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Can temporal representation and reasoning make a difference in automated legal reasoning? Lessons from an AI-based ethical reasoner

Bruce McLaren; Kevin D. Ashley
In: Kevin Ashley; Tom van Engers (Hrsg.). Proceedings of the Thirteenth International Conference on Artificial Intelligence and Law. International Conference on Artificial Intelligence and Law (ICAIL), June 6-10, Pittsburgh, Pennsylvania, USA, Pages 229-238, ISBN 978-1-4503-0755-0, ACM Press, New York, NY, USA, 2011.


Given a renewed interest in the field of AI and Law in more complex factual representations of legal cases in terms of narratives, techniques for representing and reasoning about temporal orderings of facts will become increasingly important. The SIROCCO (System for Intelligent Retrieval of Operationalized Cases and COdes) program employed a representation for the temporal ordering of events in ethics cases in a way that informed determinations of whether and how ethical norms were violated and if the problem and other cases were normatively analogous at a deeper level. At the same time, the program supported ordinary case enterers in translating the facts of textually described cases into a machine-processable representation. This paper presents these previously unpublished aspects of the work including a report of an empirical evaluation of the contribution of the temporal representation to the program's success in retrieving relevant norms and cases. Although the results were negative, a consideration of the reasons why is illuminating. While SIROCCO dealt with engineering ethics cases, it is clear that similar temporal considerations apply in legal cases and that the approach is likely to be useful in legal narrative representations.