Some Thoughts on Modeling Legal Systems

“Modeling the Law & Justice System” - Virtual Talk at the Indian Institute of Technology - Delhi

This presentation highlights the Complexity Challenge in Law, Six Forms of Modeling Legal Systems and concludes with some thoughts about Law + STEM.

Thanks to the following organizations for hosting me -
DAKSH
Indian Institute of Technology, Delhi
National Law University, Delhi
DCoE IIT, Delhi

Transcript

1. S O M E T H O U G H T S O N M O D E L I N G L E G A L SY ST E M S @computational professor daniel martin katz danielmartinkatz.com Illinois tech - chicago kent law computationallegalstudies.com https://bit.ly/3yxhY2e
4. TO DAY L E T M E B E G I N W I T H A N O B V I O U S STAT E M E N T …
5. W H I C H ( F O R S O M E ) M I G H T A L S O B E A P R OVO CAT I V E STAT E M E N T …
6. L AW I S E N G I N E E R I N G
7. H O W E V E R , TO DAY I T I S A PA RT I C U L A R TY P E O F E N G I N E E R I N G
8. I M P L E M E N T E D I N A PA RT I C U L A R M A N N E R
9. T H E Q U E ST I O N I S TO W H AT E X T E N T T H E F I E L D O F L AW M I G H T B E N E F I T F R O M
10. I N S I G H T S O F F E R E D B Y T H E T R A D I T I O N A L ST E M ACA D E M I C F I E L D S
12. F O R T H E B E N E F I T O F O U R M U LT I D I S C I P L I N A R Y AU D I E N C E
13. L E T U S STA RT W I T H T H E B R OA D E ST P O S S I B L E Q U E ST I O N
14. W H AT I S T H E P U R P O S E O F L AW A N D L E G A L I N ST I T U T I O N S ?
15. S O C I E T I E S C R E AT E R U L E S TO T R Y TO G OV E R N VA R I O U S F O R M S O F S O C I A L , E CO N O M I C A N D P O L I T I CA L B E H AV I O R
16. S O C I E T I E S C R E AT E G OV E R N A N C E I N ST I T U T I O N S D E VOT E D TO VA R I O U S L E G A L TA S K S
17. R U L E M A K I N G R U L E I N T E R P R E TAT I O N R U L E E N F O R C E M E N T T H E S E TA S K S I N C LU D E
18. O F CO U R S E A S T H I S I N VO LV E S H U M A N S T H E S E P R O C E S S E S A R E N OT N E C E S S A R I LY N E U T R A L
19. A N D TO P D O W N G OV E R N M E N TA L R U L E S A R E FA R F R O M T H E O N LY D R I V E R S O F B E H AV I O R
20. B U T T H E G U I D I N G P U R P O S E I S TO H E L P E N G I N E E R C E RTA I N C L A S S E S O F B E H AV I O R
21. A N D P R E V E N T / M I N I M I Z E OT H E R F O R M S O F B E H AV I O R
22. I H O P E YO U CA N S E E A L R E A DY T H AT T H I S I S AC T UA L LY A G R A N D E N G I N E E R I N G C H A L L E N G E
