Make Law Better - The Legal Innovation Agenda in Vectors and Phases

Make Law Better - The Legal Innovation Agenda in Vectors and Phases

Make Law Better ( #MakeLawBetter) - The Legal Innovation Agenda in Vectors and Phases

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Daniel Martin Katz

September 19, 2018
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  1. The Legal Innovation Agenda in Vectors and Phases daniel martin

    katz blog | ComputationalLegalStudies.com corp | LexPredict.com edu | illinois tech - chicago kent law lab | TheLawLab.com #MakeLawBetter page | DanielMartinKatz.com
  2. MY OPENING STATEMENT

  3. IS THE MOST TRIVIALLY OBVIOUS OF ALL OBSERVATIONS

  4. AT ALL LEVELS …

  5. AND NOTWITHSTANDING THE SUBMARKET IN QUESTION …

  6. LAW IS FAILING TO DELIVER VALUE COMMENSURATE WITH THE COSTS

    WE IMPOSE …
  7. None
  8. THERE ARE MANY REASONS FOR THE CHALLENGES WE FACE …

  9. BUT I THINK THE MOST SIMPLE EXPLANATION IS THAT …

  10. THIS IS A FIELD HISTORICALLY CENTERED AROUND SUBJECT MATTER EXPERTISE

  11. AND *NOT* FOCUSED ON OPERATIONAL EXCELLENCE

  12. None
  13. SO OUR CONVERSATION IS *NOT* ABOUT THE CONTENT OF ANY

    PARTICULAR LEGAL RULE …
  14. INSTEAD THIS IS ABOUT HOW WE CAN CONTINUE TO …

    #MAKELAWBETTER
  15. BECAUSE NOTWITHSTANDING THE CHALLENGES

  16. IT IS NOT ALL DOOM AND GLOOM …

  17. THERE ARE GREEN SHOOTS

  18. THERE ARE AN INCREASING NUMBER OF FOLKS …

  19. WORKING GLOBALLY … WORKING DOMESTICALLY …

  20. TO ADVANCE THE LEGAL INNOVATION AGENDA

  21. I WOULD BE REMISS IF I DID NOT MENTION THIS

    EVENT WHICH RECENTLY TOOK PLACE …
  22. 22 COUNTRIES 40 PARTICIPATING CITIES 600+ HACKATHON TEAMS ~5000 PARTICIPANTS

    GLOBALLY
  23. I THINK IT JUST ONE OF MANY SIGNALS THAT INDICATE

    THAT THERE IS A REAL APPETITE FOR CHANGE
  24. None
  25. BY WAY OF INTRODUCTION

  26. I AM AN ACADEMIC

  27. I AM A SCIENTIST & TECHNOLOGIST

  28. I AM A SCIENTIST & TECHNOLOGIST

  29. I AM A TEACHER

  30. LexPredict.com CONSULTANT & ADVISOR TO THE FORTUNE 1000, AM LAW

    200, LEGAL TECH STARTUPS, ETC.
  31. I AM IN THE LEGAL INNOVATION AND VENTURE SPACE AS

    AN ADVISOR
  32. LexPredict.com I AM AN EMPLOYER 15+ TEAM MEMBERS

  33. I MENTION ALL OF THIS ONLY SO THAT YOU MIGHT

    BE ABLE TO ORIENT SOME OF MY COMMENTARY
  34. AND UNDERSTAND THAT I AM *NOT* A MERE SPECTATOR OR

    COMMENTATOR BUT RATHER AN ACTIVE PARTICIPANT … #SKININTHEGAME
  35. SO TODAY ALLOW ME TO SHARE SOME OF MY NOTES

    FROM THE FIELD
  36. THE LEGAL INNOVATION AGENDA

  37. None
  38. WHEN WE TALK ABOUT ‘INNOVATION’ IN LEGAL …

  39. THE ROBOT LAWYERS NARRATIVE IS THE FAVORITE STORY IN THE

    MEDIA
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  48. None
  49. THERE IS MUCH MORE TO THE LEGAL INNOVATION CONVERSATION

  50. IN OTHER WORDS, #LEGALINNOVATION IS FAR BROADER THAN JUST #LEGALTECH

    PER SE
  51. LEGAL INNOVATION LEGAL TECH

  52. LEGAL INNOVATION CAN BE DECOMPOSED INTO AT LEAST SIX VECTORS

  53. SIX VECTORS OF LEGAL INNOVATION

  54. PROCESS IMPROVEMENT A.I. + LEGAL ANALYTICS HUMAN CAPITAL + CULTURE

    INTELLIGENT MONETIZATION MARKET(S) STRUCTURE + DYNAMICS PRODUCTIZATION AND SCALE
  55. None
  56. MARKET(S) STRUCTURE

  57. OF COURSE THERE IS NO LEGAL ‘MARKET’ PER SE BUT

    RATHER A SET OF SUBMARKETS
  58. (VISUAL VIA BILL HENDERSON)

