What is Computational Legal Studies? Presentation @ University of Houston - Workshop on Law & Computation

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What is Computational Legal Studies? Presentation @ University of Houston - Workshop on Law & Computation

  1. 1. What is Computational Legal Studies? Professor Daniel Martin Katz Illinois Tech - Chicago Kent College of Law @computationaldanielmartinkatz.com computationallegalstudies.com
  2. 2. What is Computational Legal Studies?
  3. 3. What is Computational Legal Studies?
  4. 4. Computational Legal Studies is
  5. 5. Sociophysics
  6. 6. Natural Language Processing
  7. 7. Machine Learning
  8. 8. Network Science
  9. 9. Statistical Methods
  10. 10. Out of Equilibrium Models
  11. 11. Non Linearity
  12. 12. Scaling
  13. 13. Diffusion
  14. 14. Social Epidemiology
  15. 15. Information Theory
  16. 16. New Kind of Science
  17. 17. Computational Game Theory
  18. 18. Web Scrapping
  19. 19. Information Visualization
  20. 20. What is Computational Legal Studies?
  21. 21. Computational Legal Studies Offers
  22. 22. A Set of Tools
  23. 23. that allow us to perhaps better understand
  24. 24. ‘Law’ in a modern society
  25. 25. Taxonomy of Approaches
  26. 26. Data Analysis Formal Models Computational Legal Studies
  27. 27. Data Analysis Formal Models Computational Legal Studies
  28. 28. Data Analysis
  29. 29. This is the Era of “Big Data” Decreasing Data Storage Costs Increasing Computing Power Fundamentally Altering the Scope of Scientific Inquiry
  30. 30. Highlighting the Data Deluge 2008 2009 2010
  31. 31. The Case for a Computational Approach Legal Systems Output large amounts of Information Need Methods that Scale to the Size and Scope of this Body of Information
  32. 32. Data Analysis statistical models and methods network analytic methods text as data other related approaches
  33. 33. What is Computational Legal Studies?
  34. 34. Computational Legal Studies is
  35. 35. quantitative legal prediction
  36. 36. do i have a case?
  37. 37. how do lawyers generate this assessment?
  38. 38. can it be automated?
  39. 39. Mental Models vs Aggregated Data
  40. 40. Weather Prediction
  41. 41. Tide Prediction
  42. 42. vs.
  43. 43. lots of factors matter
  44. 44. Inputs / Data Quality
  45. 45. Time Scales Matter
  46. 46. inherent system variability matters
  47. 47. ‘complexity’ matters
  48. 48. Some Potential Inputs
  49. 49. what is the relevant information contained therein?
  50. 50. text, citations, votes, etc.
  51. 51. other metadata
  52. 52. what form might the outputs take?
  53. 53. standard client memo + statistical portrait of 10,000 ‘similar’ cases
  54. 54. the caveat
  55. 55. your mileage may vary
  56. 56. but a statistical portrait
  57. 57. would be useful
  58. 58. to gut check a mental model
  59. 59. other big implications ...
  60. 60. the market for legal services
  61. 61. the market for legal education
  62. 62. ‘thinking like a lawyer’?
  63. 63. in the age of big data ...
  64. 64. What is Computational Legal Studies? Data Analysis Formal Models
  65. 65. Formal Models
  66. 66. Formal Models computational game theory network models Agent Based Modeling
  67. 67. Why Generate Formal Models?
  68. 68. Formal Models v. Data
  69. 69. The Evaluation of Counterfactuals
  70. 70. The Evaluation of Alternative ‘States of the world’
  71. 71. Cannot not be Exclusively Data Driven
  72. 72. A Few Examples ...
  73. 73. Theoretical Models and Computational Simulations schelling’s segregation model Axelrod’s Evolution of Cooperation model
  74. 74. An Entire Course on Computational Formal Models 18 Classes and more than 1000 slides! ICPSR Summer Methods Program
  75. 75. computational game theory network models Agent Based Modeling What is Computational Legal Studies? Data Analysis Formal Models statistical models and methods network analytic methods text as data
  76. 76. and more ...
  77. 77. Now Some Selected Applications
  78. 78. Project #1: United States Code
  79. 79. The United States Code
  80. 80. Compiled Version of Federal Statutory Law Drawn from the Statutes at Large Does not Include Admin Regulations The United States Code
  81. 81. These are the 50 titles in the Code
  82. 82. A Perspective on the Scope of Law in a Modern Society How Large is the United States Code? How Complex is the United States Code? How has its Scope Changed Over Time? Are Changes in Code Coupled with Changes in the Scope of the Administrative State?
  83. 83. How Large is the United States Code?
  84. 84. How Large is the United States Code?
