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Modelling competing legal arguments using Bayesian model comparison and averaging

Neil, M; Fenton, N; Lagnado, D; Gill, RD; (2019) Modelling competing legal arguments using Bayesian model comparison and averaging. Artificial Intelligence and Law 10.1007/s10506-019-09250-3. Green open access

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Abstract

Bayesian models of legal arguments generally aim to produce a single integrated model, combining each of the legal arguments under consideration. This combined approach implicitly assumes that variables and their relationships can be represented without any contradiction or misalignment, and in a way that makes sense with respect to the competing argument narratives. This paper describes a novel approach to compare and ‘average’ Bayesian models of legal arguments that have been built independently and with no attempt to make them consistent in terms of variables, causal assumptions or parameterization. The approach involves assessing whether competing models of legal arguments are explained or predict facts uncovered before or during the trial process. Those models that are more heavily disconfirmed by the facts are given lower weight, as model plausibility measures, in the Bayesian model comparison and averaging framework adopted. In this way a plurality of arguments is allowed yet a single judgement based on all arguments is possible and rational.

Type: Article
Title: Modelling competing legal arguments using Bayesian model comparison and averaging
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s10506-019-09250-3
Publisher version: http://doi.org/10.1007/s10506-019-09250-3
Language: English
Additional information: Copyright © The Author(s) 2019. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords: Bayesian model comparison and averaging · Bayesian networks · Legal argumentation
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: http://discovery.ucl.ac.uk/id/eprint/10072884
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