Exploring the Physical Properties of Regulatory Ecosystems - Professors Danie...Daniel Katz
Exploring the Physical Properties of Regulatory Ecosystems: Regulatory Dynamics Revealed by Securities Filings — Professors Daniel Martin Katz + Michael J Bommarito
Why We Are Open Sourcing ContraxSuite and Some Thoughts About Legal Tech and ...Daniel Katz
Why We Are Open Sourcing ContraxSuite and Some Thoughts About Legal Tech and the Modern Information Economy - By Michael Bommarito + Daniel Martin Katz from LexPredict
Artificial Intelligence and Law - A Primer Daniel Katz
Artificial Intelligence in Law (and beyond) including Machine Learning as a Service, Quantitative Legal Prediction / Legal Analytics, Experts + Crowds + Algorithms
LexPredict - Empowering the Future of Legal Decision MakingDaniel Katz
LexPredict is an enterprise legal technology and consulting firm, specializing in the application of best-in-class processes and technologies from the technology, financial services, and logistics industries to the practice of law, compliance, insurance, and risk management.
We focus on the goals of prediction, optimization, and risk management to enable holistic organizational changes that empower legal decision-making.
These changes span people and processes, software and data, and execution and education.
Fin (Legal) Tech – Law’s Future from Finance’s Past (Some Thoughts About the ...Daniel Katz
Fin (Legal) Tech – Law’s Future from Finance’s Past (Some Thoughts About the Financialization of the Law) – Professors Daniel Martin Katz + Michael J Bommarito
Exploring the Physical Properties of Regulatory Ecosystems - Professors Danie...Daniel Katz
Exploring the Physical Properties of Regulatory Ecosystems: Regulatory Dynamics Revealed by Securities Filings — Professors Daniel Martin Katz + Michael J Bommarito
Why We Are Open Sourcing ContraxSuite and Some Thoughts About Legal Tech and ...Daniel Katz
Why We Are Open Sourcing ContraxSuite and Some Thoughts About Legal Tech and the Modern Information Economy - By Michael Bommarito + Daniel Martin Katz from LexPredict
Artificial Intelligence and Law - A Primer Daniel Katz
Artificial Intelligence in Law (and beyond) including Machine Learning as a Service, Quantitative Legal Prediction / Legal Analytics, Experts + Crowds + Algorithms
LexPredict - Empowering the Future of Legal Decision MakingDaniel Katz
LexPredict is an enterprise legal technology and consulting firm, specializing in the application of best-in-class processes and technologies from the technology, financial services, and logistics industries to the practice of law, compliance, insurance, and risk management.
We focus on the goals of prediction, optimization, and risk management to enable holistic organizational changes that empower legal decision-making.
These changes span people and processes, software and data, and execution and education.
Fin (Legal) Tech – Law’s Future from Finance’s Past (Some Thoughts About the ...Daniel Katz
Fin (Legal) Tech – Law’s Future from Finance’s Past (Some Thoughts About the Financialization of the Law) – Professors Daniel Martin Katz + Michael J Bommarito
The Three Forms of (Legal) Prediction: Experts, Crowds and Algorithms -- Prof...Daniel Katz
The Three Forms of (Legal) Prediction: Experts, Crowds and Algorithms -- Professors Daniel Martin Katz & Michael J. Bommarito - Illinois Tech Law / Univ of Michigan CSCS (Updated Version)
Bruce, T. R., and Richards, R. C. (2011). Adapting Specialized Legal Metadata...Robert Richards
In the domain of print-based U.S. legal information, specialized tools that create connections between different categories of
metadata increase legal research efficiency. Such tools, redesigned for the electronic sphere, could enhance digital legal information systems. This paper illustrates this kind of redesign, through a case study of one such tool—the Parallel Table of Authorities and Rules in the U.S. Code of Federal Regulations, which connects regulations to the statutes that authorize them.