23. T H I S C H A L L E N G E I S O N E TO W H I C H T H O S E B E YO N D T H E T R A D I T I O N A L F I E L D O F L AW
24. A R E W E L L P O I S E D TO CO L L A B O R AT I V E LY CO N T R I B U T E
26. BY WAY OF INTRODUCTION
27. I AM AN ACADEMIC
28. I AM A SCIENTIST & TECHNOLOGIST
29. I AM A SCIENTIST & TECHNOLOGIST
30. I AM A SCIENTIST & TECHNOLOGIST
31. I AM A SCIENTIST & TECHNOLOGIST https://legaltechcenter.de/en/index.html
32. I AM A TEACHER
33. I AM A TEACHER
34. I AM A TEACHER
35. I AM A THOUGHT LEADER
36. I AM A THOUGHT LEADER
37. I AM IN THE LEGAL INNOVATION AND VENTURE SPACE AS AN ADVISOR
38. LexPredict.com CONSULTANT & ADVISOR TO THE FORTUNE 1000, AM LAW 200, LEGAL TECH STARTUPS, ETC.
39. I AM A SUCCESSFUL ENTREPRENEUR
40. I MENTION ALL OF THIS ONLY SO THAT YOU MIGHT BE ABLE TO ORIENT SOME OF MY COMMENTARY
41. AND UNDERSTAND THAT I AM *NOT* A MERE SPECTATOR OR A COMMENTATOR BUT RATHER AN ACTIVE PARTICIPANT … #SKININTHEGAME
42. SO TODAY ALLOW ME TO SHARE SOME OF MY NOTES FROM THE FIELD
44. PA RT I CO N F R O N T I N G T H E CO M P L E X I TY C H A L L E N G E
45. W H E T H E R YO U A R E A L A R G E M U LT I N AT I O N A L CO R P O R AT I O N , A S M A L L B U S I N E S S O R A N I N D I V I D UA L C I T I Z E N …
46. L AW H A S A CO M P L E X I TY C H A L L E N G E …
47. IF YOU TAKE A STEP BACK
48. THE REAL ANIMATING DRIVER IN THE DEMAND FOR UNITS OF LEGAL PRODUCTION
49. IS COMPLEXITY
50. SOCIAL, ECONOMIC AND POLITICAL COMPLEXITY
51. MANIFESTS ITSELF IN OUR DOMAIN AS LEGAL COMPLEXITY
52. WHILE IT IS SOMEWHAT HARD TO PRECISELY DEFINE …
54. VIRTUALLY EVERY WAY YOU MIGHT CONSIDER IT LEGAL COMPLEXITY HAS GROWN
55. DANIEL MARTIN KATZ, CORINNA COUPETTE, JANIS BECKEDORF & DIRK HARTUNG, COMPLEX SOCIETIES AND THE GROWTH OF THE LAW, 10 SCIENTIFIC REPORTS 18737 (2020) CORINNA COUPETTE, JANIS BECKEDORF, DIRK HARTUNG, MICHAEL BOMMARITO, & DANIEL MARTIN KATZ, MEASURING LAW OVER TIME: A NETWORK ANALYTICAL FRAMEWORK WITH AN APPLICATION TO STATUTES AND REGULATIONS IN THE UNITED STATES AND GERMANY, FRONT. PHYS. (2021 FORTHCOMING)
56. SIGNIFICANT GROWTH IN LAWS AND REGULATIONS
57. SO THE QUESTION IS HOW TO MATCH THAT COMPLEXITY WITH THE APPROPRIATE
58. COMPLEXITY MITIGATION TACTICS …
59. MIXTURES OF PEOPLE, PROCESS AND TECHNOLOGY
60. DESIGNING MORE SCALABLE SYSTEMS
61. BECAUSE THE LEGACY MODEL HAS BEEN
62. TO USE LOTS OF LABOR TO SOLVE HIGH COMPLEXITY PROBLEMS
63. BUT THAT APPEARS TO BE REACHING ITS PRACTICAL AND ECONOMIC LIMITS
64. THE APPROACH NEEDS TO BE MORE FUNDAMENTAL
65. AND LEVERAGE THE BEST OF SCIENCE AND TECH
66. http://prawfsblawg.blogs.com/prawfsblawg/2017/03/-complexity-mitigation-strategies- for-law-law-land-and-beyond-and-some-other-thoughts-on-hadfield-su.html#more SOME THOUGHTS ON LEGAL COMPLEXITY MITIGATION STRATEGIES
68. PA RT I I S I X F L AVO R S O F M O D E L I N G
69. M O D E L S O F VA R I O U S F L AVO R S CA N B E S E E N AC R O S S S C I E N C E A N D E N G I N E E R I N G
70. T H U S , I WA N T TO D I S C U S S A S E R I E S O F I D E A S A S S O C I AT E D W I T H
71. T H E M O D E L I N G O F L E G A L SY ST E M S
73. T H E DA K S H C E N T R E O F E XC E L L E N C E F O R L AW A N D T E C H N O LO GY AT I I T- D E L H I ( D CO E ) WA S E STA B L I S H E D I N O C TO B E R 2 0 2 0 A S A CO L L A B O R AT I O N B E T W E E N I N D I A N I N ST I T U T E O F T E C H N O LO GY ( I I T ) D E L H I A N D DA K S H S O C I E TY, B E N G A LU R U H I G H L I G H T S F R O M A R E C E N T CA L L F O R P R OJ E C T S A . M O D E L I N G T H E J U ST I C E SY ST E M B . TO O L TO M A K E L AW S M O R E ACC E S S I B L E TO C I T I Z E N S , A N D CA S E D U R AT I O N & O U TCO M E P R E D I C TO R C . CA S E F LO W M A N AG E M E N T D. S C I E N T I F I C S C H E D U L I N G O F CA S E S & WO R K A L LO CAT I O N F O R J U D G E S
74. A . M O D E L I N G T H E J U ST I C E SY ST E M B . TO O L TO M A K E L AW S M O R E ACC E S S I B L E TO C I T I Z E N S , A N D CA S E D U R AT I O N & O U TCO M E P R E D I C TO R C . CA S E F LO W M A N AG E M E N T D. S C I E N T I F I C S C H E D U L I N G O F CA S E S & WO R K A L LO CAT I O N F O R J U D G E S A L L F O U R O F T H E S E AC T UA L LY I N VO LV E M O D E L S
