A Model of Jury Decisions where all Jurors have the same Evidence
A Model of Jury Decisions where all Jurors have the same Evidence
复制标题
所有陪审员拥有相同证据的陪审团决策模型
DOI：
10.1007/s11229-004-1276-z
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发表时间：
2004
期刊：
影响因子：
1.5
通讯作者：
C. List
中科院分区：
文献类型：
--
作者：
F. Dietrich;C. List
在孔多塞经典陪审团模型的独立性和能力假设下，随着陪审团规模的增加，多数人做出正确决定的概率趋近于确定性，这是一个看似不现实的结果。使用贝叶斯网络，我们认为该模型的独立性假设要求世界的状态（有罪或无罪）是所有陪审员投票的最新共同原因。但通常——可以说在所有法庭案件和许多专家小组中——最新的这种共同原因是陪审员观察到的共同“证据体”。在相应的贝叶斯网络中，选票不是世界状态的直接后代，而是证据体的直接后代，而证据体又是世界状态的直接后代。我们建立了一个基于贝叶斯网络的陪审团决策模型。我们的模型允许误导性证据的可能性，即使是对于一个最有能力的观察者，这在经典模型中是不容易容纳的。我们证明(i)正确多数判决的概率收敛于证据体不具有误导性的概率，其值通常低于1；（ii）根据所要求的“无合理怀疑”门槛，即使在任意大的陪审团中，也可能不可能“排除任何合理怀疑”确定被告有罪。
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’.