Technology, Data and Computation Session @ The World Bank - Law, Justice, and Development Week

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Technology, Data and Computation Session @ The World Bank - Law, Justice, and Development Week

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Technology, Data and Computation Session @ The World Bank - Law, Justice, and Development Week

  1. 1. Technology, Data and Computation daniel martin katz blog | ComputationalLegalStudies.com corp | LexPredict.com page | DanielMartinKatz.com edu | illinois tech - chicago kent college of law Law, Justice, and Development Week 2015
  2. 2. application of tools/ideas from computer science and/or computational science would be potentially fruitful in the law
  3. 3. So We StartedThis ... March 17, 2009
  4. 4. ComputationalLegalStudies.com
  5. 5. computation
  6. 6. is not just about machines
  7. 7. humans are engaging in computation
  8. 8. thus there are …
  9. 9. three ways to do computation …
  10. 10. http://computationallegalstudies.com/2015/09/the-three-forms-of-legal-prediction- experts-crowds-and-algorithms-professors-daniel-martin-katz-michael-j-bommarito/ i expand on this idea here
  11. 11. three ways to do computation … experts, crowds, algorithms
  12. 12. the world is moving ….
  13. 13. from experts alone
  14. 14. from experts alone
  15. 15. (ensembles thereof) from experts alone experts, crowds, algorithms
  16. 16. Computational Law
  17. 17. data driven AI rules based AI Competing Orientations in Artificial Intelligence
  18. 18. data driven AI rules based AI Competing Orientations in Artificial Intelligence + Law
  19. 19. 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
  20. 20. How Ideas in Computational Law is helping support new legal infrastructures
  21. 21. lex mercatoria (merchant law) “The medieval lex mercatoria was the product of customs and practices among traders, and could be enforced through the local courts. However, the merchants needed to solve their disputes rapidly, sometimes on the hour, with the least costs and by the most efficient means. Public courts did not provide this. A trial before the courts would delay their business, and that meant losing money. The lex mercatoria provided quick and effective justice.
  22. 22. existing legal order did not work for merchants for medieval commerce required
  23. 23. merchant law offered a useful innovation in support of (long distance)commerce
  24. 24. there is a modern version of lex mercatoria
  25. 25. online lex mercatoria (merchant law)
  26. 26. online commerce requires low friction method for resolving disputes secure payment
  27. 27. online commerce requires low friction method for resolving disputes secure payment
  28. 28. How Ideas in Computational Law are helping reduce complexity through user interface (as well as rules and data)
  29. 29. I would like to share one tool developed at IIT Chicago-Kent College of Law https://www.kentlaw.iit.edu/institutes-centers/center-for-access-to-justice-and-technology
  30. 30. IIT Chicago-Kent College of Law has significant work in furtherance of access to justice https://www.kentlaw.iit.edu/institutes-centers/center-for-access-to-justice-and-technology
  31. 31. used by a variety of legal aid organizations both in U.S. and abroad … https://www.kentlaw.iit.edu/institutes-centers/center-for-access-to-justice-and-technology
  32. 32. you can think about this as a sort of ‘turbotax-ifcation’ of legal rules/forms/processes https://www.kentlaw.iit.edu/institutes-centers/center-for-access-to-justice-and-technology
  33. 33. What is A2J Author? An online tool from Chicago-Kent & CALI to build graphical interfaces for low-income, self-represented individuals.
  34. 34. A2J Author Gathers Data Authoring tool in the Cloud End User A2J Guided Interview
  35. 35. “Learn  More”  bubbles,  definition  pop-ups, audio, graphic and video capabilities. A2J Author “just  in  time”  Learning
  36. 36. Connects to National Server - LawHelpInteractive.org
  37. 37. Completed Documents Delivered to Local Computer
  38. 38. Uses for A2J Author Document Assembly Online Intake Benefits EligibilityScreen &Calculators E-FilingTriage Stand-Alone Info Guides
  39. 39. 2,524,639 1,529,205 A2J Guided Interviews
  40. 40. A2J Author 5.0- Cloud app & Mobile viewer!
  41. 41. Goal for Version 6.0 of A2J Author we want to reinvent delivery of legal services using mobile
  42. 42. How Ideas in Computational Law are helping reduce complexity using visualization
  43. 43. 3D HDVisualization of Supreme Court Citation Network Campaign Contributions and Legislative Ecosystems The United States Code American Federal Judiciary
  44. 44. © daniel martin katz michael j bommarito
  45. 45. Wearable LawEmbedded Law Internet of Legal Things
  46. 46. Longer Term Ideas Wearable LawEmbedded Law
  47. 47. http://www.openlawlab.com/2013/05/14/legal-jacket-concept/ Longer Term Ideas Wearable LawEmbedded Law
  48. 48. How Ideas in Computational Law are helping support lower friction / higher trust transactions
  49. 49. we are starting a decade(s) long process of overhauling the global financial infrastructure (also the trust architecture)
  50. 50. it is a massive friction reduction exercise
  51. 51. EXECUTIVE SUMMARY but blockchain is important bitcoin is probably not that important
  52. 52. How Ideas in Computational Law are helping litigants predict legal outcomes
  53. 53. Quantitative Legal Prediction - or - How I Learned to Stop Worrying and Start Preparing for the Data Driven Future of the Legal Services Industry 62 Emory L. J. 909 (2013) available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2187752
  54. 54. Predicting Judicial Decision Making
  55. 55. experts
  56. 56. crowds
  57. 57. Black Reed Frankfurter Douglas Jackson Burton Clark Minton Warren Harlan Brennan Whittaker Stewart White Goldberg Fortas Marshall Burger Blackmun Powell Rehnquist Stevens OConnor Scalia Kennedy Souter Thomas Ginsburg Breyer Roberts Alito Sotomayor Kagan 1953 1963 1973 1983 1993 2003 2013 9-0 Reverse 8-1, 7-2, 6-3 19 19 19 19 19 20 20 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 - Reverse 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 0.00 0.25 0.50 0.75 1.00 - 8-1, 7-2, 6-3 9-0 19 19 19 19 19 20 20 algorithms
  58. 58. humans + machines humans or machines >
  59. 59. question is how to assemble such streams for particular problems
  60. 60. law is a field dominated by individual human experts
  61. 61. in most fields - significant quality improvements have been made by moving from experts to ensembles
  62. 62. in part computational law is about helping build those ensembles
  63. 63. using experts, crowds, algorithms
  64. 64. Implications for Predicting Judicial Behavior
  65. 65. Implications for the Rule of Law
  66. 66. Variations from the Predictable Anomaly Detection Flag of Potential Corruption, etc.
  67. 67. 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
  68. 68. A Few Plugs:
  69. 69. we would welcome your submissions
  70. 70. we would welcome your submissions
  71. 71. thelawlab.com
  72. 72. LexPredict.com
  73. 73. ComputationalLegalStudies.com BLOG
  74. 74. @ computational
  75. 75. Daniel Martin Katz @ computational computationallegalstudies.com lexpredict.com danielmartinkatz.com illinois tech - chicago kent college of law@

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