  85. 85. How Large is the United States Code?
  86. 86. How Large is the United States Code?
  87. 87. ~Title 29 - Labor How Large is the United States Code?
  88. 88. This is the United States Code
  89. 89. Computational Approach to Measurement of Complexity Measure that Representation in a Manner that is Qualitatively Justified Provide a Mathematical Representation of the Object
  90. 90. The US Code as a Mathematical Object Hierarchical Structure Title 26 Subtitle A Chapter 1 Subchapter F Part I Section 501 Subsection (c) Paragraph (3) http://arxiv.org/abs/1003.4146
  91. 91. Citation Network Example: Tax Evasion Title 26 - Tax Cites Title 18 - Crimes & Criminal Procedure The US Code as a Mathematical Object http://computationallegalstudies.com
  92. 92. Linguistic Content United States Code Features 24 Million Words The US Code as a Mathematical Object
  93. 93. Published in Physica A (October 2010) The US Code as a Mathematical Object
  94. 94. How Complex is U.S. Code? Ongoing Project -- Daniel Katz & Michael Bommarito “Measuring the Complexity of the United States Code”
  95. 95. The Complexity of Knowledge Acquisition 3 Factors Influence Complexity of Executing a KA Protocol Structure Language Dependence
  96. 96. Project #2: Network Analysis of the Federal Judiciary
  97. 97. the Federal Judicial Heirarchy United States Supreme Court Federal Court of Appeals Federal District Court
  98. 98. What is the Social Topology of the American Federal Judiciary?
  99. 99. ... And How Can We Measure it?
  100. 100. Collected Nearly 19,000 Law Clerk ‘Events’ 1995 - 2005 For All Article III Judges Relying Upon Data From Staff Directories Network Analysis of the Federal Judiciary
  101. 101. The Core Claim In the Aggregate ... Law Clerk Movements Reveal Between Judicial Actors Social or Professional Relationships
  102. 102. Network Analysis of the Federal Judiciary Judge E Justice ZJustice Y Judge C Judge D Judge B Judge A
  103. 103. Network Analysis of the Federal Judiciary
  104. 104. Network Analysis of the Federal Judiciary Daniel Katz & Derek Stafford (2010)
  105. 105. Project #3: Exploring the Path of Precedent? The Legal Genome Project and the analysis of Judicial Citations
  106. 106. The United States Reports
  107. 107. Nodes = Cases Decided by the Supreme Court Directed Edges = Citations between Cases United States Supreme Court Case to Case Citation Network
  108. 108. Case to Case Citation Network of the United States Supreme Court Dickerson v. U.S. 530 U.S. 428 (2000) Miranda v. Arizona 384 U.S. 436 (1966) Oregon v. Elstad 530 U.S. 428 (2000)
  109. 109. Exploring the Path of Precedent? Dynamic Visualization of the Early Supreme Court Citation Network
  110. 110. Cases Decided by the Supreme Court Citations in the Current Year Citations from prior years http://computationallegalstudies.com/ 2010/02/11/the-development-of-structure-in- the-citation-network-of-the-united-states- supreme-court-now-in-hd/ PLAY MOVIE! Beijing
  111. 111. Distance Measures for Dynamic Citation Networks
  112. 112. Growth Rules For Citation Networks
  113. 113. Dynamic Directed Acyclic Graphs
  114. 114. Dynamic Directed Acyclic Graphs Examples: Academic Articles
  115. 115. Dynamic Directed Acyclic Graphs Examples: Academic Articles Judicial Citations
  116. 116. Dynamic Directed Acyclic Graphs Examples: Academic Articles Judicial Citations Patent Citations
  117. 117. Network Dynamics: The Early Jurisprudence of the United States Supreme Court
  118. 118. Cases Decided by the Supreme Court Citations in the Current Year Citations from prior years
  119. 119. A Formalization of D-DAG’s
  120. 120. Six Degrees of Marbury v. Madison
  121. 121. A Formalization of D-DAG’s
  122. 122. Basic Idea of Sink Based Distance Measure
  123. 123. The Simplest Non-Trivial Distance Measure
  124. 124. Flexible Framework For More Detailed Specifications
  125. 125. Distance Measure <- -> Dendrogram
  126. 126. Potential Application to Patent Citations?
  127. 127. Sternitzke, Bartkowski & Schramm (2008) Potential Application to Patent Citations?
  128. 128. http://www.eecs.umich.edu/cse/dm_11_video/erdi.mp4 http://people.kzoo.edu/~perdi/Talk By Péter Érdi Network Analysis of Patent Citations
  129. 129. http://ssrn.com/author=627779 http://arxiv.org/abs/0909.1819available at:
  130. 130. Additional Materials Available Online!
  131. 131. @computational Thank You For Your Attention!
  132. 132. Professor Daniel Martin Katz Illinois Tech - Chicago Kent College of Law @computationaldanielmartinkatz.com computationallegalstudies.com

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