Interpolating causal mechanisms: The paradox of knowing more.
Interpolating causal mechanisms: The paradox of knowing more.
复制标题
插入因果机制：了解更多的悖论
DOI：
10.1037/xge0001016
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Waldmann
中科院分区：
文献类型：
--
作者：
Stephan;Tentori;Pighin;Waldmann
因果知识不是静态的;它不断根据新的证据进行修改。目前的一组七个实验探讨了一个重要的情况下，因果信念修订，一直被忽视的研究，到目前为止：因果插值。插值的一个简单的原型情况是这样一种情况，即我们最初知道两个变量之间的因果关系或正协变，但后来对连接这两个变量的机制感兴趣。我们的关键发现是，机制变量的插值往往被歪曲，这导致了了解更多的悖论：人们对一种机制了解得越多，他们就越倾向于发现两个变量之间的概率关系（即弱化效应）。事实上，在我们所有的实验中，我们发现，尽管关于两个变量的学习数据相同，但当后续研究表明这两个变量被假设为直接因果联系（即C→ E）时，与被试被告知因果关系实际上是由代表机制组成部分的变量介导（M;即C→ M→ E）时相比，将这两个变量联系起来的概率更高。我们对弱化效应的解释是，人们经常将先前存在但未知的机制的发现与新变量被添加到先前更简单的因果模型中的情况相混淆，从而违反了自然类域中的因果稳定性假设。实验测试了这一假设的几个含义。（PsycInfo数据库记录（c）2021阿帕，保留所有权利）
Causal knowledge is not static; it is constantly modified based on new evidence. The present set of seven experiments explores 1 important case of causal belief revision that has been neglected in research so far: causal interpolations. A simple prototypic case of an interpolation is a situation in which we initially have knowledge about a causal relation or a positive covariation between 2 variables but later become interested in the mechanism linking these 2 variables. Our key finding is that the interpolation of mechanism variables tends to be misrepresented, which leads to the paradox of knowing more: The more people know about a mechanism, the weaker they tend to find the probabilistic relation between the 2 variables (ie, weakening effect). Indeed, in all our experiments we found that, despite identical learning data about 2 variables, the probability linking the 2 variables was judged higher when follow-up research showed that the 2 variables were assumed to be directly causally linked (ie, C→ E) than when participants were instructed that the causal relation is in fact mediated by a variable representing a component of the mechanism (M; ie, C→ M→ E). Our explanation of the weakening effect is that people often confuse discoveries of preexisting but unknown mechanisms with situations in which new variables are being added to a previously simpler causal model, thus violating causal stability assumptions in natural kind domains. The experiments test several implications of this hypothesis.(PsycInfo Database Record (c) 2021 APA, all rights reserved)