In the debate about the legal value of naked statistical evidence, Di Bello argues that (1) the likelihood ratio of such evidence is unknown, (2) the decision-theoretic considerations indicate that a conviction based on such evidence is unacceptable when expected utility maximization is combined with fairness constraints, and (3) the risk of mistaken conviction based on such evidence cannot be evaluated and is potentially too high. We argue that Di Bello’s argument for (1) works in a rather narrow context, and that (1) is not exactly in line with the way expert witnesses are required to formulate their opinions. Consequently, Di Bello’s argument for (2), which assumes (1), does not apply uniformly to all convictions based on naked evidence. Moreover, if Di Bello’s analysis is correct, it applies also to eyewitness testimony, given empirical results about its quality, and so the distinctions drawn by DiBello cut across the distinction between naked statistical evidence and other types of evidence. Finally, if we weaken the rather strong requirement of precise measurability of the risk of mistaken conviction, to the availability of reasonable but imprecise and fallible estimates, many field and empirical studies show that often the risk of mistaken conviction based on naked statistical evidence can be estimated to a similar extent as the risk of mistaken conviction based on any other sort of evidence.

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基于决策理论和基于风险的裸露统计证据方法：一些后果和挑战

在关于裸露的统计证据的法律价值的辩论中，迪贝洛认为（1）此类证据的似然比未知，（2）决策理论考虑表明，当预期效用最大化时，基于此类证据的定罪是不可接受的（3）基于此类证据的错误定罪的风险无法评估，并且可能过高。我们认为，狄贝洛（1）的论点在相当狭窄的范围内起作用，并且（1）与专家证人提出其意见的方式并不完全一致。因此，迪贝洛关于（2）的论点（假设为（1））并不适用于所有基于裸露证据的定罪。此外，如果Di Bello的分析是正确的，那么它也适用于目击者的证词，给出关于其质量的经验结果，因此DiBello所做出的区分跨越了裸露的统计证据与其他类型的证据之间的区别。最后，如果我们削弱对错误定罪风险的精确可测性的强烈要求，以提供合理但不准确且容易犯错的估计，许多实地和实证研究表明，基于裸露的统计证据经常会导致错误定罪的风险常常是根据任何其他种类的证据，估计与误判的风险相似。