HLS Students Harness Artificial Intelligence to Revolutionize How Lawyers Dra...Evisort
Evisort might just be the hottest legal tech and AI company you’ve never heard of. Born out of Harvard Law School, MIT and the Harvard Innovation Lab; funded by an investment firm backed by Bill Gates, Mark Zuckerberg, Jeff Bezos and other Silicon Valley luminaries; recently profiled in a Columbia Business School case study on entrepreneurship; and its three founders named to Forbes 30 Under 30, it’s safe to say this is a company worth watching.
Written for procurement professionals and individuals who are not intimately acquainted with the legal profession or to whom legal procurement is an entirely new concept.
This presentation by the John O. McGinnis, Northwestern Pritzker School of Law was made during a roundtable discussion on Disruptive innovations in legal services held at the 61st meeting of the Working Party No. 2 on Competition and Regulation on 13 June 2014. More papers, presentations and contributions from delegations on the topic can be found out at www.oecd.org/daf/competition/disruptive-innovations-in-legal-services.htm
The Three Forms of (Legal) Prediction: Experts, Crowds and Algorithms -- Prof...Daniel Katz
The Three Forms of (Legal) Prediction: Experts, Crowds and Algorithms -- Professors Daniel Martin Katz & Michael J. Bommarito - Illinois Tech Law / Univ of Michigan CSCS (Updated Version)
Bruce, T. R., and Richards, R. C. (2011). Adapting Specialized Legal Metadata...Robert Richards
In the domain of print-based U.S. legal information, specialized tools that create connections between different categories of
metadata increase legal research efficiency. Such tools, redesigned for the electronic sphere, could enhance digital legal information systems. This paper illustrates this kind of redesign, through a case study of one such tool—the Parallel Table of Authorities and Rules in the U.S. Code of Federal Regulations, which connects regulations to the statutes that authorize them.
HLS Students Harness Artificial Intelligence to Revolutionize How Lawyers Dra...Evisort
Evisort might just be the hottest legal tech and AI company you’ve never heard of. Born out of Harvard Law School, MIT and the Harvard Innovation Lab; funded by an investment firm backed by Bill Gates, Mark Zuckerberg, Jeff Bezos and other Silicon Valley luminaries; recently profiled in a Columbia Business School case study on entrepreneurship; and its three founders named to Forbes 30 Under 30, it’s safe to say this is a company worth watching.
Written for procurement professionals and individuals who are not intimately acquainted with the legal profession or to whom legal procurement is an entirely new concept.
This presentation by the John O. McGinnis, Northwestern Pritzker School of Law was made during a roundtable discussion on Disruptive innovations in legal services held at the 61st meeting of the Working Party No. 2 on Competition and Regulation on 13 June 2014. More papers, presentations and contributions from delegations on the topic can be found out at www.oecd.org/daf/competition/disruptive-innovations-in-legal-services.htm
INSIDER'S PERSPECTIVE: Three Trends That Will Define the Next Horizon in Lega...LexisNexis
In a recent Information Today article, Sean Fitzpatrick of LexisNexis discusses trends that will define the future of legal research as we know it.
Humans create 2.5 quintillion bytes of data each day, and the cost of storing and maintaining each byte of data is declining. In fact, the growth of stored data is outpacing the ability of most people to manage it.
Powerful tools, such as natural language processing and machine learning, are helping professionals bridge the gap between information overload and the ability to harvest the power of Big Data.
Millennials now make up nearly one-third of the U.S. workforce and they are our most educated generation.
Join us for our free weekly, no-stress, no-sales-pitch discussions about all-things-AI as it relates to the legal profession. Bring a bag lunch and any questions you might have and join us for an informative session.
What we'll discuss:
* Brief introduction on ChatGPT, GPT-4 and generative AI as it relates to law.
* Strengths and limitations of using generative-AI tools like ChatGPT.
* Tools and enhancements coming specifically targeted at helping attorneys leverage AI.
* Cover specific practical applications around drafting documents, summarization and speeding research.
* 3 arguments for AI adoption in your law firm.
* Q&A with our team - bring ANY question; there are no such things as dumb questions here.