76. S O W H AT I S M O D E L I N G ?
77. T H E T E R M TA K E S O N D I F F E R E N T M E A N I N G S AC R O S S T H E S C I E N C E S
78. H E R E A R E S O M E E L E M E N T S
79. A M O D E L I S A R E P R E S E N TAT I O N O F A SY ST E M L I K E LY I N VO LV E S A L E V E L O F A B ST R AC T I O N CA N B E U S E D TO U N D E R STA N D B OT H SY ST E M CO M P O N E N T S A N D T H E I R CO N N E C T I O N TO O N E A N OT H E R T H E R E A R E VA R I O U S A P P R OAC H E S O N E CA N U S E
82. AT L E A ST S I X D I F F E R E N T F O R M S O F “ M O D E L I N G ” A R E R E L E VA N T F O R L E G A L SY ST E M S
83. R E M E M B E R E AC H O F T H E S E H A S A N ACCO M PA N Y I N G M E N TA L M O D E L . .
84. B U T L E T U S STA RT AT T H E M AC R O S CA L E M O D E L S A N D WO R K TO WA R D T H E M I C R O S CA L E M I C R O M E S O M AC R O
86. M O D E L I N G TY P E 1 M O D E L I N G T H E L AW I T S E L F ( AG G R E G AT E L E V E L )
87. I H AV E A L R E A DY G I V E N A B I T O F A P R E V I E W O F T H I S A P P R OAC H
88. TA K E T H E L E G A L R U L E S T H E M S E LV E S A N D M O D E L T H E M
89. B OT H STAT I CA L LY A N D A S A F U N C T I O N O F T I M E
90. L AW S CA N O F T E N B E M O D E L E D A S CO M B I N AT I O N A H I E R A R C H Y, R E F E R E N C E N E T WO R K , S E Q U E N C E G R A P H
92. H E R E A R E S O M E E X A M P L E S …
93. Boulet, Romain, Pierre Mazzega, and Daniele Bourcier. "A network approach to the French system of legal codes—part I: analysis of a dense network." Artificial Intelligence and Law 19.4 (2011): 333-355. Boulet, Romain, Pierre Mazzega, and Danièle Bourcier. "Network approach to the French system of legal codes part II: the role of the weights in a network." Artificial Intelligence and Law 26.1 (2018): 23-47.
95. Koniaris, Marios, Ioannis Anagnostopoulos, and Yannis Vassiliou. "Network Analysis in the Legal Domain: A complex model for European Union legal sources." Journal of Complex Networks 6.2 (2017): 243-268.
96. M. Bommarito. & D. Katz. A Mathematical Approach to the Study of the United States Code. Physica A: Statistical Mechanics and its Applications, 389(19), 4195-4200 (2010). D. Katz & M. Bommarito. Measuring the complexity of the law: the United States Code. Artificial intelligence and law, 22(4), 337-374. (2014)
97. H E R E W E I N V E ST I G AT E D A S I N G L E S N A P S H OT O F T H E 2 0 1 0 U N I T E D STAT E S CO D E I N A N E F F O RT TO E X P LO R E I T S CO M P L E X I TY
98. THEN WE STUDIED THE STATUTORY LAW OF TWO LARGE COUNTRIES OVER 25 YEARS DANIEL MARTIN KATZ, CORINNA COUPETTE, JANIS BECKEDORF & DIRK HARTUNG, COMPLEX SOCIETIES AND THE GROWTH OF THE LAW, 10 SCIENTIFIC REPORTS 18737 (2020)
99. LEVERAGED INFO MAP (MAP EQUATION) TO ALGORITHMICALLY REORGANIZE THE STATUTORY LAW INTO MORE COHERENT CATEGORIES (TOPICS)
100. MAP EQUATION MAP EQUATION SOURCE ROSVALL, M., AXELSSON, D. & BERGSTROM, C. THE MAP EQUATION. EUR. PHYS. J. SPEC. TOP. 178, 13–23 (2009).