  59. Service The Nature of the Offering Type of Client (Prototypical)

    (Product + Service) Hybrid Product Fortune 1000 Mid Cap Companies Retail A2J THE MARKET(S) IN LAW
  60. ALTHOUGH A MORE NUANCED ACCOUNT COULD BE OFFERED FOR EACH

    SUBMARKET
  61. IN GENERAL, THE INCUMBENTS ARE UNDER ATTACK FROM VARIOUS DIRECTIONS

    … #DEATHBY1000CUTS
  62. NOT ONE SINGLE ‘DISRUPTOR’ BUT RATHER THE SUM OF VARIOUS

    DISRUPTIVE TRENDS #DEATHBY1000CUTS
  63. None
  64. OBVIOUSLY LAW FIRMS ARE ALWAYS COMPETING AGAINST OTHER LAW FIRMS

  65. THE (OTHER) COMPETITORS (i.e. the entities folks might not see)

  66. BIG 4 LPO’S #LEGALTECH CLIENTS

  67. None
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  74. None
  75. BIG 4 LPO’S #LEGALTECH CLIENTS

  76. None
  77. None
  78. "This reflects the remarkable rate of change taking place in

    the legal market," said Liam Brown, Founder and Chairman of Elevate, "and it demonstrates that Elevate has assembled the right team at the right time to help our clients address the complex business challenges and unprecedented cost pressures they face.
  79. None
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  81. None
  82. None
  83. It has $300+ million in revenue in 2016 The equivalent

    of an AMLaw 100 Law Firm
  84. 2000+ total employees

  85. None
  86. LABOR ARBITRAGE PROCESS ARBITRAGE DATA / TECHNOLOGY INTEGRATION LADDER TO

    A FULL PLATFORM SOLUTION
  87. None
  88. BIG 4 LPO’S #LEGALTECH CLIENTS

  89. LEX.STARTUP

  90. OVER THE PAST FEW YEARS, WE HAVE SEEN SIGNIFICANT GROWTH

    IN THE SHEER NUMBER OF STARTUPS …
  91. THERE ARE A VARIETY OF DIFFERENT LISTS

  92. ANGELLIST 749+ ‘LEGAL TECH’ COMPANIES 1800+ IF YOU ONLY SEARCH

    UNDER ‘LEGAL’ HTTPS://ANGEL.CO/COMPANIES? MARKETS%5B%5D=LEGAL+TECH
  93. tech.law.stanford.edu STANFORD CODEX LIST 790+ COMPANIES

  94. 691 COMPANIES ON THIS LIST INCLUDING MY COMPANY WHICH IS

    NOT INCLUDED ON THE OTHER TWO LISTS THEREFORE BOB’S 
 LIST IS THE BEST LIST :) https://www.lawsitesblog.com/2016/04/towards- accurate-listing-legal-tech-startups.html
  95. THINGS ARE HEATING UP ON THE CONTINENT AS WELL BEYOND

    US + UK
  96. FRENCH LEGAL TECH GERMAN LEGAL TECH

  97. BELGIUM LEGAL TECH DUTCH LEGAL TECH

  98. AND BEYOND …

  99. AUSTRALIA LEGAL TECH ISRAEL LEGAL TECH

  100. AFRICAN LEGAL TECH http://legaltechafrica.co/startups/

  101. BRAZIL LEGAL TECH MEXICO LEGAL TECH

  102. None
  103. ALTHOUGH LEGAL IS A RELATIVELY SMALL SECTOR OF THE ECONOMY

  104. WE HAVE HAD SOME WAVES OF VENTURE FUNDING …

  105. HERE ARE JUST A FEW EXAMPLES …

  106. 5.8M SERIES A 2M SEED

  107. 8.7M SERIES A 4.3M SEED ROUND

  108. 12M SERIES B 7M SERIES A 1.8M SEED

  109. 10.25M+ RAISED THUS FAR

  110. 1M SERIES A 150K SEED

  111. 20M SERIES C 7M PRIOR ROUNDS

  112. 125M+ RAISED THUS FAR

  113. OF COURSE WE HAVE HAD A NUMBER OF FAILED COMPANIES

    #PARFORTHECOURSE
  114. BUT WE HAVE ALSO SEEN A NUMBER OF NOTABLE EXITS

  115. None
  116. None
  117. 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 ....
  118. None
  119. None
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  121. COLLECTIVELY THESE ENTITIES ARE DOING THE LION’S SHARE OF LEGAL

    INDUSTRY R + D
  122. AND THERE IS STILL PLENTY TO PLAY FOR …

  123. SIGNIFICANT AMOUNTS OF CAPITAL ARE COMING INTO THE MARKET IN

    JUST THE PAST MONTHS
  124. None
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  133. BIG 4 LPO’S #LEGALTECH CLIENTS

  134. EVERY CUSTOMER IN ANY SECTOR FACES THE DIY VS BUY

    DECISION
  135. None
  136. None
  137. ~450 ~1200+ Number of Attendees Number of Attendees 2016 2017

  138. #cloc2017

  139. #cloc2018 2200+ Attendees

  140. Legal Operations

  141. Legal Operations

  142. Legal Operations

  143. None
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  146. None
  147. SOME OTHER RELATED EXAMPLES

  148. 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.”'
  149. 34!