The Future of Legal Services, NCSB Committee to Study Regulatory Reform, July...Legal Evolution PBC
Overview of economic forces currently impacting the market for legal services. Includes transition from one-to-one to one-to-many legal products and solutions. Challenge for profession is to lagging legal productivity. Requires investment in multidisciplinary human capital combined with the creation of new business models.
Architecting Information For An Open Source CitizenryRachel Knickmeyer
Metaphorically, software and law have fundamental things in common. They’re both specialized, obtuse, and generally inaccessible to the layperson. Both govern our daily lives. And whereas software is compiled or interpreted and executed on specialized digital machines, law is interpreted and executed by specially trained human nervous systems.
Open source software relies on community support of two kinds: contribution and collaboration. The same concept lies at the heart of the Open Government Initiative, which focuses on transparency, participation and accessibility. Despite ongoing progress toward transparency, however, significant opportunities remain for improving how government collaborates with citizens to make the process of crafting legislation more accessible. In this talk, we propose that the problems we see with the current state of collaborative government participation is a problem of UX; and information architecture can provide a bipartisan pathway to solving these problems.
We will cover how GitHub’s success stems from its user experience and understanding of its core users: developers. Jumping off from this, we will discuss the concept of open government; covering some its important milestones; and demonstrate how some of the less successful ventures contained critical user experience shortfalls. Finally, we will present research findings and a conceptual IA that is particular to the crafting of laws and legislation. This talk will be a call to action as well: get ready to get involved!
The impact of AI and Blockchain technologies in the Legal IndustryHunter Thompson
This is a paper I wrote for my final semester of my Bachelor of Law (Honours) for the subject Innovation and intellectual Property Law, for which I received a high distinction (56/60). I wanted to share this paper with my Linkedin colleagues in the hope that it might provide an overview of two areas of disruption in law that I believe are highly relevant and interesting.
The role we play as creators - A designer's take on AIGiuseppe de Cesare
There is a growing interest in AI, but the field is understood only by a few, often by technicians. What’s our involvement as designers? What do we know about these new disruptive technologies? Often we know little. This talk will unveil benefits and pitfalls of AI through concrete cases offering designers a framework for understanding. It will introduce a toolkit of ethical principles, that will make you reflect upon the potential of AI to change what is our conventional understanding of a product or a service. Design is about developing a higher awareness of the role we play as creators and builders.
Legal Analytics Course - Class 9 - Clustering Algorithms (K-Means & Hierarchical Clustering) - Professor Daniel Martin Katz + Professor Michael J Bommarito
Legal Analytics Course - Class 5 - Quantitative Legal Prediction + Data Drive...Daniel Katz
Legal Analytics Course - Class 5 - Quantitative Legal Prediction + Data Driven Future of Law Practice - Professor Daniel Martin Katz + Professor Michael J Bommarito
In 2020, the Ministry of Home Affairs established a committee led by Prof. (Dr.) Ranbir Singh, former Vice Chancellor of National Law University (NLU), Delhi. This committee was tasked with reviewing the three codes of criminal law. The primary objective of the committee was to propose comprehensive reforms to the country’s criminal laws in a manner that is both principled and effective.
The committee’s focus was on ensuring the safety and security of individuals, communities, and the nation as a whole. Throughout its deliberations, the committee aimed to uphold constitutional values such as justice, dignity, and the intrinsic value of each individual. Their goal was to recommend amendments to the criminal laws that align with these values and priorities.
Subsequently, in February, the committee successfully submitted its recommendations regarding amendments to the criminal law. These recommendations are intended to serve as a foundation for enhancing the current legal framework, promoting safety and security, and upholding the constitutional principles of justice, dignity, and the inherent worth of every individual.
DNA Testing in Civil and Criminal Matters.pptxpatrons legal
Get insights into DNA testing and its application in civil and criminal matters. Find out how it contributes to fair and accurate legal proceedings. For more information: https://www.patronslegal.com/criminal-litigation.html
ASHWINI KUMAR UPADHYAY v/s Union of India.pptxshweeta209
transfer of the P.I.L filed by lawyer Ashwini Kumar Upadhyay in Delhi High Court to Supreme Court.
on the issue of UNIFORM MARRIAGE AGE of men and women.
