From data to information: Automating data science to explore the U.S. court system

Andrew Paley, Andong L.Li Zhao, Harper Pack, Sergio Servantez, Rachel F. Adler, Marko Sterbentz, Adam Pah, David Schwartz, Cameron Barrie, Alexander Einarsson, Kristian Hammond

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The U.S. court system is the nation's arbiter of justice, tasked with the responsibility of ensuring equal protection under the law. But hurdles to information access obscure the inner workings of the system, preventing stakeholders - from legal scholars to journalists and members of the public - from understanding the state of justice in America at scale. There is an ongoing data access argument here: U.S. court records are public data and should be freely available. But open data arguments represent a half-measure; what we really need is open information. This distinction marks the difference between downloading a zip file containing a quarter-million case dockets and getting the real-time answer to a question like "Are pro se parties more or less likely to receive fee waivers?"To help bridge that gap, we introduce a novel platform and user experience that provides users with the tools necessary to explore data and drive analysis via natural language statements. Our approach leverages an ontology configuration that adds domain-relevant data semantics to database schemas to provide support for user guidance and for search and analysis without user-entered code or SQL. The system is embodied in a "natural-language notebook"user experience, and we apply this approach to the space of case docket data from the U.S. federal court system. Additionally, we provide detail on the collection, ingestion and processing of the dockets themselves, including early experiments in the use of language modeling for docket entry classification with an initial focus on motions.

Original languageEnglish (US)
Title of host publicationProceedings of the 18th International Conference on Artificial Intelligence and Law, ICAIL 2021
PublisherAssociation for Computing Machinery, Inc
Pages119-128
Number of pages10
ISBN (Electronic)9781450385268
DOIs
StatePublished - Jun 21 2021
Event18th International Conference on Artificial Intelligence and Law, ICAIL 2021 - Virtual, Online, Brazil
Duration: Jun 21 2021Jun 25 2021

Publication series

NameProceedings of the 18th International Conference on Artificial Intelligence and Law, ICAIL 2021

Conference

Conference18th International Conference on Artificial Intelligence and Law, ICAIL 2021
Country/TerritoryBrazil
CityVirtual, Online
Period6/21/216/25/21

Keywords

  • data analytics
  • information extraction
  • natural language processing
  • notebook interface
  • visualization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Law

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