101. RESULTING CLUSTER QUOTIENT GRAPHS
102. TRACE THE CLUSTER QUOTIENT GRAPHS OVER TIME
103. THEN WE ADDED ALL OF THE FEDERAL LEVEL REGULATIONS TO THE STATUTES CORINNA COUPETTE, JANIS BECKEDORF, DIRK HARTUNG, MICHAEL BOMMARITO, & DANIEL MARTIN KATZ, MEASURING LAW OVER TIME: A NETWORK ANALYTICAL FRAMEWORK WITH AN APPLICATION TO STATUTES AND REGULATIONS IN THE UNITED STATES AND GERMANY, FRONT. PHYS. (2021 FORTHCOMING)
106. OF COURSE THERE ARE EVEN LARGER SCALES (WE ARE ONLY COVERING THE RED TILES)
107. T H I S F L AVO R O F M O D E L I N G I N VO LV E S CO M B I N AT I O N S O F I N F O R M AT I O N T H E O R Y, N E T WO R K S C I E N C E A N D N AT U R A L L A N G UAG E P R O C E S S I N G
109. M O D E L I N G TY P E 2 M E A S U R E SY ST E M L E V E L O U T P U T S
110. H O W WO U L D O N E E VA LUAT E T H E Q UA L I TY O F A L E G A L SY ST E M I N A G I V E N CO U N T RY ?
111. CA N W E CO M PA R E L E G A L SY ST E M S B A S E D U P O N C E RTA I N M E A S U R E S O F Q UA L I TY ?
112. H O W M I G H T W E CO M B I N E A N I N D I V I D UA L M E A S U R E O F Q UA L I TY I N TO A CO M P O S I T E M E A S U R E ?
113. I T I S T H E S E A N D OT H E R R E L AT E D Q U E ST I O N S
114. W H I C H N G O ’ S , R E S E A R C H E R S A N D OT H E R S S E E K TO R E G U L A R LY A N S W E R
115. I T T U R N S O U T T H AT T H E S E Q U E ST I O N S A R E N OT A LWAY S E A SY TO A N S W E R
117. T H E R E A R E LOT S O F M E A S U R E S W H I C H AT T E M P T TO B R OA D LY C H A R AC T E R I Z E F I D E L I TY TO CO N C E P T S S U C H A S ‘ R U L E O F L AW ’
118. B U T T H E G OA L I S TO M OV E F R O M “ I K N O W I T W H E N I S E E I T ”
119. TO M O R E O B J E C T I V E A N D G E N E R A L I Z E D M E A S U R E S
120. AG A I N M U C H E A S I E R S A I D T H A N D O N E
122. H E R E A R E A F E W E X A M P L E S O F PA P E R S A N D P R OJ E C T S O N T H E S U B J E C T
123. 1) SUPPORT OF JUSTICE INSTITUTIONS THROUGH TARGETED INTERVENTIONS THAT IMPROVE THE SPECIALIST FUNCTIONS OF THE JUSTICE SYSTEM 2) LEGAL EMPOWERMENT, THROUGH THE PROTECTION AND PROACTIVE OUTREACH TO WOMEN, THE POOR AND MARGINALIZED GROUPS TO UNDERSTAND AND NAVIGATE THEIR LEGAL PROBLEMS 3) JUSTICE IN SECTORS THROUGH THE STRENGTHENING OF THE REGULATORY FRAMEWORKS AND INSTITUTIONS OF ALL THOSE SECTORS CRITICAL FOR THE ACHIEVEMENT OF BROADER DEVELOPMENT OBJECTIVES 4) DEVELOPMENT OF ANALYTICS AND DIAGNOSTICS TO INFORM POLICY, PROMOTE DIALOGUE AMONG STAKEHOLDERS AND BETTER TARGET REFORMS. WORLD BANK EXPERTISE IN JUSTICE AND DEVELOPMENT THE WORLD BANK HAS WORKED ON JUSTICE AND DEVELOPMENT AROUND THE GLOBE FOR MORE THAN 25 YEARS THROUGH MORE THAN 800 PROJECTS.
124. http://info.worldbank.org/governance/wgi/#doc-methodology
125. https://worldjusticeproject.org/
128. M O D E L I N G TY P E 3 E M P I R I CA L E VA LUAT I O N O F L E G A L R U L E S / P O L I CY M A K I N G
129. A S A N I N T E L L E C T UA L F I E L D
130. L AW FAC E D A C R E D I B I L I TY R E VO LU T I O N
131. W H E R E B Y L AW Y E R S J U D G E S P O L I CY M A K E R S
132. W E R E C R A F T I N G L E G A L R U L E S A N D D O C T R I N E S
133. A N D C R I T I Q U I N G L E G A L R U L E S A N D D O C T R I N E S
134. W I T H O U T A N Y E M P I R I CA L F O C U S O N T H E R E A L WO R L D P E R F O R M A N C E O F T H E S E R U L E S A N D D O C T R I N E S
135. R O U G H LY ~ 2 5 Y E A R S AG O T H E R E B E G A N TO B E ‘ E M P I R I CA L T U R N ’ I N L E G A L S C H O L A R S H I P
136. Legal Scholarship Has become far more ‘empirical’ in nature
140. D E T E R M I N E ( A S B E ST P O S S I B L E ) W H E T H E R A PA RT I C U L A R P O L I CY I N T E RV E N T I O N AC H I E V E S T H E D E S I R E D E N D S TASK
141. MODELING APPROACH CO U L D E M P LOY T R A D I T I O N A L Q UA N T I TAT I V E S O C I A L S C I E N C E M E T H O D S ( S U C H A S R E G R E S S I O N )
142. MODELING APPROACH O R M I G H T I N VO K E M O R E S O P H I ST I CAT E D E CO N O M E T R I C M E T H O D S
143. EXAMPLE METHODS I N ST R U M E N TA L VA R I A B L E S , P R O P E N S I TY S CO R E M ATC H I N G , R U B I N CAU S A L M O D E L , R E G R E S S I O N D I S CO N T I N U I TY, D I F F E R E N C E I N D I F F E R E N C E S , E TC .
