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law+tech+design+delivery
by daniel martin katz
edu | illinois tech - chicago kent college of law
blog | ComputationalLegalStudies.com
corp | LexPredict.com
observations regarding innovation in the legal industry
page | DanielMartinKatz.com
#legalinnovation
three faces of innovation in legal
(1) lawyers for innovators / entrepreneurs
what many lawyers and law schools think of as “Innovation Law"
(1) lawyers for innovators / entrepreneurs
(2) lawyers as innovators - substance
poison pill - “the most important innovation in corporate law
since Samuel Calvin Tate Dodd invented the trust
for John D. Rockefeller and Standard Oil in 1879”
(2) lawyers as innovators - substance
emerging areas - 3D Printing, Driverless Cars, Augmented Reality,
Data Breach, Crypto/Blockchain, Future of Work,
Big Data+Privacy, etc.
Drones, Internet of Things, CyberSecurity,
(2) lawyers as innovators - substance
(3) lawyers as innovators - business/process
innovation directed toward transforming the practice of law
(3) lawyers as innovators - business/process
today I want to talk about
emerging innovations on
this third face
lawyers as innovators
substance
business/process
Four Pillars of Innovation
in Law
{Law + Tech + Design
TM
+ Delivery}
{Law
Substantive
Legal
Expertise
+ Tech + Design
TM
+ Delivery}
{Law
Substantive
Legal
Expertise
Analytics
Platform
AI
Computing
KM
+ Tech + Design
TM
+ Delivery}
{Law
Substantive
Legal
Expertise
Analytics
Platform
AI
Computing
KM
Process Improvement
User Experience
Design Thinking
Project Mgmt
+ Tech + Design
TM
+ Delivery}
{Law
Substantive
Legal
Expertise
Analytics
Platform
AI
Computing
KM
Process Improvement
User Experience
Design Thinking
Project Mgmt
Business Models
Regulation
Marketing
+ Tech + Design
TM
+ Delivery}
labor
arbitrage
process/tech
arbitrage
regulatory
arbitrage
a.i. / predictive
analytics
the flavors of arbitrage
At the outset, I should note
there are several distinct markets
for legal services
Enterprise Law
Small and
Medium
Enterprises
Retail
Government
Criminal
five legal sub-sectors
Enterprise Law
Small and
Medium
Enterprises
Retail
Government
Criminal
five legal sub-sectors
My Friend
Bill Henderson ...
has some basic data on
these markets
Enterprise Law
statistics via Bill Henderson
Entities with (>50+Million)
Fortune 1000 other large entities
Enterprise Law
statistics via Bill Henderson
Size of Market $150 billion
Number of Potential Clients 40,000
Small/Medium Enterprises
statistics via Bill Henderson
Size of Market $60 billion
Number of Potential Clients 6 million
Retail / Main Street
statistics via Bill Henderson
Number of Potential Clients 318 million
Size of Market $75 billion
(with huge potential upside)
observation 1
What is the hallmark of the
bespoke legal work?
Complexity
Social, Economic and
Political Complexity
Which for our
purposes manifests
in legal complexity
In the face of ever
growing legal complexity
we have applied greater
and greater numbers of
human experts to solve
the underlying problem
Lawyer as Complexity Engineer
complexity keeps growing ...
and so has total expenditures
on legal services
Legal Expenditures as
a function of GDP
(some disagreement between these
plots but they project a similar trend)
Cobb Douglas is
the traditional way
to describe a
production
function
LaborCapital
Cobb Douglas is
the traditional way
to describe a
production
function
LaborCapital
Cobb Douglas is
the traditional way
to describe a
production
function
historically we have
turned this dial
~1984 - 2009
Returns to Legal Experts (Big Law)
~1984 - 2009 ~2009 - Present
Returns to Legal Experts (Big Law)
~1984 - Present
Returns to Legal Experts (Retail)
~1984 - 2009 ~2009 - Future
Returns to Legal Technology (Capital)
Legal is a mature market
and in mature markets
efficiency trumps growth
What does the change in
the return structure imply?
Far greater returns in
process improvement
substitution of capital for labor
observation 2
What is one major historic
barrier to legal innovation?
Client Sophistication
The Sophisticated
General Counsel
Although many of pieces
were already in place ...
The Financial Crisis Placed
Significant Pressure on GC’s
To Control Their Legal Spend
Legal was brought
in line with
the Other C Level
Officers/Divisions
“I am not running your
training program ...”