How to Obtain Permanent Residency in the NetherlandsBridgeWest.eu
You can rely on our assistance if you are ready to apply for permanent residency. Find out more at: https://immigration-netherlands.com/obtain-a-permanent-residence-permit-in-the-netherlands/.
Responsibilities of the office bearers while registering multi-state cooperat...Finlaw Consultancy Pvt Ltd
Introduction-
The process of register multi-state cooperative society in India is governed by the Multi-State Co-operative Societies Act, 2002. This process requires the office bearers to undertake several crucial responsibilities to ensure compliance with legal and regulatory frameworks. The key office bearers typically include the President, Secretary, and Treasurer, along with other elected members of the managing committee. Their responsibilities encompass administrative, legal, and financial duties essential for the successful registration and operation of the society.
A "File Trademark" is a legal term referring to the registration of a unique symbol, logo, or name used to identify and distinguish products or services. This process provides legal protection, granting exclusive rights to the trademark owner, and helps prevent unauthorized use by competitors.
Visit Now: https://www.tumblr.com/trademark-quick/751620857551634432/ensure-legal-protection-file-your-trademark-with?source=share
WINDING UP of COMPANY, Modes of DissolutionKHURRAMWALI
Winding up, also known as liquidation, refers to the legal and financial process of dissolving a company. It involves ceasing operations, selling assets, settling debts, and ultimately removing the company from the official business registry.
Here's a breakdown of the key aspects of winding up:
Reasons for Winding Up:
Insolvency: This is the most common reason, where the company cannot pay its debts. Creditors may initiate a compulsory winding up to recover their dues.
Voluntary Closure: The owners may decide to close the company due to reasons like reaching business goals, facing losses, or merging with another company.
Deadlock: If shareholders or directors cannot agree on how to run the company, a court may order a winding up.
Types of Winding Up:
Voluntary Winding Up: This is initiated by the company's shareholders through a resolution passed by a majority vote. There are two main types:
Members' Voluntary Winding Up: The company is solvent (has enough assets to pay off its debts) and shareholders will receive any remaining assets after debts are settled.
Creditors' Voluntary Winding Up: The company is insolvent and creditors will be prioritized in receiving payment from the sale of assets.
Compulsory Winding Up: This is initiated by a court order, typically at the request of creditors, government agencies, or even by the company itself if it's insolvent.
Process of Winding Up:
Appointment of Liquidator: A qualified professional is appointed to oversee the winding-up process. They are responsible for selling assets, paying off debts, and distributing any remaining funds.
Cease Trading: The company stops its regular business operations.
Notification of Creditors: Creditors are informed about the winding up and invited to submit their claims.
Sale of Assets: The company's assets are sold to generate cash to pay off creditors.
Payment of Debts: Creditors are paid according to a set order of priority, with secured creditors receiving payment before unsecured creditors.
Distribution to Shareholders: If there are any remaining funds after all debts are settled, they are distributed to shareholders according to their ownership stake.
Dissolution: Once all claims are settled and distributions made, the company is officially dissolved and removed from the business register.
Impact of Winding Up:
Employees: Employees will likely lose their jobs during the winding-up process.
Creditors: Creditors may not recover their debts in full, especially if the company is insolvent.
Shareholders: Shareholders may not receive any payout if the company's debts exceed its assets.
Winding up is a complex legal and financial process that can have significant consequences for all parties involved. It's important to seek professional legal and financial advice when considering winding up a company.
Military Commissions details LtCol Thomas Jasper as Detailed Defense CounselThomas (Tom) Jasper
Military Commissions Trial Judiciary, Guantanamo Bay, Cuba. Notice of the Chief Defense Counsel's detailing of LtCol Thomas F. Jasper, Jr. USMC, as Detailed Defense Counsel for Abd Al Hadi Al-Iraqi on 6 August 2014 in the case of United States v. Hadi al Iraqi (10026)
ALL EYES ON RAFAH BUT WHY Explain more.pdf46adnanshahzad
All eyes on Rafah: But why?. The Rafah border crossing, a crucial point between Egypt and the Gaza Strip, often finds itself at the center of global attention. As we explore the significance of Rafah, we’ll uncover why all eyes are on Rafah and the complexities surrounding this pivotal region.
