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Modeling the Evolution of Legal Discretion: An Artificial Intelligence Approach

Kannai, Ruthi, Schild, Uri J and Zeleznikow, John (2007) Modeling the Evolution of Legal Discretion: An Artificial Intelligence Approach. Ratio Juris, 20 (4). pp. 530-558. ISSN 0952-1917

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Much legal research focuses on understanding how judicial decisionmakers exercise their discretion. In this paper we examine the notion of legal or judicial discretion, and weaker and stronger forms of discretion. At all times our goal is to build cognitive models of the exercise of discretion, with a view to building computer software to model and primarily support decision-making. We observe that discretionary decision-making can best be modeled using three independent axes: bounded and unbounded, defined and undefined, and binary and continuous. Examples of legal tasks are given from each of the eight ensuing octants and we conclude by saying what this model shows about current legal trends. We should stress that our taxonomy has been based on our observations of how discretionary legal decisions are made. No claim is made that our model is either complete (providing advice in every domain) or exact, but it does help knowledge engineers construct legal decision support systems in discretionary domains.

Item Type: Article
Uncontrolled Keywords: ResPubID13933, information technology, legal decision making, artificial intelligence, AI
Subjects: FOR Classification > 0806 Information Systems
Faculty/School/Research Centre/Department > School of Management and Information Systems
SEO Classification > 8999 Other Information and Communication Services
Depositing User: VUIR
Date Deposited: 01 Dec 2010 03:12
Last Modified: 25 Sep 2018 05:09
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