Quantitative Legal Prediction ( Or How I Learned to Stop Worrying and Embrace Disruptive Technology) Daniel Martin Katz Michigan State University - College of Law
Qualitative Legal Prediction - Prof. Daniel Katz
Dec 03, 2014
Professor Daniel Katz' presentation at lawTechcamp 2011 in Toronto, ON
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Quantitative Legal Prediction( Or How I Learned to Stop Worrying and
Embrace Disruptive Technology)
Daniel Martin KatzMichigan State University - College of Law
(1) Big Data and Moore’s Law
(1) Big Data and Moore’s Law
(2) The ‘Soft’ AI Revolution
(1) Big Data and Moore’s Law
(2) The ‘Soft’ AI Revolution
(3) Prediction
(1) Big Data and Moore’s Law
(2) The ‘Soft’ AI Revolution
(3) Prediction
(4) Mental Models v. Aggregation
(1) Big Data and Moore’s Law
(2) The ‘Soft’ AI Revolution
(3) Prediction
(4) Mental Models v. Aggregation
(5) Quantitative Legal Prediction
This is the Era of “Big Data”
This is the Era of “Big Data”
Increasing Computing Power
This is the Era of “Big Data”
Increasing Computing Power
This is the Era of “Big Data”
Decreasing Data Storage Costs
Increasing Computing Power
This is the Era of “Big Data”
Decreasing Data Storage Costs
Increasing Computing Power
This is the Era of “Big Data”
Decreasing Data Storage Costs
Increasing Computing Power
Fundamentally Altering the Scope of Scientific Inquiry
Highlighting the Data Deluge
Highlighting the Data Deluge
Highlighting the Data Deluge
2008
Highlighting the Data Deluge
2008
Highlighting the Data Deluge
2008 2009
Highlighting the Data Deluge
2008 2009
Highlighting the Data Deluge
2008 2009 2010
Highlighting the Data Deluge
Highlighting the Data Deluge
Highlighting the Data Deluge
2011
Highlighting the Data Deluge
2011
Highlighting the Data Deluge
2011 2011
Highlighting the Data Deluge
Highlighting the Data Deluge
Highlighting the Data Deluge
Okay But ...
Data is only half the story
Computationand
Artificial Intelligence
The Artificial Intelligence Revolution is On
The Artificial Intelligence Revolution is On
The Artificial Intelligence Revolution is On
The Artificial Intelligence Revolution is On
The Artificial Intelligence Revolution is On
The Artificial Intelligence Revolution is On
An Meaningful ‘Soft’ AI Example
E-Discovery
Some Applicable Terms
Natural Language Processing
Natural Language Processing
Knowledge Representation
Natural Language Processing
Knowledge Representation
Feature Extraction
Natural Language Processing
Knowledge Representation
Feature Selection
Feature Extraction
Natural Language Processing
Knowledge Representation
Machine Learning
Feature Selection
Feature Extraction
Natural Language Processing
Knowledge Representation
Machine Learning
Feature Selection
Feature Extraction
Classification
Natural Language Processing
Clustering
Knowledge Representation
Machine Learning
Feature Selection
Feature Extraction
Classification
Prediction
A Few Words About Prediction
Imagine Two DifferentComplex Systems
Weather
Tides
vs.
Easy/ Predictable Difficult / Chaotic
vs.
Easy/ Predictable Difficult / Chaotic
vs.
Easy/ Predictable Difficult / Chaotic
The Caliber of Prediction is
A Function of Various Factors
Including ...
Underlying System
Variability
Quality of Inputs
Etc.
Formal Treatment of the question of
prediction in alternative Domains
Quantitative Legal
Prediction
It Already Exists ...
This is a Great Example
But What Does the Market Really Care About?
Disputes v. Decisions
Disputes, Filings, etc.
Bargaining in the Shadow of the Law
What is the Client’s First Question?
do i have a case?
how is that assessment generated?
Mental Models vs
Aggregated Data
lots of factors matter
Time Scales Matter
inherent system variability matters
‘complexity’ matters
Some Potential Inputs
what is the relevant information contained
therein?
text, citations, votes, etc.
other metadata
what form might the outputs take?
standard client memo
+
statistical portrait of 10,000 ‘similar’ cases
How do we assess similarity?
Analogical Reasoning and the Science of Similarity
similarity measures
=~distance measures
developing these distance functions
is an important part of my research
just one example ...
Six Degrees of Marbury v. Madison A Sink Based Visualization
Some Additional Thoughts
Study of Law Can Be a Scientific Exercise
The Practice of Law Can be Closer to Engineering
The Market for Legal Services
The Market for Legal Education
Have a Date With Destiny
Some Reading For Your Consideration
@computational
AdditionalMaterialsAvailableOnline!
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