Artificial Intelligence and Law

, Volume 18, Issue 4, pp 311-320

First online:

Emerging AI & Law approaches to automating analysis and retrieval of electronically stored information in discovery proceedings

  • Kevin D. AshleyAffiliated withSchool of Law, University of Pittsburgh Email author 
  • , Will BridewellAffiliated withCognitive Systems Laboratory, Center for the Study of Language and Information, Stanford University

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This article provides an overview of, and thematic justification for, the special issue of the journal of Artificial Intelligence and Law entitled “E-Discovery”. In attempting to define a characteristic “AI & Law” approach to e-discovery, and since a central theme of AI & Law involves computationally modeling legal knowledge, reasoning and decision making, we focus on the theme of representing and reasoning with litigators’ theories or hypotheses about document relevance through a variety of techniques including machine learning. We also identify two emerging techniques for enabling users’ document queries to better express the theories of relevance and connect them to documents: social network analysis and a hypothesis ontology.


E-discovery Litigators’ relevance hypotheses User modeling Machine learning Social networks Legal ontologies