144. S I N C E M O ST P O L I CY E VA LUAT I O N CA N N OT R E A L LY B E U N D E RTA K E N U N D E R R A N D O M I Z E D CO N T R O L T R I A L ( R C T ) TY P E CO N D I T I O N S
145. F O L K S O F T E N L E V E R AG E M E T H O D S TO T R Y TO G E T SY N T H E T I C V E R S I O N S O F R C T ’ S
146. CAU S A L I N F E R E N C E A P P R OAC H E S A R E B E ST F O R A P P R O P R I AT E P R O B L E M S / Q U E ST I O N S W H E R E I D E N T I F Y I N G / L I N K I N G CAU S E A N D E F F E C T A R E K E Y
148. O N S S R N A LO N E , T H E R E A R E T H O U S A N D S O F E M P I R I CA L L E G A L ST U D I E S TY P E PA P E R S
149. https://papers.ssrn.com/sol3/JELJOUR_Results.cfm? form_name=journalBrowse&journal_id=2123644
150. H E R E A R E J U ST A F E W E X A M P L E O F PA P E R S L E V E R AG I N G VA R I O U S E M P I R I CA L M E T H O D S
151. E VA LUAT I N G T H E I M PAC T S O F C H A N G E S I N C I V I L P L E A D I N G R U L E S
152. E X P LO R I N G T H E P E R F O R M A N C E O F B A N K R U P TCY R E F O R M F O R CO N S U M E R D E B TO R S
153. E VA LUAT I N G T H E R O L E O F E X P U N G E M E N T O N T H E O U TCO M E S O F CO N V I C T E D C R I M I N A L S
154. R E V I E W I N G W H E T H E R C H A N G E S I N PAT E N T L AW D O C T R I N E H AV E WO R K E D TO U N D E R M I N E PAT E N T T R O L L S
155. Epstein, L., & Martin, A. D. (2014). An introduction to empirical legal research. Oxford University Press. Lawless, Robert M., Jennifer K. Robbennolt, and Thomas Ulen. Empirical methods in law. New York: Aspen Publishers, 2010.
157. M O D E L I N G TY P E 4 S I M U L AT I O N B A S E D A N A LY S I S O F L E G A L R U L E S / P O L I CY M A K I N G
158. E M P I R I CA L M O D E L S / M E T H O D S A R E TY P I CA L LY U S E D TO A N A LY Z E P E R F O R M A N C E O F P O L I C I E S W H I C H A R E A L R E A DY D E P LOY E D
159. S O M E T I M E S A P O L I CY M A K E R WO U L D L I K E TO U N D E R STA N D I N A DVA N C E T H E L I K E LY I M PAC T S
160. T H E A LT E R N AT I V E TO P O ST H O C E M P I R I CA L E VA LUAT I O N I S TO CO N ST R U C T U P F R O N T G A M E T H E O R E T I C O R S I M U L AT I O N B A S E D M O D E L S
161. T H E R E A R E A VA R I E TY O F A P P R OAC H E S TO B U I L D F O R M A L M O D E L S
162. G A M E T H E O R E T I C M O D E L S AG E N T B A S E D M O D E L S SY ST E M DY N A M I C S M O D E L S
163. R E M E M B E R T H E R E I S A N U N CA N N Y VA L L E Y I N T H E O R E T I CA L M O D E L S
164. Hyper Stylized Fairly Realistic T H E U N CA N N Y VA L L E Y I N T H E O R E T I C M O D E L S Conway’s Game of Life The Sims Video Game
165. B E WA R E F O L K S C LO B B E R YO U I N T H E VA L L E Y B E CAU S E O F S O M E D E TA I L T H AT I S ‘ M I S S I N G ’ F R O M T H E M O D E L
167. H E R E A R E A F E W E X A M P L E S O F PA P E R S / P R OJ E C T S L E V E R AG I N G D I F F E R E N T M E T H O D S
168. T WO O L D E R PA P E R S W H I C H H AV E S PAW N E D M A N Y F O L LO W O N A N A LY S E S
169. T H E A RT I C L E U T I L I Z E S A N E W G A M E - T H E O R E T I C F R A M E WO R K , F O C U S I N G O N T WO C E N T R A L D I M E N S I O N S O F P O L I CY- M A K I N G I N ST R U M E N T S I N PA RT I C U L A R : T I M I N G A N D B R E A DT H .