  150. 37! “I"believe"strongly"that"data"analy2cs"is" a"new"fron2er"in"the"legal"space.”" Susie!Lees! General!Counsel!! Allstate!! “Leveraging" data," not" only"

    that" we" possess" but" that" our" law" firms" have" amassed"over"the"years,"offers"a"plethora" of" un<tapped" opportuni=es—not" simply" to" help" us" forecast" and" manage" legal" expenses," but" also" to" help" our" clients" make"more"informed"business"decisions.”"
  151. None
  152. PRODUCTIZATION AND SCALE

  153. HISTORICALLY - LAW HAS BEEN A SERVICE BUSINESS THROUGH WHICH

    SUBJECT MATTER EXPERTISE IS DELIVERED
  154. HOWEVER, IT IS (SLOWLY) BECOMING MUCH MORE …

  155. Service The Nature of the Offering Type of Client (Prototypical)

    (Product + Service) Hybrid Product Fortune 1000 Mid Cap Companies Retail A2J THE MARKET(S) IN LAW
  156. The Nature of the Offering THE MARKET(S) in LAW Type

    of Client (Prototypical)
  157. PRODUCTIZATION OF LEGAL KNOWLEDGE

  158. PRODUCTIZED KNOWLEDGE IS WHAT THE BIG 4 DO BEST

  159. AMONG OTHER THINGS, PRODUCTS HELP WITH THE ‘JUST IN TIME’

    IMPERATIVE (LABOR CANNOT SCALE INSTANTANEOUSLY)
  160. PRODUCTS ALSO HELP YOU CROSS-SELL SERVICES

  161. PRODUCTS MAKE YOU HARD TO GET RID OF …

  162. PRODUCT BUSINESS WILL TYPICALLY HAVE A HIGHER MULTIPLE (THAT IS

    NOT BY ACCIDENT)
  163. None
  164. SO WHY DON’T WE SEE MORE SCALABLE TECHNOLOGY OFFERINGS CREATED

    BY LAW FIRMS ?
  165. TECH IS A CAPITAL INTENSIVE FIELD

  166. LAW FIRMS ARE PARTNERSHIPS AND GIVEN RULE 5.4 FIRMS CANNOT

    SHARE PROFITS WITH #NONLAWYERS WHERE #NONLAWYERS = HUMANS
  167. THIS IS THE ORIGINAL SIN OF LAW AS A BUSINESS

  168. LAW FIRMS HAVE (1) NO REAL ASSETS (2) CASH ACCOUNTING

    THIS HAS LIMITED SCALE
  169. THIS HAS MADE ACCESS TO CAPITAL FAR MORE DIFFICULT

  170. None
  171. THESE ARE THE HEADWINDS …

  172. HOWEVER, NOTWITHSTANDING EACH OF THESE ENTITIES (AS WELL AS OTHERS)

    ARE UNDERTAKING SOME SORT OF R+D OPERATION
  173. THE RACE IS ON …

  174. None
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  180. GIVEN MICRO- INCENTIVES MIGHT NEED TO CREATE A SEPARATE CAPITAL

    FUNDED R+D OPERATION
  181. None
  182. None
  183. None
  184. WITH SOME NOTABLE EXCEPTIONS … THERE ARE SIMILAR SCALABILITY ISSUES

    IN OTHER SUBMARKETS
  185. None
  186. PROCESS IMPROVEMENT

  187. THE INDUSTRIALIZATION OF THE ARTISAN

  188. ACROSS THE ECONOMY THERE ARE MANY EFFORTS TO CONVERT AN

    ARTISANAL PROCESS INTO AN INDUSTRIAL PROCESS
  189. WE WANT TO ENSURE THAT WE CAN MAINTAIN THE ARTISAN

    ELEMENTS THAT DO ADD VALUE
  190. WITH RESPECT TO A GIVEN PROCESS THERE IS OFTEN A

    SIGNIFICANT SPREAD Kim Craig from Seyfarth Lean Consulting
  191. RECENTLY MET WITH THE GENERAL COUNSEL OF A LARGE COMPANY

    WHO OVER PAST DECADE HAD REDUCED THE LEGAL EXPENDITURES OF THE COMPANY BY NEARLY 50% USING THE LEAN METHODOLOGY
  192. LEAN, SIX SIGMA AND OTHER PROCESS IMPROVEMENT METHODOLOGIES

  193. CAN HELP IMPROVE ALMOST EVERY SUBSECTOR IN LAW

  194. THE INTELLECTUAL ORIGINS CAN BE TRACED TO A MUCH EARLIER

    TIME
  195. THE INTELLECTUAL ORIGINS CAN BE TRACED TO A MUCH EARLIER

    TIME
  196. the toyota production system lean ideas lean for enterprises (white

    collar, etc.)
  197. CONVERT HIGH VOLATILITY PROCESS

  198. CONVERT HIGH VOLATILITY PROCESS INTO A LOWER VOLATILITY PROCESS

  199. WHAT YOU ARE LEFT WITH IS A VERY USEFUL ARTIFACT

  200. THE PROCESS MAP

  201. IT CAN AID IN Increasing Response Times Predicting Resource Loads

    Coordination Across Stakeholders Increasing Margins on Work
  202. I AM VERY HAPPY TO HAVE THE CHANCE TO HELP

