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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A study designed to test the counterfactual explanation found support for it.
“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
Icard et al. (2017) demonstrated an interaction between the moral status of actions and the causal structure with which actions combine to bring about their effects.
“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 conjunctive scenarios, when asked for agreement to the claim that 'Billy caused the motion detector to go off', people's ratings are typically higher compared to a control version where Billy is also allowed to be in the room at 9am (abnormal inflation).
“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 disjunctive causal structures, 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 (abnormal deflation).
“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 conjunctive cases, the salient counterfactual reveals that the outcome wouldn't have occurred if not for the norm-violating agent, thus leading to increased attribution of causality.
“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
Morally bad or forbidden actions are more likely to be selected as 'the' cause of harmful outcomes, even when the descriptive causal contribution of other actions has been identical.
“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
The typical 'abnormal selection' effect (preferential selection of causes that are abnormal, for example morally bad) is found in conjunctive causal structures.
“The typical”
From Exploring the psychology of LLMs’ moral and legal reasoning (2024) · cites this paper as Icard et al., 2017
Icard and colleagues proposed that abnormal deflation in disjunctive scenarios can be explained by counterfactual reasoning: norm violation affects the salience of counterfactual cases such that we're more likely to consider counterfactuals in which the norm wasn't violated.
“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 disjunctive structures, considering the same salient counterfactual reveals that the outcome would still have occurred, which deflates causal attribution.
“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
All tested models show the same abnormal inflation effect that Icard et al. found for conjunctive structures.
“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
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People's thinking plans adapt to the problem they're trying to solve
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Causal Selection and Egalitarianism
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Communicating Causal Structure
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Plural causes in causal judgmentPreprint
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How much did each of the authors of this paper causally contribute to its writing?
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Causation, Norms, and Cognitive Bias.
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Resituating the Relevance of Alternatives for Causal Attributions
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On the different content of counterfactual and causal explanations
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Self-citationProblems and Prescriptions in Psychiatric Explanation
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How children map causal verbs to different causes across development
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Self-citation
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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