170. T H E M O D E L U T I L I Z E S R U L E S F O R TA X PAY E R B E H AV I O R A N D A P P R E H E N S I O N O F TA X E VA D E R S I N O R D E R TO T E ST T H E E F F E C T S O F N E T WO R K TO P O LO G I E S I N T H E P R O PAG AT I O N O F E VA S I V E B E H AV I O R
171. S I M U L AT I O N O F G OV E R N A N C E A N D E N F O R C E M E N T O F F O R E ST S E X T R AC T I O N L I M I T S W I T H L E S S O N S F O R OT H E R CO M M O N P O O L R E S O U R C E G OV E R N A N C E P R O B L E M S
172. U S E S B E L I E F L E A R N I N G TO M O D E L T H E DY N A M I C S O F R AT ’ S O F F E N D E R , TA R G E T, A N D G UA R D I A N B E H AV I O R S W I T H I N A N AG E N T- B A S E D M O D E L I S T H AT T H E AG E N T S L E A R N A N D A DA P T G I V E N O B S E RVAT I O N O F OT H E R AG E N T S ’ AC T I O N S W I T H O U T K N O W L E D G E O F T H E PAYO F F S T H AT D R OV E T H E OT H E R AG E N T S ’ C H O I C E S .
175. M O D E L I N G TY P E 5 M O D E L U S E R E X P E R I E N C E W I T H A L E G A L P R O C E S S
176. L AW H A S M A N Y P R O C E S S E S A N D P R O C E D U R E S
177. I N D E E D W E T E AC H E N T I R E C L A S S E S O N L E G A L P R O C E S S E S A N D P R O C E D U R E S
178. T H E R E A R E OT H E R WAY S TO C H A R AC T E R I Z E P R O C E S S E S A N D P R O C E D U R E S
180. R E L E VA N T I N T E L L E C T UA L D I S C I P L I N E S
181. P R O C E S S E N G I N E E R I N G O P E R AT I O N S R E S E A R C H D E S I G N T H I N K I N G H U M A N CO M P U T E R I N T E R AC T I O N ( H C I )
183. T H E D E V E LO P M E N T A N D / O R D E P LOY M E N T O F S O F T WA R E
184. I T I S B A S E D U P O N M O D E L S
185. CA S E M G M T M AT T E R M G M T R E Q U I R E S A ST E P B Y ST E P U N D E R STA N D I N G O F P R O C E S S
187. I T CA N A L S O S U P P O RT T H E ‘ R E E N G I N E E R I N G ’ O F T H AT P R O C E S S
188. I T I S CA N A L S O P R OV I D E T H E F O U N DAT I O N A L DATA TO S U P P O RT OT H E R TY P E O F M O D E L I N G E F F O RT S
190. THERE ARE KNOWN METHODOLOGIES FOR MANAGING PROCESS CENTRIC WORK PROJECT MGMT PROCESS IMPROVEMENT
192. INDEED, ACROSS THE ECONOMY THERE ARE MANY EFFORTS TO CONVERT AN ARTISANAL PROCESS INTO AN INDUSTRIAL PROCESS
193. THE INDUSTRIALIZATION OF THE ARTISAN
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. WE WANT TO ENSURE THAT WE CAN MAINTAIN THE ARTISAN ELEMENTS THAT DO ADD VALUE
198. WITH RESPECT TO A GIVEN PROCESS THERE IS OFTEN A SIGNIFICANT SPREAD
199. LEAN, SIX SIGMA AND OTHER PROCESS IMPROVEMENT METHODOLOGIES
200. CAN HELP IMPROVE ALMOST EVERY SUBSECTOR IN LAW
201. CONVERT HIGH VOLATILITY PROCESS
202. CONVERT HIGH VOLATILITY PROCESS INTO A LOWER VOLATILITY PROCESS
203. WHAT YOU ARE LEFT WITH IS A VERY USEFUL ARTIFACT …
204. Responsible Role Task Description Estimated Time Billing Code Precedential Document Tool/ Technology Used Participant INDIVIDUAL PROCESS STEP
205. THE PROCESS MAP
206. IT CAN AID IN Increasing Response Times Predicting Resource Loads Coordination Across Stakeholders Increasing Margins on Work