    CO-TEACH THIS CLASS
  203. None
  204. SOME ADDITIONAL RESOURCES

  205. None
  206. None
  207. None
  208. ARTIFICIAL INTELLIGENCE + LEGAL ANALYTICS

  209. THIS IS A TOPIC FOR WHICH I AM OFTEN CALLED

    UPON TO COMMENT
  210. AND FOR WHICH A FULL FLEDGED PRESENTATION COULD BE OFFERED

  211. https://www.slideshare.net/Danielkatz/ artificial-intelligence-and-law-a-primer ACCESS MORE HERE

  212. ARTIFICIAL INTELLIGENCE IS A BROAD FIELD

  213. LETS LOOK AT THESE SPECIFIC SUBFIELDS

  214. data driven AI rules based AI

  215. None
  216. EXPERT SYSTEMS

  217. http://www.reinventlawchannel.com/richard-susskind- future-of-artificial-intelligence-and-law RICHARD SUSSKIND DEVELOPED THE FIRST EXPERT SYSTEM IN

    LAW IN THE 1980’S
  218. HERE ARE SOME MORE CONTEMPORARY EXAMPLES …

  219. BUT THE BASIC IDEA IS TO ENCODE THE RULES THAT

    GOVERN A DECISION MAKING PROCESS AND TURN IT INTO SOFTWARE
  220. TURBOTAX IS THE MOST COMMERCIALLY SUCCESSFUL EXPERT SYSTEM OF ALL

    TIME (30+ MILLION USERS)
  221. (BUT WITH OTHER INCREASING INTERESTING CAPABILITIES) “DRAG + DROP A.I.”

    FOR BUILDING LEGAL EXPERT SYSTEMS
  222. EXPERT SYSTEMS FOR ACCESS TO JUSTICE #A2J #A2JAUTHOR DECISION TREE

    A2J AUTHOR www.a2jauthor.org Used over 3.5 Million times 2.1 Million Documents generated IMPACT
  223. EXPERT SYSTEMS WILL BECOME CHATBOTS (THUS HELPING BRIDGE THE DATA

    VS RULES DIVIDE)
  224. None
  225. DATA DRIVEN A.I.

  226. THE ALTERNATIVE TO HARD CODING THE RULES IS TO LET

    DATA DO THE LIFTING …
  227. DATA DRIVEN A.I. = MACHINE LEARNING NATURAL LANGUAGE PROCESSING

  228. None
  229. THE ULTIMATE GOAL IS TO PREDICT SOME CLASS OF LEGAL

    OUTCOMES
  230. HERE ARE JUST A FEW USE CASES IN LAW

  231. #Predict Relevant Documents Data Driven EDiscovery/Due Diligence (Predictive Coding)

  232. #Predict Relevant Documents Data Driven EDiscovery/Due Diligence (Predictive Coding) #Predict

    Contract Terms/Outcomes Data Driven Transactional Work
  233. #Predict Relevant Documents Data Driven EDiscovery/Due Diligence (Predictive Coding) #Predict

    Rogue Behavior Data Driven Compliance #Predict Contract Terms/Outcomes Data Driven Transactional Work
  234. #Predict Relevant Documents #Predict Case Outcomes / Costs Data Driven

    Legal Underwriting Data Driven EDiscovery/Due Diligence (Predictive Coding) #Predict Rogue Behavior Data Driven Compliance #Predict Contract Terms/Outcomes Data Driven Transactional Work
  235. #Predict Relevant Documents #Predict Case Outcomes / Costs Data Driven

    Legal Underwriting Data Driven EDiscovery/Due Diligence (Predictive Coding) #Predict Rogue Behavior Data Driven Compliance #Predict Contract Terms/Outcomes Data Driven Transactional Work #Predict Regulatory Outcomes Data Driven Lobbying, etc.
  236. None
  237. IN MANY INSTANCES BLENDS OF INTELLIGENCE WILL OUTPERFORM A SINGLE

    STREAM OF INTELLIGENCE
  238. THE PSEUDOCODE OF OUR TIMES …

  239. HUMANS + MACHINES HUMANS OR MACHINES >

  240. Professor Katz noted …“We believe the blend of experts, crowds,

    and algorithms is the secret sauce for the whole thing.” May 2nd 2017
  241. None
  242. THE STRUCTURE OF HOW THE WORK IS DONE

  243. A.I. Tool Suite (Legal) Data Scientist Subject Matter Expert(s) +

    +
  244. the path (hint: it’s hard to skip steps) Current State

    Assessment Strategic Planning Tool Selection Solution Design Descriptive Analytics Diagnostics Forecasting
  245. Simple Data Models Claim&Type& Statutes& Outcome& Payout& 00001& Employment&–& Single&Plain>ff&&

