinking?)
(a) Induce a Plausible
Model from Existing Data
(b) Validate Model
Either:
Out of Sample
Forward Prediction
Or Both
(2) System Dynamics
Imagine Two Different
Complex Systems
Weather
Tides
vs.
Complex/ Predictable Complex / Chaotic
TIDES ALMANAC
Some Formal Treatment of
the Science of Prediction
Big Data in Legal?
Road Map to the Future
Five
Concrete
Applications
in Legal
Prediction of
Case Outcomes
Better Pricing Forensics
Second Generation
“Predictive Coding”
Mapping of Deal Drafting
to Substantive Outcomes
How Do We Truly Measure
Attorney Quality
+
Performance?
Daniel Martin Katz
Illinois Tech – Chicago Kent Law
Associate Professor of Law
@ computational
computationallegalstudies.com
danielmartinkatz.com
lexpredict.com

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