207. I TEACH A FULL LENGTH CLASS AT ILLINOIS TECH LED BY OUR COLLEAGUES FROM THE LAW FIRM SEYFARTH SHAW
210. SO THINK OF THE PROCESS MAP AS A FIRST ORDER ESTIMATION OF YOUR ACTUAL PROCESSES
211. RICH / GRANULAR DATA CAN HELP ILLUMINATE THE ACTUAL PROCESSES PRESENT IN VARIOUS (LEGAL) ORGANIZATIONS
212. FOR EACH NODE IN A PROCESS WE WANT TO BE ABLE TO RENDER A PREDICTION ABOUT THINGS SUCH AS DURATION, COST, ETC.
213. COURTS CAN PROVIDE SCIENTIFIC SCHEDULE OF CASES, ETC.
214. EACH UNIT OF TIME LINKED + LOGGED TO A NODE ON THE PROCESS MAP
215. LEAN PROCESS MAPPING
216. IF THERE IS NOT A NODE THEN IT CAN BE ADDED AND THUS THE MAP BECOMES MORE REFLECTIVE OF REALITY
217. JUST BE CAREFUL NOT TO CREATE A #RIDICULOGRAM
218. WITH PREDICTIONS ABOUT INDIVIDUAL NODES
219. WE CAN THEN SUM TO GENERATE PREDICTIONS ABOUT THE DISTRIBUTIONAL MOMENTS OF AN OVERALL MATTER (OR PHASE) (i.e. mean, variance, skewness, kurtosis)
220. THIS MATTER SHOULD TAKE … BETWEEN 9-15 MONTHS IN 85% OF THE SIMILAR MATTERS (WHAT ABOUT THE LONG TAIL?)
221. THIS MATTER WILL COST… MOST COMMON RANGE 275K - 345K BUT THE SECOND MODE IS 555K - 625K (AND THAT SECOND MODE TYPICALLY IS REALIZED WHEN THE FOLLOWING FACTORS ARE PRESENT … )
222. SPEAKING OF #PREDICTION
224. M O D E L I N G TY P E 6 P R E D I C T I V E M O D E L I N G O F L E G A L SY ST E M S
225. H O W LO N G W I L L T H I S M AT T E R L A ST ?
226. H O W M U C H W I L L T H I S M AT T E R CO ST ?
227. W I L L W E W I N ?
228. WHAT ARE THE RIGHT RESOURCES TO USE AT THE MATTER AND TASK LEVEL ?
229. T H E R E A R E A W I D E VA R I E TY O F P R E D I C T I O N P R O B L E M S W I T H I N L AW
230. T H E R E A R E T WO M A J O R CA N D I DAT E S F O R P R O C E S S I N G P R E D I C T I O N S and / or
231. CO G N I T I V E S C I E N C E CO M P U T E R S C I E N C E
232. https://speakerdeck.com/danielkatz/the-three-forms-of-legal-prediction-experts-crowds-plus-algorithms I E X PA N D O N T H I S OV E R H E R E
234. CO M P U TAT I O N A L P R E D I C T I O N W I L L L E A D TO T WO PA RT I C U L A R FA M I L I E S O F M O D E L I N G M E T H O D S
235. P R E D I C T I O N MACHINE LEARNING NATURAL LANGUAGE PROCESSING A N D / O R =
236. T H E S E M O D E L I N G M E T H O D S A R E L E V E R AG E D I N U S E CA S E S S U C H A S T H E F O L LO W I N G
237. #Predict Substantive Case Outcomes #Predict Rogue Behavior/Compliance #Predict Contract Terms/Outcomes #Predict Case Scheduling #Predict Judge Work Allocation #Predict Relevant Legal Information #Predict Costs / Duration for Litigants
239. A N D F R O M A G LO B A L P E R S P E C T I V E
240. T H E R E H A S B E E N S I G N I F I CA N T S C I E N T I F I C A N D CO M M E R C I A L I N T E R E ST
241. I N B U I L D I N G A N D L E V E R AG I N G M O D E L S
242. #JudicialAnalytics Quantitative Legal Prediction
243. #PredictiveCoding #E-Discovery Quantitative Legal Prediction
244. General Counsels as Legal Procurement Specialists #LegalSpendAnalytics Quantitative Legal Prediction TyMetrix/ELM - Using $80 billion+ in Legal Spend Data to Help GC’s Look for Arbitrage Opportunities, Value Propositions in Hiring Law Firms
245. “Lawyers say the real value in mediation and arbitration might in the future come from large-scale data analysis of arbitrators and mediators themselves, in an effort to predict outcomes and potentially affect the course of settlements … Matthew Saunders, partner at Ashurst, notes that data analytics “could be extended to predicting which way arbitrators or a mediator might go”. #ArbitrationAnalytics
250. “…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.”