INTRODUCTION
What makes Rafah so significant that it captures global attention? The phrase ‘All eyes are on Rafah’ resonates not just with those in the region but with people worldwide who recognize its strategic, humanitarian, and political importance. In this guide, we will delve into the factors that make Rafah a focal point for international interest, examining its historical context, humanitarian challenges, and political dimensions.
NATURE, ORIGIN AND DEVELOPMENT OF INTERNATIONAL LAW.pptxanvithaav
These slides helps the student of international law to understand what is the nature of international law? and how international law was originated and developed?.
The slides was well structured along with the highlighted points for better understanding .
Introducing New Government Regulation on Toll Road.pdfAHRP Law Firm
For nearly two decades, Government Regulation Number 15 of 2005 on Toll Roads ("GR No. 15/2005") has served as the cornerstone of toll road legislation. However, with the emergence of various new developments and legal requirements, the Government has enacted Government Regulation Number 23 of 2024 on Toll Roads to replace GR No. 15/2005. This new regulation introduces several provisions impacting toll business entities and toll road users. Find out more out insights about this topic in our Legal Brief publication.
Can Law Librarians Help Law Become More Data Driven ? An Open Question in Need of a Solution — Professor Daniel Martin Katz
1. Can Librarians Help
Law Become More
Data Driven ?
an open question in need of a solution
daniel martin katz
blog | ComputationalLegalStudies.com
corp | LexPredict.com
page | DanielMartinKatz.com
edu | illinois tech - chicago kent law
lab | TheLawLab.com
6. Helped 3.5 million+ Users
Seek Access to Justice
Guided
Interview
Completed
Document
A2J AUTHOR
www.a2jauthor.org
LOGIC
Used over
3.5
Million
times
2.1 Million
Documents generated
IMPACT
11. 3D HD Visualization of Supreme
Court Citation Network
Campaign Contributions and
Legislative Ecosystems
Six Degrees
of
Marbury
v.
Madison
Electronic
World
Treaty
Index
Radial
SCOTUS
Citation
Network
Scientific
Research
25. Can Librarians Help
Law Become More
Data Driven ?
an open question in need of a solution
daniel martin katz
blog | ComputationalLegalStudies.com
corp | LexPredict.com
page | DanielMartinKatz.com
edu | illinois tech - chicago kent law
lab | TheLawLab.com
27. A Reset on Robot LawyersI.
The Rise of #LegalAnalyticsII.
The Killer Use Case(s) - Fin (Legal) Tech)III.
The Infrastructure for #LegalAnalyticsIV.
Building a Legal Data StrategyV.
29. There has been lots of recent
interest in applying
artificial intelligence to law
30.
31.
32.
33.
34.
35.
36.
37.
38. and there is a bit of confusion
as to where we stand today
and where we are headed
39.
40.
41. data driven AI rules based AI
Competing Orientations in
Artificial Intelligence
42. 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
43. we see a decent amount of
rules based AI
in legal industry
74. 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
105. General Counsels as Legal
Procurement Specialists
TyMetrix/ELM -
Using $50 billion+ in Legal
Spend Data to Help GC’s
Look for Arbitrage
Opportunities, Value
Propositions in Hiring Law
Firms
#LegalSpendAnalytics
Quantitative Legal Prediction
118. Columbia Law Review
October, 2004
Theodore W. Ruger, Pauline T. Kim,
Andrew D. Martin, Kevin M. Quinn
Legal and Political Science
Approaches to Predicting
Supreme Court Decision
Making
The Supreme Court
Forecasting Project:
149. “Software developers were asked on
two separate days to estimate the
completion time for a given task, the
hours they projected differed by 71%,
on average.
W h e n p a t h o l o g i s t s m a d e t wo
assessments of the severity of biopsy
results, the correlation between their
ratings was only .61 (out of a perfect
1.0), indicating that they made
inconsistent diagnoses quite frequently.