    Race& Title&VII& SeCled& $10,000& 00002& Employment&–& Single&Plain>ff&& Race& Title&VII& SeCled& $70,000& 00003& Employment&–& Single&Plain>ff&& Age& Title&VII& & Summary& Judgment& N/A& 00004& Employment&–& Single&Plain>ff&& Gender& Title&VII& & Dismissed& N/A& 00005& Employment&–& Single&Plain>ff&& Age& Title&VII& & Dismissed& N/A& 00006& Employment&–& Single&Plain>ff&& Disability& ADA&Title&III& SeCled& $21,000& Ma4er&No& Ma4er&Type& 00001& Employment&–& Single&Plain>ff&& 00002& Employment&–& Single&Plain>ff&& 00003& Employment&–& Single&Plain>ff&& 00004& Employment&–& Single&Plain>ff&& 00005& Employment&–& Single&Plain>ff&& 00006& Employment&–& Single&Plain>ff&& General Practice-Specific
  246. Complex Models Too Lawsuits Docket Record Related Disputes

  247. Fill in the gaps $10k Base Damages Claimed Filed in

    ‘Unfriendly’ Jurisdiction Conservative Appointed Judge Repeat Plaintiff’s Counsel $6.3k + $3.1k (Yes) - $4.4k (No) + $4.2k per case (<= 6 cases) + $0.40 per $1 claimed - $1.6k per case (7 < cases) Claim Type + $2.3k (Disability) - $7k (Age) Matter Management Matter Management Matter Management Outside Source [ ]
  248. Practice- Related Data Synthesis and Transformation Interface and Interaction Task

    Norms Collaboration Culture Coordination PuQng&It&Together&
  249. None
  250. None
  251. LET ME OFFER JUST A FEW OTHER OBSERVATIONS ON THE

    STATE OF A.I. AND LAW
  252. WE NEED MORE PEER REVIEWED VALIDATION STUDIES (1)

  253. AND LESS MARKETING MATERIAL

  254. THERE ARE AN INCREASING NUMBER OF RELEVANT ACADEMIC PAPERS (AND

    IN SOME CASES ASSOCIATED COMPANIES)
  255. None
  256. None
  257. None
  258. None
  259. “…I study choice of law by analyzing the nearly 1,000,000

    contracts that have been disclosed to the Securities and Exchange Commission between 1996–2012.”
  260. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0174698 Katz DM, Bommarito MJ II, Blackman J (2017), A

    General Approach for Predicting the Behavior of the Supreme Court of the United States. PLoS ONE 12(4): e0174698.
  261. None
  262. (2) ECONOMICS ASSOCIATED WITH LEGAL A.I. ARE RAPIDLY CHANGING

  263. MACHINE LEARNING AS A SERVICE #MLaaS + ENTERPRISE OPEN SOURCE

    MOVEMENT
  264. ARE FUNDAMENTALLY CHANGING THE POSSIBILITY FRONTIER

  265. WE ARE GETTING A BROADER MENU

  266. WE ARE GETTING MORE STANDARDIZATION

  267. I WORK THIS OUT FURTHER HERE …

  268. https://www.slideshare.net/Danielkatz/ machine-learning-as-a-service-mlaas-open- source-and-the-future-of-legal-analytics-by- daniel-martin-katz-michael-j-bommarito-ii

