A model of jury decisions where all jurors have the same evidence

Synthese 142 (2):175 - 202 (2004)
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Under the independence and competence assumptions of Condorcet’s classical jury model, the probability of a correct majority decision converges to certainty as the jury size increases, a seemingly unrealistic result. Using Bayesian networks, we argue that the model’s independence assumption requires that the state of the world (guilty or not guilty) is the latest common cause of all jurors’ votes. But often – arguably in all courtroom cases and in many expert panels – the latest such common cause is a shared ‘body of evidence’ observed by the jurors. In the corresponding Bayesian network, the votes are direct descendants not of the state of the world, but of the body of evidence, which in turn is a direct descendant of the state of the world. We develop a model of jury decisions based on this Bayesian network. Our model permits the possibility of misleading evidence, even for a maximally competent observer, which cannot easily be accommodated in the classical model. We prove that (i) the probability of a correct majority verdict converges to the probability that the body of evidence is not misleading, a value typically below 1; (ii) depending on the required threshold of ‘no reasonable doubt’, it may be impossible, even in an arbitrarily large jury, to establish guilt of a defendant ‘beyond any reasonable doubt’.


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Author Profiles

Franz Dietrich
Centre National de la Recherche Scientifique
Christian List
Ludwig Maximilians Universität, München

References found in this work

Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Cambridge University Press.
Causality.Judea Pearl - 2000 - Cambridge University Press.
Epistemic democracy: Generalizing the Condorcet jury theorem.Christian List & Robert E. Goodin - 2001 - Journal of Political Philosophy 9 (3):277–306.

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