期刊论文详细信息
Frontiers in Psychology
Explaining Away, Augmentation, and the Assumption of Independence
article
Nicole Cruz1  Ulrike Hahn1  Norman Fenton2  David Lagnado3 
[1] Department of Psychological Sciences, University of London, United Kingdom;School of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom;Department of Experimental Psychology, University College London, United Kingdom
关键词: intercausal reasoning;    explaining away;    noisy-or;    uncertain evidence;    negative evidence;   
DOI  :  10.3389/fpsyg.2020.502751
学科分类:社会科学、人文和艺术(综合)
来源: Frontiers
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【 摘 要 】

In reasoning about situations in which several causes lead to a common effect, a much studied and yet still not well-understood inference is that of explaining away. Assuming that the causes contribute independently to the effect, if we learn that the effect is present, then this increases the probability that one or more of the causes are present. But if we then learn that a particular cause is present, this cause “explains” the presence of the effect, and the probabilities of the other causes decrease again. People tend to show this explaining away effect in their probability judgments, but to a lesser extent than predicted by the causal structure of the situation. We investigated further the conditions under which explaining away is observed. Participants estimated the probability of a cause, given the presence or the absence of another cause, for situations in which the effect was either present or absent, and the evidence about the effect was either certain or uncertain. Responses were compared to predictions obtained using Bayesian network modeling as well as a sensitivity analysis of the size of normative changes in probability under different information conditions. One of the conditions investigated: when there is certainty that the effect is absent, is special because under the assumption of causal independence, the probabilities of the causes remain invariant, that is, there is no normative explaining away or augmentation. This condition is therefore especially diagnostic of people’s reasoning about common-effect structures. The findings suggest that, alongside earlier explanations brought forward in the literature, explaining away may occur less often when the causes are assumed to interact in their contribution to the effect, and when the normative size of the probability change is not large enough to be subjectively meaningful. Further, people struggled when given evidence against negative evidence, resembling a double negation effect.

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