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Open Legal Data
Workshop
Stanford University CodeX Center
Harry Surden
Professor of Law, University of Colorado
Affiliated...
Overview
• Computation has Revolutionized Many Fields
• Law is not one of them
• Data is required for Computational Analys...
Computational Legal Analysis
• Computational Law (Rules-based, deductive)
– Rules-based systems computing legal outcomes
–...
Problem
• Computation has revolutionized:
– Finance, medicine, engineering, science, etc.
– Machine learning and computati...
To do computation
We need data to analyze
• Think of Law as data to be analyzed
– Federal statutes and administrative rule...
The Legal Data Bottleneck
• Legal data exists, but it is not
– Openly accessible (behind pay-walls)
– Structured in a way ...
For really interesting
computational work in law we need
• High-quality legal data that is
– Open and Accessible (little o...
Possibilities
harrysurden.com
Possibilities
lexpredict.com
Possibilities
• With high quality, structured legal data:
– Predictions of federal, state court decision
– Finding pattern...
Open Legal Data
• Legal data for computation that is:
– Open and Accessible (little or no cost)
– Structured (machine read...
Upcoming info
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Open Legal Data Workshop at Stanford

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On May 19, 2016 I hosted a workshop at Stanford's Codex Center about ways to make legal data more open and accessible for computation. These are the slides from my presentation framing the issue.

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Open Legal Data Workshop at Stanford

  1. 1. Open Legal Data Workshop Stanford University CodeX Center Harry Surden Professor of Law, University of Colorado Affiliated Faculty: Stanford CodeX Center
  2. Overview • Computation has Revolutionized Many Fields • Law is not one of them • Data is required for Computational Analysis • Legal data: neither accessible nor high-quality
  3. Computational Legal Analysis • Computational Law (Rules-based, deductive) – Rules-based systems computing legal outcomes – Represent laws in computer-understandable form – Example: Turbotax; Computable contracts • Machine Learning & Law (often Statistical) – Algorithms that learn patterns from data – Widely Used: self-driving cars, translation, etc – Example: Supreme Court prediction project
  4. Problem • Computation has revolutionized: – Finance, medicine, engineering, science, etc. – Machine learning and computation used for • Prediction, automation, outlier detection, analysis, • New drug discovery, etc • But computation has barely touched law – Why?
  5. To do computation We need data to analyze • Think of Law as data to be analyzed – Federal statutes and administrative rules – State and local laws and codes – Judicial orders and opinions – Lawsuit motions and evidence, etc. Quality legal data not widely available for analysis
  6. The Legal Data Bottleneck • Legal data exists, but it is not – Openly accessible (behind pay-walls) – Structured in a way that makes analysis feasible • Lack of widely accessible legal data – Bottleneck to really interesting work in • Machine learning and Law • Computational law
  7. For really interesting computational work in law we need • High-quality legal data that is – Open and Accessible (little or no cost) – Structured (machine readable) – Standardized (common encoding formats) – Coded (human-tagged and organized) – Semantic (embedded with meaning)
  8. Possibilities harrysurden.com
  9. Possibilities lexpredict.com
  10. Possibilities • With high quality, structured legal data: – Predictions of federal, state court decision – Finding patterns or biases in legal data – More computational law systems – Advanced legal data visualizations – Discovery of unknown connections or structures – Outlier detection – ….many more
  11. Open Legal Data • Legal data for computation that is: – Open and Accessible (little or no cost) – Structured (machine readable) – Standardized (common encoding formats) – Coded (human-tagged and organized) – Semantic (embedded with meaning)
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