(i.e. Don’t Put
1st and 2nd Year
Associates
on our work)
“If you want our work -
you are going to work
with other providers”
The General Counsel
as Legal Supply Chain Manager
Blended
Teams
of
Providers
Law Firm
+
E-Discovery Firm
+
Legal Process Outsourcing
+
Law Division Insourcing
+
Software/Analytics Firm
Legal Supply
Chain Mgmt.
Data and Logistics =
General Counsels
as the Maestros
Client Sophistication is
Critical to this Story ...
Client Sophistication
has reset historic
relationships ...
observation 3
all of the above is a
necessary precondition
for legal entrepreneurs
Lex.Startup
is beginning to take hold
15
2009
Lex.Startup
15
2009
Lex.Startup
15 500+
2009 2015
Law or Legal Related Companies
as highlighted by Josh Kubicki @ ReInventLaw London 2013
Lex.Startup
The VC Community
Is Turning to Legal
and investing real money
R e p o r t e d s a l e
price between $35
million and $40
million.
Final Number was
likely between
$80 - $100 million
A n u m b e r o f
venture capitalists
have invested in
t h e c o m p a n y ,
including Silicon
Valley’s Sequoia
C a p i t a l w h i c h
invested $7 million
in 2007 ....
And There is
Lots More in this Space ...
So what are these
folks doing?
R + D Function in the
Legal Industry
observation 4
the path of legal(tech)
has in part followed
developments
in artificial intelligence
data driven AI rules based AI
Competing Orientations in
Artificial Intelligence
expert
systems
Computational Law
Data Driven Rules Based
prediction
models
and
methods
network
analytic
methods
natural
language
processing
self
executing
law
visual
law
computable
codes
we see a decent amount of
rules based AI
in legal industry
that is actually pretty consistent
with path of A.I. in general
lots of issues
with expert systems
and/or
rules based A.I.
(without data or an evolutionary dynamic)
rules based A.I. data driven A.I.
1980’s, 1990’s, Early 2000’s
>
rules based A.I. data driven A.I.
1980’s, 1990’s, Early 2000’s
rules based A.I. data driven A.I.
2005 - Present
<
>
rules based A.I. data driven A.I.
1980’s, 1990’s, Early 2000’s
rules based A.I. data driven A.I.
2005 - Present
<
>
as usual law lags other sectors of the economy
A.I. State of the Art
A.I. State of the Art
purely data centric
A.I. State of the Art
purely data centric
augment expert forecasts w/ data
iterative data < > rules
A.I. State of the Art
purely data centric
augment expert forecasts w/ data
The Rise of
Quantitative
Legal
Prediction
Quantitative
Legal
Prediction
Data
Driven
Law
Practice
Is starting to gain steam ...
implication is that
every organization in legal
needs a data strategy
Every organization needs
relevant human capital
(and in law such human capital is in limited supply)
Quantitative Methods for Lawyers
Professor Daniel Martin Katz
Legal Analytics
Professor Daniel Martin Katz
Professor Michael J Bommarito II
legalanalyticscourse.com
free
course
material!
(more coming soon)
Some Examples
2011
The Age of
Quantitative Legal Prediction
2011
The Age of
Quantitative Legal Prediction
2011
The Age of
Quantitative Legal Prediction
2012
The Age of
Quantitative Legal Prediction
2012
2013
The Age of
Quantitative Legal Prediction
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
2013
The Age of
Quantitative Legal Prediction
2013
2013
2013
2013
2014
2014
2014
2014
Some Commercial Examples
Predictive
Coding
in
E-Discovery
https://lexmachina.com/
“The software
identifies standard
and terms in
contracts, and its
benchmarking
tools show
lawyers how their
current document
compares to the
standard.”
http://www.noticeandcomment.com/
General Counsels as Legal
Procurement Specialists
TyMetrix -
Using $50 billion+ in Legal
Spend Data to Help GC’s
Look for Arbitrage
Opportunities, Value
Propositions in Hiring Law
Firms
Legal Procurement
(High End of Market)
There are 3 Known Ways
to Predict Something
Algorithms, Experts, Crowds
example from my own work
predicting the decisions of the
Supreme Court of the United States
experts
crowds
Black
Reed
Frankfurter
Douglas
Jackson
Burton
Clark
Minton
Warren
Harlan
Brennan
Whittaker
Stewart
White
Goldberg
Fortas
Marshall
Burger
Blackmun
Powell
Rehnquist
Stevens
OConnor
Scalia
Kennedy
Souter
Thomas
Ginsburg
Breyer
Roberts
Alito
Sotomayor
Kagan
1953 1963 1973 1983 1993 2003 2013
9-0 Reverse
8-1, 7-2, 6-3
19 19 19 19 19 20 20
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
- Reverse
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
-
8-1, 7-2, 6-3
9-0
19 19 19 19 19 20 20
algorithms
For most problems ...