  269. BUT SUFFICE TO SAY IS NO LONGER THE ONLY GAME

    IN TOWN
  270. Machine Learning as a Service #MLaaS

  271. Machine Learning as a Service #MLaaS

  272. Machine Learning as a Service #MLaaS

  273. Machine Learning as a Service #MLaaS

  274. None
  275. (3) WE WILL GO THE WAY OF THE WORLD AND

    SEE MORE OPEN SOURCE OFFERINGS IN LEGAL
  276. WE NEED MORE #OPENSOURCE IN LAW

  277. I AM PRACTICING WHAT I PREACH

  278. None
  279. contraxsuite.com

  280. https://github.com/LexPredict/lexpredict-contraxsuite

  281. None
  282. None
  283. INTELLIGENT MONETIZATION

  284. ONE OF THE CHALLENGES THAT LEGAL INNOVATORS HAVE FACED IS

    PROBLEM SELECTION
  285. PERFORMANCE PEDIGREE > HISTORICALLY IN LAW

  286. PERFORMANCE IS *NOT* RIGOROUSLY MEASURED …

  287. INDEED, ALMOST EVERY TIME WE BENCHMARK EXPERTS THEY ARE NOT

    NEARLY AS GOOD AS WE THINK
  288. EVEN IF YOU HAVE A BETTER MOUSETRAP …

  289. IF YOU ARE 5% OR 10%+ BETTER AT SOMETHING

  290. YOU NEED TO FIND A CUSTOMER (CLIENT) WHO ACTUALLY CARES

  291. None
  292. SOMETIMES IT IS WAY EASIER TO SELL #LEGALINNOVATION TYPE IDEAS

  293. TO OTHER SECTORS IMPACTED BY LEGAL DECISIONS OR LEGAL RISK

  294. IN OTHER WORDS, ACROSS THE ENTIRE ECONOMY …

  295. THE BOUNDARIES BETWEEN MARKET SECTORS ARE BEGINNING TO EVAPORATE …

  296. LEGALTECH REGTECH FINTECH INSURTECH ON THE MARGINS THERE IS NO

    REAL DIFFERENCE BETWEEN THE FOLLOWING FIELDS -
  297. WHICH IS JUST A WAY OF IDENTIFYING THAT ASPECTS OF

    ‘LAW’ ARE ACTUALLY JUST FINANCE, INSURANCE IN THE FIRST PLACE …
  298. LITIGATION FUNDING

  299. LITIGATION FUNDING +1568% in 4 years

  300. LAW AS INSURANCE

  301. EVENT DRIVEN LEGAL TRADING

  302. LEGAL SIGNAL PROCESSING

  303. None
  304. https://www.slideshare.net/Danielkatz/fin-legal-tech-laws-future-from- finances-past-some-thoughts-about-the-financialization-of-the-law- professors-daniel-martin-katz-michael-j-bommarito

  305. None
  306. HUMAN CAPITAL + CULTURE

  307. THE DEMOGRAPHIC REALITY …

  308. WE ARE ABOUT TO HAVE THE LARGEST GENERATIONAL TRANSFER IN

    HUMAN HISTORY
  309. THIS IS A MAJOR CHALLENGE TO EVERY ORGANIZATION

  310. None
  311. ORGANIZATIONS NEED DIFFERENT (BETTER) HUMAN CAPITAL IN ORDER TO SUPPORT

    ALL OF THESE TRENDS HIGHLIGHTED HEREIN
  312. AND THIS SHOULD BE REFLECTED IN THE CONTENT OF LEGAL

    EDUCATION
  313. LIBERAL ARTS LEGAL.EDU

  314. POLYTECHNIC LEGAL.EDU LIBERAL ARTS LEGAL.EDU

  315. Daniel Martin Katz, The MIT School of Law? A Perspective

    on Legal Education in the 21st Century, University of Illinois Law Review (2014)
  316. I OUTLINE IN THIS PAPER MY VISION FOR WHAT LAW.EDU

    COULD BE ... (AND I AM NOT ALONE IN THIS VIEW)
  317. None
  318. None
  319. None
  320. SO WITH THAT UNDERSTANDING OF THE CURRENT INPUTS, DYNAMICS AND

    CONSTRAINTS
  321. I WOULD LIKE TO LOOK OVER THE #LEGALHORIZON …

  322. FROM CHAOS + COMPLEXITY TO REINVENTION

  323. BLOCKCHAINLAWCLASS.COM

  324. FROM HUNTER GATHERER SOCIETIES TO A HIGHLY COMPLEX GLOBAL ECONOMIC

    SYSTEM(S)
  325. ECONOMIC HISTORY TO DATE CAN BE SEEN AS A QUEST

    TO SCALE TRUST AND LOWER TRANSACTION COSTS
  326. MESOPOTAMIA GREECE ROME MEDIEVAL ERA MERCHANT LAW RENAISSANCE PRE ANALOG

    ERA THE CORPORATION MARITIME LAW + INSURANCE HUNTER GATHERERS CODE OF HAMMURABI SOME EARLY TRANSACTION ENHANCING INNOVATIONS AND SOCIETIES
  327. THERE ARE A VARIETY OF DIFFERENT WAYS TO DIVIDE UP

    RECENT HISTORY AND PROJECT FORWARD …
  328. WE COULD DIVIDE UP THE PAST ~150 YEARS INTO THREE

    SEPARATE ERAS ANALOG ERA DIGITAL ERA COMPUTATIONAL ERA
  329. EACH ERA LAYERS UPON THE PRIOR PERIODS … ANALOG ERA

    DIGITAL ERA COMPUTATIONAL ERA
  330. THE WORLD ECONOMIC FORUM CALLS THIS THE ‘FOURTH INDUSTRIAL REVOLUTION’

  331. None
  332. I WOULD CALL IT THE COMPUTATIONAL AGE …

  333. INDEED HERE IS OUR BLOG WHICH HAS BEEN RUN SINCE

    2009 (FEEL FREE TO SET THIS AS YOUR HOMEPAGE) HTTPS://COMPUTATIONALLEGALSTUDIES.COM/
  334. TELEGRAPH TELEPHONES INTERNET LONG TAIL COMMERCE (MERCHANT LAW TAKE 2)

    CRYPTO INFRASTRUCTURE ANALOG ERA DIGITAL ERA COMPUTATIONAL ERA INTERNET OF THINGS FIAT CURRENCY EARLY COMPUTERS GLOBALIZATION PERSONAL COMPUTERS ARTIFICIAL INTELLIGENCE AUTOMOBILE CREDIT CARDS CHARGE CARDS
  335. SOME OF THE KEY INGREDIENTS OF THE COMPUTATIONAL ERA …

