On balance

Authors:
Marc Lauritsen
Affiliations:
Capstone Practice Systems, Harvard, Massachusetts
Venue:
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Law
Year:
2013

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Abstract

In the course of legal reasoning -- whether for purposes of deciding an issue, justifying a decision, predicting how an issue will be decided, or arguing for how it should be decided -- one often is required to reach (and assert) conclusions based on a balance of reasons that is not straightforwardly reducible to the application of rules. Recent AI & Law work has modeled reason-balancing, both within and across cases, with set-theoretic and rule- or value-ordering approaches. This article explores how modeling it in 'choiceboxing' terms may yield new questions, insights, and tools.