257. 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.
258. H E R E A R E A F E W E X A M P L E S I N T H E CO N T E X T O F CO U RT A D M I N I ST R AT I O N
259. https://motoraccidents.lawnet.sg/
260. https://civilresolutionbc.ca/
261. https://www.chinadaily.com.cn/a/201901/24/WS5c4959f9a3106c65c34e64ea.html The 206 System Transcribe testimony Transfer physical data and documents to electronic databases Display relevant parameters immediately, such as time, place, people, behavior and consequences Identify defective or contradicting evidence Respond to oral commands to display evidence and information on screens around the courtroom Inter-connect with judicial, procuratorial, public security authorities and courts
262. B U T T H E R E I S M U C H M O R E T H AT CA N B E D O N E …
263. A N D T H I S I S W H E R E YO U CO M E I N …
265. PA RT I I I L AW M E E T S ST E M
266. I H AV E LO N G B E L I E V E D T H AT A L AW S C H O O L A N D A T E C H N I CA L S C H O O L S H O U L D M E E T
267. LIBERAL ARTS LEGAL.EDU
268. POLYTECHNIC LEGAL.EDU LIBERAL ARTS LEGAL.EDU
269. Daniel Martin Katz, The MIT School of Law? A Perspective on Legal Education in the 21st Century, University of Illinois Law Review (2014)
270. I OUTLINE IN THIS PAPER MY VISION FOR WHAT LAW.EDU COULD BE ... (AND I AM NOT ALONE IN THIS VIEW)
271. THERE QUITE A FEW LAW SCHOOLS WITH SOME CREDIBLE VERSION OF A POLYTECHNIC OFFERING (SOME ARE MORE SERIOUS THAN OTHERS)
273. THE DEMOGRAPHIC REALITY …
274. WE ARE ABOUT TO HAVE THE LARGEST GENERATIONAL TRANSFER IN HUMAN HISTORY
275. THIS IS A MAJOR CHALLENGE TO EVERY ORGANIZATION
277. ORGANIZATIONS NEED DIFFERENT (BETTER) HUMAN CAPITAL IN ORDER TO SUPPORT ALL OF THESE TRENDS HIGHLIGHTED HEREIN
278. INCLUDING HELPING SOLVE THE COMPLEXITY CHALLENGE IN LAW
279. WE NEED MORE MULTI DISCIPLINARY INDIVIDUALS
280. WE NEED MORE MULTI DISCIPLINARY TEAMS
281. AND THIS SHOULD BE REFLECTED IN THE CONTENT OF LEGAL EDUCATION
282. T Shaped Professionals
283. via
285. I N T H I S P R E S E N TAT I O N
286. I H AV E B R I E F LY H I G H L I G H T E D AT L E A ST S I X F O R M S O F M O D E L I N G T H AT M I G H T B E L E V E R AG E D
287. TO B E T T E R U N D E R STA N D A N D H O P E F U L LY I M P R OV E T H E D E L I V E R Y O F J U ST I C E
288. I H AV E I D E N T I F I E D VA R I O U S M E T H O D S A N D I N T E L L E C T UA L F I E L D S W H O S E WO R K M I G H T A L S O B E L E V E R AG E D
289. M U C H M O R E CO U L D B E S A I D I N A LO N G E R F O R M S E S S I O N …
290. B U T I T H I N K T H I S H E L P S M A P T H E I N T E L L E C T UA L T E R R A I N ( AT L E A ST I N PA RT )
291. A N D H O P E F U L LY S P U R S A S E R I E S O F F R U I T F U L CO L L A B O R AT I O N S
292. AT T H E I N T E R S E C T I O N O F L AW + ST E M
294. T H A N K YO U I I T D E L H I F O R H O ST I N G M E TO DAY N LU D E L H I
295. T H A N K YO U DA K S H S O C I E TY F O R R E AC H I N G O U T TO I N V I T E M E F O R T H E TA L K
296. T H A N K YO U DA K S H C E N T R E O F E XC E L L E N C E AT I I T- D E L H I F O R H AV I N G M E A S A M E N TO R TO T H E C E N T E R
297. S O M E T H O U G H T S O N M O D E L I N G L E G A L SY ST E M S @computational professor daniel martin katz danielmartinkatz.com Illinois tech - chicago kent law computationallegalstudies.com https://bit.ly/3yxhY2e