Whether assessing the accuracy of expert forecasting, the pros and cons of group communication, or the value of evidence in diagnostic or predictive reasoning, dependencies between experts, group members, or evidence have traditionally been seen as a form of redundancy. We demonstrate that this conception of dependence conflates the structure of a dependency network, and the observations across this network. By disentangling these two elements we show, via mathematical proof and specific examples, that there are cases where dependencies yield an informational advantage over independence. More precisely, when a structural dependency exists, but observations are either partial or contradicting, these observations provide more support to a hypothesis than when this structural dependency does not exist, ceteris paribus. Furthermore, we show that lay reasoners endorse sufficient assumptions underpinning these advantageous structures yet fail to appreciate their implications for probability judgments and belief revision.

无论是评估专家预测的准确性，团队交流的利弊，还是诊断或预测推理中证据的价值，专家，团队成员或证据之间的依存关系传统上都被视为一种冗余形式。我们证明了这种依存关系的概念可以使依存关系网络的结构以及该网络中的观察结果变得更加平整。通过解开这两个元素，我们通过数学证明和具体示例说明，在某些情况下，依赖项会产生信息优势过度独立。更确切地说，当一个结构性的依赖存在，但观察是部分或矛盾，这些意见提供了一个假设时相比，这种结构性的依赖性不存在更多的支持，其他条件不变。此外，我们表明，外行推理者认可了支持这些有利结构的充分假设，但未能意识到其对概率判断和信念修正的影响。