Judgments made by different people
are even more likely to diverge.”
154. (most pundits did not
identify as a serious
candidate him until
mid-January 2017)
Neil Gorsuch was #1
o n o u r F a n t a s y
Platform 12 Days after
Donald Trump was
elected President
(i.e Nov 20)
161. Final Version of #PredictSCOTUS
1816-2015
case accuracy
70.2%
71.9%
justice accuracy
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0174698
170. expert
forecast
crowd
forecast
learning problem is to discover how to blend streams of intelligence
algorithm
forecast
ensemble method
ensemble model
via back testing we can learn the weights
to apply for particular problems
171. By the way, you
might ask why does
one care about
marginal improvements
in prediction ?
#Fin(Legal)Tech
172. It is a fair question
because in the
private market …
improvements in
performance must
be linked up to an
actual business
model …
183. play “whack-a-mole”, reacting to
problems by creating fear and
friction within organizations and
the impression that there is a
legal risk around every corner.
Mediocre Lawyers
184. can help clients shape
(perhaps distort)
external perception of risk.
Merely Clever Lawyers
185. design systems that
balance risk and improve
transparency, helping clients
correctly price risk internally
Great Lawyers
190. help price risk /
help reduce information asymmetries
transactional =
191. litigation =
characterize (predict) risk/exposure
shift the expected value of a lawsuit
help price risk /
help reduce information asymmetries
transactional =
192. litigation =
characterize (predict) risk/exposure
shift the expected value of a lawsuit
compliance = identify + prevent rogue behavior
monitor behavior in (near) real time
help price risk /
help reduce information asymmetries
transactional =
193. litigation =
characterize (predict) risk/exposure
shift the expected value of a lawsuit
compliance = identify + prevent rogue behavior
monitor behavior in (near) real time
help price risk /
help reduce information asymmetries
transactional =
regulatory =
help identify (predict) the decisions
of regulators / law makers and the risk
associated with various outcomes
199. #Fin(Legal)Tech
application of those ideas and
technologies to a wide range of
law related spheres including
litigation, transactional work
and compliance.
257. "We are increasingly thinking that there's room in
legal tech for a Red Hat in legal — companies that
really focus on development of software by providing
wraparound services, but offer their software open
source," Michael J Bommarito II said.
Michael J. Bommarito
Co-Founder
CEO @ LexPredict
259. Will you resell the software to third parties?
YES%NO%
How much does ContraxSuite cost?
Will you keep derivative work open?Free%
YES%NO%
Free%$12K/year%
50% in trust for open source grants ! 50% for ContraxSuite, LLC!
260. If you are just
buying tools from
vendors you likely
have no alpha
268. D - I - K - W
From Data Strategy to Wisdom
Data$
Informa+on$
Knowledge$
Wisdom$
Direct'record'of'fact,'
signal,'symbol'
Indirect'record'or'
descrip6on$
Interpreta6on'of'
informa6on$
Ac6onable'inference'or'
heuris6c$
Data-Information-Knowledge-Wisdom
Data$
Readings'from'a'temperature'
sensor'in'Tahoe.$
Informa+on$
The'average'temperature'in'the'
month'of'December'is'32.2F.$
Knowledge$
Snow'is'likely'to'accumulate'in'
December.'
Wisdom$
January'is'a'good'month'to'plan'
a'ski'trip'to'Tahoe.$
269. When is Data Valuable?
Even when it’s not
LOW$ HIGH$
HIGH$LOW$
IMPACT'
FREQUENCY'
High3frequency,'high3impact'3'best'use'case'for'data'
• Systema/c'understanding'and'treatment'
• Standardized$reporEng'and'sta/s/cal$treatment'
• PotenEal'for'automaEon'and'predicEon'
Example:'
• Labor'&'Employment'for'a'large'employer'
• Patent'Defense'for'a'large'tech'company'
271. 33!
