The DOI matches its Crossref record; 51 of the 52 references it cites were found in a registry or an index.
Normality and actual causal strength
Abstract
Existing research suggests that people's judgments of actual causation can be influenced by the degree to which they regard certain events as normal. We develop an explanation for this phenomenon that draws on standard tools from the literature on graphical causal models and, in particular, on the idea of probabilistic sampling. Using these tools, we propose a new measure of actual causal strength. This measure accurately captures three effects of normality on causal judgment that have been observed in existing studies. More importantly, the measure predicts a new effect ("abnormal deflation"). Two studies show that people's judgments do, in fact, show this new effect. Taken together, the patterns of people's causal judgments thereby provide support for the proposed explanation.
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In the citing paper
“In this case, a study designed to achieve exactly this goal found support for the proposed explanation, as we will see in Section 2.7 (Icard et al., 2017).”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“Icard et al. (2017) additionally demonstrated an interaction between the moral status of actions and the causal structure with which actions combine to bring about their effects.”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“When asked for their agreement to the claim that”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“However, when the description is changed to a so-called disjunctive causal structure where either Billy's or Suzy's being in the room at 9am is sufficient for the motion detector to go off, this changes.In this version of the scenario, Billy's action would be rated as less causal when he is forbidden to be in the room at 9am compared to when he is allowed to do so.This effect has been dubbed ab”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“In conjunctive cases, this salient counterfactual reveals that the outcome wouldn't have occurred if not for the norm-violating agent, thus leading to increased attribution of causality.”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“Most famously, morally bad or forbidden actions are more likely to be selected as”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“The typical”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“Icard and colleagues have proposed that this can be explained by counterfactual reasoning.Crucially, they claim that norm violation affects the salience of counterfactual cases such that we're more likely to consider counterfactuals in which the norm wasn't violated.”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“In contrast, considering the same salient counterfactual in disjunctive structures reveals that the outcome would still have occurred.This deflates causal attribution.”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
In the citing paper
“In other words, all tested models show the same abnormal inflation effect that Icard et al. found for conjunctive structures.”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
Citations
Cites
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Norm theory: Comparing reality to its alternatives.
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Proceedings of the 35th Annual Meeting of the Cognitive Science Society
Culbertson, J., & Wilson, C. (2013) · Cited by 1,139
Lewis, D. M. (2000) · The Journal of Philosophy · doi:10.2307/2678389 · Cited by 936
(2004) · The MIT Press eBooks · doi:10.7551/mitpress/1752.001.0001 · Cited by 896
Proceedings of the 39th Annual Conference of the Cognitive Science Society
Motamedi, Y., Schouwstra, M., Culbertson, J., Smith, K., & Kirby, S. (2017) · Cited by 870
Cited by
Sorted by citations
Woodward, J. (2007) · Oxford University Press eBooks · doi:10.1093/oso/9780197585412.001.0001 · Cited by 206
Phillips, J., Morris, A., & Cushman, F. A. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.09.007 · Cited by 115
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning
Kenny, E. M., & Keane, M. T. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i13.17377 · Cited by 108
Differentiating “could” from “should”: Developmental changes in modal cognition
Shtulman, A., & Phillips, J. (2017) · Journal of Experimental Child Psychology · doi:10.1016/j.jecp.2017.05.012 · Cited by 89
A counterfactual explanation for the action effect in causal judgment
Henne, P., Niemi, L., Pinillos, Á., Brigard, F. D., & Knobe, J. (2019) · Cognition · doi:10.1016/j.cognition.2019.05.006 · Cited by 89
Self-citation
Metadata
- Authors
- Icard, T. F., Kominsky, J. F., & Knobe, J.
- Affiliations
- Stanford University (US)
- Harvard University (US)
- Yale University (US)
- Corresponding author
- Icard, Thomas F.
- Venue
- Cognition
- Publisher
- Elsevier BV
- Published
- 2017-04
- Volume
- 161
- Pages
- 80-93
- ISSN
- 0010-0277 (ISSN-L)
- OpenAlex
- W2583640572
- Cited by
- 155
- References
- 52
- Citations by year
- 2026: 18 · 2025: 19 · 2024: 20 · 2023: 24 · 2022: 17 · 2021: 26 · 2020: 9 · 2019: 11 · 2018: 9 · 2017: 1
- FWCI
- 4.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cognition (publishedVersion)
- PubMed (publishedVersion)
- PhilPapers (PhilPapers Foundation) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Life Sciences › Neuroscience › Cognitive Neuroscience › Psychology of Moral and Emotional Judgment
- Keywords
- actual causation, normality, causal judgment, causal strength, probability sampling, causal graphical models, causal explanation, counterfactual reasoning
- MeSH terms
- Bayes Theorem, Humans, Imagination, Judgment, Models, Psychological
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