When one model casts doubt on another: A levels-of-analysis approach to causal discounting.

Khemlani, Sangeet; Oppenheimer, Daniel M.

doi:10.1037/a0021809

Cited by 21 publications

(14 citation statements)

References 132 publications

(203 reference statements)

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“…Similarly, an extensive literature on discounting (Kelley, 1973) indicates that people frequently discount the role of a cause in producing an effect given a belief that other causes could have produced that effect (see Morris &Larrick, 1995 andOppenheimer, 2011 for reviews of the discounting literature). For example, one might infer that Sally failed an exam because she did not study enough.…”

Section: Previous Findingsmentioning

confidence: 99%

Not so simple! Mechanisms increase preference for complex explanations

Jc¹,

Sloman²,

Bechlivanidis³

et al. 2020

Preprint

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Mechanisms play a central role in how we think about causality, yet not all causal explanations describe mechanisms. Across four experiments, we find that people evaluate explanations differently depending on whether or not they include mechanisms. Despite common wisdom suggesting that explanations ought to be simple (appealing to as few causes as necessary to explain an effect), the previous literature is divided over whether people adhere to this simplicity principle. Our findings suggest that the presence of mechanisms in an explanation is one factor that moderates this preference for simplicity. Without mechanisms, people typically exhibit a preference for simple explanations, consistent with probabilistic accounts. This preference is significantly reduced or even reversed when explanations contain mechanisms, suggesting that mechanisms afford a different way of evaluating explanations. Rather than focusing on probability, complex explanations that contain mechanisms may be preferred because they provide a fuller account of the underlying causal network, promoting a greater sense of understanding.

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Section: Previous Findingsmentioning

confidence: 99%

Not so simple! Mechanisms increase preference for complex explanations

Jc¹,

Sloman²,

Bechlivanidis³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…In light of the central role of explaining away in causal reasoning, it is surprising that few studies have rigorously tested whether human reasoning honors this principle. One reason for this oversight may be that in social psychology a related phenomenon, discounting (see Jones, 1979;Kelley, 1972) has been observed in many studies so that explaining away has often been taken for granted (see Khemlani & Oppenheimer, 2010;McClure, 1998, for reviews). However, discounting has been used as an umbrella term for different phenomena.…”

Section: Failures Of Explaining Awaymentioning

confidence: 99%

Failures of explaining away and screening off in described versus experienced causal learning scenarios

Rehder

Waldmann

2016

Mem Cogn

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Causal Bayes nets capture many aspects of causal thinking that set them apart from purely associative reasoning. However, some central properties of this normative theory routinely violated. In tasks requiring an understanding of explaining away and screening off, subjects often deviate from these principles and manifest the operation of an associative bias that we refer to as the rich-get-richer principle. This research focuses on these two failures comparing tasks in which causal scenarios are merely described (via verbal statements of the causal relations) versus experienced (via samples of data that manifest the intervariable correlations implied by the causal relations). Our key finding is that we obtained stronger deviations from normative predictions in the described conditions that highlight the instructed causal model compared to those that presented data. This counterintuitive finding indicate that a theory of causal reasoning and learning needs to integrate normative principles with biases people hold about causal relations.

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“…For example, the presence of peer pressure to purchase a certain brand casts doubt on the effect of personal preference on the purchase decision. Research has documented the inference process involved in discounting across various domains (Khemlani and Oppenheimer 2011;McClure 1998;Oppenheimer 2004) using adult participants (Hewstone 1994;Morris and Larrick 1995) and school-age children (Karniol and Ross 1976;Sedlak and Kurtz 1981;Smith 1975). For example, Kasin, Lowe, and Gibbons (1980) showed that kindergartners judged a triangle pushed by another square to be (directionally) less "motivated" to move forward compared to an "independent" triangle.…”

Section: Theoretical Backgroundmentioning

confidence: 99%