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Legal Evidence and Proof: Statistics, Stories, Logic

Ashgate. Edited by Henry Prakken & Bart Verheij (2008)

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  1. Evidential Reasoning.Marcello Di Bello & Bart Verheij - 2011 - In G. Bongiovanni, Don Postema, A. Rotolo, G. Sartor, C. Valentini & D. Walton (eds.), Handbook in Legal Reasoning and Argumentation. Dordrecht, Netherland: Springer. pp. 447-493.
    The primary aim of this chapter is to explain the nature of evidential reasoning, the characteristic difficulties encountered, and the tools to address these difficulties. Our focus is on evidential reasoning in criminal cases. There is an extensive scholarly literature on these topics, and it is a secondary aim of the chapter to provide readers the means to find their way in historical and ongoing debates.
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  • Building Bayesian networks for legal evidence with narratives: a case study evaluation.Charlotte S. Vlek, Henry Prakken, Silja Renooij & Bart Verheij - 2014 - Artificial Intelligence and Law 22 (4):375-421.
    In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrative and probabilistic approaches. Integrating these three approaches could arguably enhance the communication between an expert and a judge or jury. In previous work, techniques were proposed to represent narratives in a Bayesian network and to use narratives as a basis for systematizing the construction of a Bayesian network for a legal (...)
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  • Proof with and without probabilities: Correct evidential reasoning with presumptive arguments, coherent hypotheses and degrees of uncertainty.Bart Verheij - 2017 - Artificial Intelligence and Law 25 (1):127-154.
    Evidential reasoning is hard, and errors can lead to miscarriages of justice with serious consequences. Analytic methods for the correct handling of evidence come in different styles, typically focusing on one of three tools: arguments, scenarios or probabilities. Recent research used Bayesian networks for connecting arguments, scenarios, and probabilities. Well-known issues with Bayesian networks were encountered: More numbers are needed than are available, and there is a risk of misinterpretation of the graph underlying the Bayesian network, for instance as a (...)
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  • A new use case for argumentation support tools: supporting discussions of Bayesian analyses of complex criminal cases.Henry Prakken - 2020 - Artificial Intelligence and Law 28 (1):27-49.
    In this paper a new use case for legal argumentation support tools is considered: supporting discussions about analyses of complex criminal cases with the help of Bayesian probability theory. By way of a case study, two actual discussions between experts in court cases are analysed on their argumentation structure. In this study the usefulness of several recognised argument schemes is confirmed, a new argument scheme for arguments from statistics are proposed, and an analysis is given of debates between experts about (...)
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  • Evidence & decision making in the law: theoretical, computational and empirical approaches.Marcello Di Bello & Bart Verheij - 2020 - Artificial Intelligence and Law 28 (1):1-5.
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