Dependencies in evidential reports: The case for informational advantages

Toby D Pilditch, Ulrike Hahn, Norman Fenton, David Lagnado

Abstract:

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, ceterus paribus. Furthermore, we show that lay reasoners endorse sufficient
assumptions underpinning these advantageous structures yet fail to appreciate their implications
for probability judgements and belief revision.