  336. CRYPTO INFRASTRUCTURE INTERNET OF THINGS ARTIFICIAL INTELLIGENCE + + ETC.

    + { }
  337. None
  338. THESE PHASES MAP REASONABLY WELL ON TO WHAT WE HAVE

    SEEN (AND WILL LIKELY SOON SEE) IN THE FIELD OF LEGAL INNOVATION
  339. ANALOG DIGITAL COMPUTATIONAL

  340. COMPUTATIONAL Chaos + Complexity Process + Predictability Reinvention + Value

    Creation ANALOG DIGITAL
  341. None
  342. A FEW EXAMPLES OF THE PATH TO REINVENTION …

  343. (1) CONTRACTS / TRANSACTIONS

  344. CHAOS + COMPLEXITY

  345. CHAOS + COMPLEXITY PROCESS + PREDICTABILITY

  346. Contract Management Dashboard Open Contracts for Review 150 11.7% compared

    to 170 this time last year Contracts by Type NDA’s Master Service Agreements Contracts Reviewed (YTD) 1798 9.3.% compared to 1983 this time last year Input Risk Mitigated $6.4M 30.0% compared to $5M this time last year Average Cycle Time (YTD) 19 days 26.7% compared to 15 days last year Total Value of All Contracts $600.2M 29.6% compared to $500M this time last year Software Licenses Sales Agreements 602 426 246 312 Global Filters from 01/01/2017 Status to 12/31/2017 Practice Matter Type 0 7 13 20 26 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Average Contract Cycle Time Agreement Name Agreement Type Days Since Receipt Division Contracts by Complexity Low Medium High 48% 37% 15% Contracts Awaiting Review NDA Software License NDA Sales Agreement MSA John Smith HR Packet MS Jane Jones HR Packet Widget Agreement Acme Services HR IT HR Sales Team IT 3 29 8 37 56
  347. WHILE THIS IS A HELPFUL STEP IT IS NOT REINVENTION

  348. AN EXAMPLE OF REINVENTION

  349. https://medium.com/aigang-network/the-synergy- between-insurance-and-blockchain-77da2849c211

  350. “WEATHER INDEXED INSURANCE IS BASED ON LOCAL WEATHER INDICES. PAYOUTS

    ARE TRIGGERED BY THE SPECIFIED COMPONENTS OF THE INDEX RATHER THAN CROP YIELDS” https://wrma.org/weather-risk-by-application/agriculture/
  351. INSURANCE CONTRACT CONTINGENCY STORED ON BLOCKCHAIN RAW SENSOR DATA (PRIVATE

    OR PUBLIC) PREPROCESSED AND SERVED UP REGULARLY CHECK FOR CONTINGENCY SATISFACTION IF CONTINGENCY IS SATISFIED INITIATE PAYMENT OR START AUDIT PROTOCOL OR PROCEED TO FINAL HUMAN APPROVAL
  352. EARLY EXAMPLES IN LAW-LAW LAND

  353. None
  354. None
  355. None
  356. None
  357. None
  358. None
  359. None
  360. (2) DISCOVERY COMPLIANCE CONVERGENCE

  361. THE DISCOVERY + COMPLIANCE CONVERGENCE

  362. None
  363. None
  364. None
  365. None
  366. THE GOAL SHOULD BE PREVENTION

  367. BEHAVIORAL PATTERNS AND SIGNALS INTELLIGENCE

  368. #DOLESSLAW http://www.reinventlawchannel.com/ron-friedmann-do-less-law/

  369. None
  370. (3) LEGAL RISK MANAGEMENT BECOMES INSURANCE

  371. TODAY WE USE LAWYERS AS THE COMPUTERS OF LEGAL RISKS

  372. BUT IN THE OTHER APPLICATIONS WE USE UNDERWRITING AND RISK

    TRANSFER VEHICLES
  373. THIS IS JUST ONE EXAMPLE OF HOW WE (PARTIALLY) DELAWYERED

    A LEGAL PROCESS
  374. LAW AS INSURANCE

  375. HERE WE ALMOST FULL DELAWYERED THE TRANSACTION

  376. None
  377. THERE IS MORE WHERE THAT CAME FROM …

  378. LITIGATION FUNDING

  379. LITIGATION FUNDING +1568% in 4 years

  380. WHERE LAW IS FINANCE LAW WILL LOOK MORE LIKE FINANCE

    #PROPTRADING
  381. CLAIM MOST OF TODAY’S LEGAL AI BUYERS SELECT ON THE

    BASIS OF UI/UX NOT ACTUAL PERFORMANCE SIZZLE > STEAK
  382. “... law firms will participate in an arms race where

    they advertise their AI models, and the future of the law business is monetizing bespoke AI models.” http://www.legalexecutiveinstitute.com/iltacon-2018-innovation/
  383. None
  384. (4) PLATFORMS AND THE LEGAL INFO ECONOMY

