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

Authors:
Kevin D. Ashley;Will Bridewell
Affiliations:
School of Law, University of Pittsburgh, Pittsburgh, PA;Cognitive Systems Laboratory, Center for the Study of Language and Information, Stanford University, Stanford, CA
Venue:
Artificial Intelligence and Law
Year:
2010

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Abstract

This article provides an overview of, and the matic 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.