“Now! we! have! program! managers,!
data! analysts,! business! analysts,!
data! scien9sts,! opera9ons!
managers,!I!mean,!we!have!a!ton!of!
stuff.! That's! the! key! for! me,! is!
thinking! about! the! right! people!
doing! the! right! tasks.! That's! the!
people!part.!And!then!how!they!do!
them,! is! the! process,! and! then,!
automa9ng! parts,! is! kind! of! that!
next,!final!step.!!
"
And$ all$ of$ that$ is$ underpinned$ by$
d a t a ." Y o u$ c a n ' t$ d o$ a n y$
improvements$ unless$ you$ have$
data.$ You$ can't$ automate$ unless$
you$have$good$data.”!
272. 36!
“From!se)lement!informa0on!and!
contracts! to! sensi0ve! client! data!
and! beyond,! Liberty! Mutual!
creates! and! stores! ever:growing!
volumes! of! unorganized! data!
across! its! worldwide! offices! and!
databases.”!
“I've!seen!a!real!transforma0on!in!
the! legal! department! just! having!
t h a t! i n f o r m a 0 o n! v i s u a l l y!
available."!
“The' legal' department' is' now'
w o r k i n g' p r e d i c 7 v e' a n d'
prescrip7ve' analy7cs,"' i.e.' ways'
to' analyze' data' that' enable'
forecas7ng'for'legal'issues.”'
276. Five reasons to care
Can you answer these questions?
1. How&many&legal&ma.ers&did&you&handle&last&year?&
2. How&much&poten:al&legal&liability&did&you&handle&last&year?&
3. How&many&hours&per&legal&ma.er&did&you&spend&last&year?&
4. How&many&dollars&per&legal&ma.er&did&you&spend&last&year?&
5. How&much&value&did&you&protect&or&create&last&year?&
277. 47!
Methods for Using (Legal) Data
Historical reporting in legal
Historical analytics in legal
Predictive analytics in legal
279. 49!
Ques&on:!What!
factors!drove!
se3lement!
amounts!last!
quarter?!
• F o r ! l a b o r ! a n d!
employment!disputes,!the!
length! of! employment!
a n d! p r e s e n c e! o f!
retaliatory! or! sexual!
harassment! claims! are!
posi&vely! related! to!
se3lement!amount!
• Disputes! origina&ng! in!
region!X!have!abnormally!
higher! se3lements! than!
expected,! given! their!
facts!
Ques&on:!What!
factors!drove!
legal!expenses!
last!quarter?!
• An! increase! in! ma3ers! in!
highCcost! jurisdic&ons! is!
posi&vely! related! to! total!
legal!expenses!
• A! decrease! in! arbitra&on/
media&on! u&liza&on! is!
posi&vely! related! to! total!
legal!expenses!
Historical analytics in legal
282. 51!
(be able to do so without a herculean effort)
1. !Measure,!monitor,!and!manage!your!resources!and!service!providers.!
!
2. !Using!data!+!experts,!model!and!improve!the!processes!you!execute.!
3. !Allocate!tasks!across!internal/external!resources!and!assess!cost!and!quality.!
4. !Manage!risk!and!be!able!to!formally!characterize!the!risks!avoided.!
5. !Jus&fy)and)explain)performance)to)the)clients.!
Five Goals for Every Legal Organization
284. Y = βo +/- β1 ( X1 ) +/- β2 ( X2 ) +/- β3 ( X3 ) +/- β4 ( X3 ) +/- β5 ( X3 ) + ε
Y = $151 + $15 ( ) + 161 ( ) + 95 ( ) + 34 ( ) +/- β5 ( ) + ε
Per
100
Lawyers
If Tier 1
Market
is True
Partner
Status
is True
Per
10
Years
Practice
Area
285. 1. Define the Parameter Space
3. Select a Model/Method
4. Validate Out of Sample
2. Collect / Normalize Data
(typically using experts)
286. Work with experts to
define relevant variables
that drive outcomes on
some problem
(experts are strong at identifying
relevant variables but have
trouble applying weights)
290. Daniel Martin Katz
@ computational
computationallegalstudies.com
lexpredict.com
danielmartinkatz.com
illinois tech - chicago kent college of law@
thelawlab.com