  385. TWO YEARS AGO

  386. MICHAEL SKAPINKER FROM THE FT WROTE THE FOLLOWING

  387. APRIL 11 2016

  388. AMONG OTHER THINGS THE ARTICLE EXPLORED CHANGES IN THE BUSINESS

    OF LAW
  389. INCLUDING THE POSSIBILITY OF AN ‘UBER MOMENT’ FOR LAWYERS

  390. THERE HAVE BEEN MANY OTHER ARTICLES ALSO EXPLORING THESE DYNAMICS

  391. AND IT SEEMS THAT THIS IDEA IS …

  392. VERY MUCH IN THE ZEITGEIST (IN ONE FORM OR ANOTHER)

  393. WHETHER IN LAW OR IN ANOTHER SECTOR OF THE ECONOMY

  394. THE DIGITAL PLATFORM IS ONE OF THE DEFINING FEATURES OF

    THE POST INTERNET ECONOMY
  395. ‘DIGITAL PLATFORMS ARE COMPLICATED MIXTURES OF SOFTWARE, HARDWARE, OPERATIONS, AND

    NETWORKS’
  396. FREELANCE LABOR (UPWORK, ELANCE, TASK RABBIT) SOCIAL NETWORKING (FACEBOOK, LINKEDIN)

    INTERNET BASED RETAIL (AMAZON, EBAY, ANGIE’S LIST) FINANCIAL / HR FUNCTIONS (WORKDAY, WORKFUSION) TRANSPORTATION (UBER, LYFT, SIDECAR) MOBILE PAYMENT (MAHALA, SQUARE)
  397. PLATFORMS AND THE BUSINESS OF LAW

  398. APPLYING A SOMEWHAT LOOSE DEFINITION …

  399. THE LAW FIRM COULD BE CALLED THE ORIGINAL ‘PLATFORM’ IN

    LAW
  400. ENTREPRENEURIALLY MINDED LAW FIRM LEADERS WERE ABLE TO ASSEMBLE TEAMS

    OF EXPERTS
  401. PARTICULARLY ACROSS THE 20TH CENTURY THE LAW FIRM REPLACED A

    MUCH MORE DECENTRALIZED FORM OF INDUSTRIAL ORGANIZATION
  402. WHILE AN ANALOG FORM OF PLATFORM, THE LAW FIRM ALLOWED

    FOR A DIFFUSE SET OF EXPERTISE TO BE BUNDLED AND SOLD TO A CLIENT
  403. OTHERWISE THE CLIENT HAD TO ORGANIZE THE NECESSARY EXPERTS AND

    ASSOCIATED LABOR TO SUPPORT THEIR SPECIFIC LEGAL TASKS …
  404. THE CLIENTS THEMSELVES ARE WORKING TO DEVELOP PLATFORMS AND ECOSYSTEMS

  405. NIKE ALLIANCE

  406. GE LAWYER RATING SYSTEM “YELP FOR LAW’ ?

  407. ON THE RETAIL SIDE OF THE BUSINESS … LEGALZOOM, CLIO,

    AVVO ARE ALL MAKING PLATFORM PLAYS
  408. THERE ARE SEVERAL VERSIONS OF ‘UBER FOR LAWSUIT FUNDING’

  409. AND THERE ARE MANY OTHER VERSIONS OF ‘UBER FOR LAWYERS’

  410. ON THE TECH SIDE OF THE LEGAL BUSINESS …

  411. THERE IS ALSO MOVEMENT TOWARD PLATFORM OFFERINGS …

  412. None
  413. None
  414. None
  415. THIS WILL BE A BIG PART OF THE LAW BUSINESS

    OF THE 2020’S …
  416. (5) SCALABLE JUSTICE AND THE MODRIA OF EVERYTHING

  417. WHY DO HAVE TO ‘GO TO COURT’ ?

  418. CAN’T WE HAVE MORE SCALABLE VERSION OF THE JUSTICE SYSTEM?

  419. EBAY

  420. CAN WE USE VASTLY ALTERNATIVE DELIVERY MODELS?

  421. FIRST WE WILL GET CHATBOTS …

  422. None
  423. ? Meet Ellie a Virtual Therapist developed at USC THE

    TRUE ROBOT LAWYER
  424. None
  425. CLOSING ARGUMENT

  426. LEGAL INNOVATION IS A 5000 YEAR OLD FIELD

  427. BUT AS NOTED EARLIER WE SORT OF STALLED OUT SOMEWHERE

    ALONG THE WAY …
  428. WE ARE GETTING THINGS BACK ON TRACK …

  429. I AM BULLISH ON THE FUTURE …

  430. NOT BECAUSE I AM AN OPTIMIST

  431. BUT RATHER BECAUSE OF TRENDS THAT ARE IN PLAY

  432. AND THE OPPORTUNITIES THAT LIE AHEAD

  433. None
  434. TO THE LEGAL INNOVATORS …

  435. I SAY — STAY THE COURSE

  436. THE LEGAL INNOVATION AGENDA

  437. IS GLOBAL

  438. IS GLOBAL IS GROWING

  439. IS GLOBAL IS GROWING AND IS SLOWLY WINNING

  440. None
  441. None
  442. None
  443. None
  444. ComputationalLegalStudies.com BLOG

  445. @ computational

  446. Daniel Martin Katz @ computational computationallegalstudies.com lexpredict.com danielmartinkatz.com illinois tech

    - chicago kent college of law @ thelawlab.com