ensembles of these streams
outperform any single stream
Humans
+
Machines
Humans
+
Machines
>
Humans
+
Machines
Humans
or
Machines
>
non-trivial question is how to
assemble such streams for
particular problems
so that we are not required to
rely exclusively on experts
law is a field dominated by
individual human experts
in most fields - significant quality
improvements have been made by
moving from experts to ensembles
observation 5
law < > finance
many elements in law look like
finance did 25-35 years ago
Lets me return to SCOTUS
Paper Released
August 24, 2015
lots of investment decisions in law
are just a version of this basic idea
law = finance
except its is implicit underwriting
with no real underwriting standards
law != finance
(but it should)
we expand on this theme in this presentation
http://computationallegalstudies.com/2015/10/fin-legal-tech-laws-future-from-finances-past-katz-bommartio/
observation 6
the discovery + compliance convergence
the goal is
near real time monitoring
challenge is that
80%+ of the world’s data
is unstructured
defect w/5 ‘airbag’
version 1.0
backdate w/5 ‘option’
etc.
near real time monitoring of
version 2.0
a large volume of
corporate communications
employee behavior
etc.
Behavior Change will change
But Behavior Change will lag
(i.e. rogue action will be done offline)
(i.e. folks will craft incriminating communications
at least for a while)
Corp Security Starts to
mirror today’s NSA
thus, discovery (in part)
becomes compliance and some
(only some) litigation is avoided
legal standards will still shift
real time monitoring will generate
lots of false positives
‘do less law’
https://vimeo.com/98606908
BROADER POINT
Three Types of Lawyers
(as described by paul lippe)
play “whack-a-mole”, reacting to
problems by creating fear and
friction within organizations and
the impression that there is a legal
disaster around every corner.
Mediocre Lawyers
can help clients shape
(perhaps distort)
external perception of risk.
Merely Clever Lawyers
design systems that
balance risk and improve
transparency, helping clients
correctly price risk internally
Great Lawyers
observation 7
Information Management
is a significant problem in legal
data that could inform
operations is not collected /
or not regularized
Dodd-Frank RRP*
for SIFI’s
(Systemically Important Financial Institution)
EXAMPLE:
*(the UK version is called ‘ring fencing’)
information necessary to
undertake due diligence or
other regulatory exercises is
locked in an antiquated format
(i.e. pdf, word, tif file)
Resolution & Recovery Plans
are Living Wills for Banks
“The living will is effectively a
roadmap and simulation
of the largest possible series of
transactions in a bank’s lifetime,
the type of analytical exercise that is
common in electronic systems design
or software testing,
but unprecedented in law.”
Ideal RRP is a
‘War Game’ whereby a
SIFI demonstrates it is
robust to failure of
various counterparties
but requires review and
understanding of the set
of agreements across all
business lines (p&l’s)
problem is
legal work product is not a
pointable data object
horizontal integration
of legal work product in the
broader corporate technology
ecosystem represents a source
of immediate value creation
“Watson [and related machine
learning technologies] will catalyze
b e t t e r o r g a n i z a t i o n o f l e g a l
information and legal data, forcing
organizations to better manage their
current data and delivering substantial
re t u r n s f ro m t h i s i n f o r m a t i o n
management step alone....”
for example -
contracts should be born
(or processed) as computational
to point straight into finance/acct
and other relevant IT systems
stored
legal
work
product
sensor data
+
contracts talking to other contracts
#InternetofContracts
This is the
#InternetofContracts
which is a special case of the
#InternetofLegalThings
which is a special case of the
which is a special case of the
which is a special case of the
#InternetofThings
#IOT
we are starting a
decade(s) long process of
overhauling the
global financial infrastructure
it is a massive friction
reduction exercise
Big 4 vs. Big Law
who will get to drive this agenda?
only time will tell …
EXECUTIVE SUMMARY
but blockchain is important
bitcoin is probably not that important
observation 8
recently met with the general
counsel of a large publicly traded
company who has reduced the
legal expenditures of the company
by nearly 50% using the lean
methodology over past decade
Lean, Six Sigma
and other
process improvement methodologies
can help improve almost
every subsector in law
the toyota
production system
lean ideas
lean for
enterprises
(white collar, etc.)
