Uploaded byDaniel Katz
Technology, Data and Computation Session @ The World Bank - Law, Justice, and Development Week
This document discusses the application of computational techniques to law, including predictive modeling, network analysis, and natural language processing. It describes how experts, crowds, and algorithms can be combined for legal prediction tasks. Specific tools are highlighted, such as the A2J Author platform for simplifying legal forms and the visualization of Supreme Court citation networks. Broader topics covered include the potential for blockchain to reduce transaction friction and the movement toward more data-driven and ensemble-based approaches in law.
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Similar to Technology, Data and Computation Session @ The World Bank - Law, Justice, and Development Week
Technology, Data and Computation Session @ The World Bank - Law, Justice, and Development Week
- 1. Technology, Data andComputation 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
- 3. application of tools/ideasfrom computer science and/or computational science would be potentially fruitful in the law
- 4. So We StartedThis... March 17, 2009
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- 8. is not justabout machines
- 9. humans are engaging incomputation
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- 11. three ways todo computation …
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- 14. three ways todo computation … experts, crowds, algorithms
- 15. the world ismoving ….
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- 21. data driven AIrules based AI Competing Orientations in Artificial Intelligence
- 22. data driven AIrules based AI Competing Orientations in Artificial Intelligence + Law
- 24. expert systems Computational Law Data DrivenRules Based prediction models and methods network analytic methods natural language processing self executing law visual law computable codes
- 26. How Ideas inComputational Law is helping support new legal infrastructures
- 27. lex mercatoria (merchantlaw) “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.
- 28. existing legal orderdid not work for merchants for medieval commerce required
- 29. merchant law offered auseful innovation in support of (long distance)commerce
- 30. there is amodern version of lex mercatoria
- 31. online lex mercatoria(merchant law)
- 32. online commerce requires lowfriction method for resolving disputes secure payment
- 33. online commerce requires lowfriction method for resolving disputes secure payment
- 37. How Ideas inComputational Law are helping reduce complexity through user interface (as well as rules and data)
- 39. I would liketo 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
- 40. IIT Chicago-Kent Collegeof Law has significant work in furtherance of access to justice https://www.kentlaw.iit.edu/institutes-centers/center-for-access-to-justice-and-technology
- 41. used by avariety of legal aid organizations both in U.S. and abroad … https://www.kentlaw.iit.edu/institutes-centers/center-for-access-to-justice-and-technology
- 42. you can thinkabout 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
- 44. What is A2JAuthor? An online tool from Chicago-Kent & CALI to build graphical interfaces for low-income, self-represented individuals.
- 45. A2J Author GathersData Authoring tool in the Cloud End User A2J Guided Interview
- 46. “Learn More” bubbles, definition pop-ups, audio, graphic and video capabilities. A2J Author “just in time” Learning
- 47. Connects to NationalServer - LawHelpInteractive.org
- 48. Completed Documents Deliveredto Local Computer
- 49. Uses for A2JAuthor Document Assembly Online Intake Benefits EligibilityScreen &Calculators E-FilingTriage Stand-Alone Info Guides
- 50.
- 51. A2J Author 5.0- Cloudapp & Mobile viewer!
- 52. Goal for Version6.0 of A2J Author we want to reinvent delivery of legal services using mobile
- 54. How Ideas inComputational Law are helping reduce complexity using visualization
- 55. 3D HDVisualization ofSupreme Court Citation Network Campaign Contributions and Legislative Ecosystems The United States Code American Federal Judiciary
- 56. © daniel martinkatz michael j bommarito
- 60. Wearable LawEmbedded Law Internetof Legal Things
- 61. Longer Term Ideas WearableLawEmbedded Law
- 62.
- 64. How Ideas inComputational Law are helping support lower friction / higher trust transactions
- 65. we are startinga decade(s) long process of overhauling the global financial infrastructure (also the trust architecture)
- 66. it is amassive friction reduction exercise
- 74. EXECUTIVE SUMMARY but blockchainis important bitcoin is probably not that important
- 76. How Ideas inComputational Law are helping litigants predict legal outcomes
- 77. 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
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- 81. 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 19731983 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
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- 84. question is howto assemble such streams for particular problems
- 85. law is afield dominated by individual human experts
- 86. in most fields- significant quality improvements have been made by moving from experts to ensembles
- 87. in part computationallaw is about helping build those ensembles
- 88. using experts, crowds,algorithms
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- 90. Implications for theRule of Law
- 91. Variations from thePredictable Anomaly Detection Flag of Potential Corruption, etc.
- 93. expert systems Computational Law Data DrivenRules Based prediction models and methods network analytic methods natural language processing self executing law visual law computable codes
- 95.
- 96. we would welcomeyour submissions
- 97. we would welcomeyour submissions
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- 105. Daniel Martin Katz @computational computationallegalstudies.com lexpredict.com danielmartinkatz.com illinois tech - chicago kent college of law@