The Life Cycle
(Rinse and Repeat)
Examples:
http://
www.seyfarth.com/
dir_docs/
publications/
LITDecJan2014LeanS
ixSigma.pdf
http://
www.seyfarth.com/
dir_docs/
publications/
LITDecJan2014LeanS
ixSigma.pdf
Remove Waste (friction)
Increase predictability
convert high volatility process
convert high volatility process
into a lower volatility process
Knowledge Mgmt (KM)
is a start
Goal is for KM system
to integrate into lawyers
actual behavior
Most Legal Organizations use
Email System as your DMS
(in reality)
Workers are looking back through
old emails to see last version of
something akin to this new doc
Or Emailing the
whole organization
“does anyone have a good
version of X,Y,Z document”
that they could share ?
Stop Wasting Time
on Document
Taxonomies
Intelligent Detailed
Taxonomy
>(user guided)
Search
KM is about
more than
just documents
knowledge lawyers possess
includes processes
That is why folks start
with KM and move to
process engineering
Lean
Process
Mapping
KM
+
Lean
observation 9
the rise of legal r + d operations
intelligent monetization of expertise
beyond just selling hours
making $ while
you sleep >
billing 2500+
hours
each of these entities
(as well as others)
are doing some sort of R+D operation
partnership is a real barrier to r + d
requires the foregoing to profits
that would otherwise be paid out
might need to create a
separate
capital funded
r+d operation
observation 10
We are all (in part) Media Companies
Implication is you
need to build
your personal brand
need build your own
lead generation operation
auditioning for the next job
while in your current job
Portfolios Resumes>
observable evidence noisy signaling
Some of my former MSU folks
http://www.chasehertel.com/
http://www.amanismathers.com/
http://about.me/
karenfrancismcwhite
http://www.andyninh.com/
http://briancpike.com/about/
http://patellis.wordpress.com/
observation 11
Retail Legal Services
+
Technology Aided Access to Justice
70%+ of US does not
have meaningful access
to legal services
in part, this is a
business model
problem ...
existing offering are
far too expensive for
main street consumer
but alternative models are
being developed ...
From Startup to Enterprise
Large Scale
Retail Facing Legal Services
more technology
continuous process improvement
yields better priced services
two examples of
major retail innovations
Reducing complexity through user interface
(even though law is getting more complex)
lots of opportunities to serve
more probono/lowbono clients
every time you remove waste is
a chance to serve more clients
I would like to share one tool
developed by
IIT Chicago-Kent College of Law
IIT Chicago-Kent College of Law
has done more to further
access to justice
than any law school in the U.S.
(and it is not even close)
used by a variety of
legal aid organizations
What is A2J Author?
An online tool
from Chicago-Kent &
CALI to build
graphical interfaces
for low-income,
self-represented
individuals.
A2J Author Gathers Data
Authoring tool in the Cloud End User A2J Guided Interview
“Learn  More”  bubbles,  definition  pop-ups, audio, graphic and video capabilities.
A2J Author “just  in  time”  Learning
Connects to National Server - LawHelpInteractive.org
Completed Documents Delivered to Local Computer
Uses for A2J Author
Document
Assembly
Online Intake
Benefits
EligibilityScreen
&Calculators
E-FilingTriage
Stand-Alone
Info Guides
2,524,639
1,529,205
A2J Guided Interviews
A2J Author 5.0-
Cloud app &
Mobile viewer!
Goal for Version 6.0 of A2J Author
we want to reinvent delivery of
legal services using mobile
observation 12
the demographic reality …
we are about to have the largest
generational transfer in human history
this is a MAJOR
challenge to
every
organization
your organization(s) needs
information systems that can help
support critical knowledge transfer
information regularization
information representation
process mapping
etc.
observation 13
organizations need different
(better) human capital in order
to support these trends
and this should be reflected in
the content of legal education
T Shaped Professionals
via
Liberal Arts Legal .Edu
Liberal Arts Legal .Edu
Polytechnic Legal .Edu
Daniel Martin Katz, The MIT School of Law? A Perspective on Legal
Education in the 21st Century, University of Illinois Law Review (2014)
I outline in this paper my vision
for what law.edu could be ...
lots of the current and future
innovation in law
started outside of law
the distinction between
lawyers and non-lawyers
is blurring at the margins
big picture idea is to have a less
law centric view of the world
big picture idea is to have a less
law centric view of the world
law + tech + design + delivery
{Law
Substantive
Legal
Expertise
Analytics
Platform
AI
Computing
KM
Process Improvement
User Experience
Design Thinking
Project Mgmt
Business Models
Regulation
Marketing
+ Tech + Design
TM
+ Delivery}
LexPredict.com
ComputationalLegalStudies.com
BLOG
@ computational
Daniel Martin Katz
@ computational
computationallegalstudies.com
lexpredict.com
danielmartinkatz.com
illinois tech - chicago kent college of law@

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