What would have happened? Counterfactuals, hypotheticals, and causal judgments

Gerstenberg, Tobias

doi:10.31234/osf.io/rsb46

Cited by 4 publications

(4 citation statements)

References 72 publications

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“…An alternative hypothesis is that people use hypothetical reasoning instead. That is, people might make causal judgments by consulting pre-existing simulations of what would happen, that they generated before the event actually happened (see Gerstenberg, 2022). Our new experimental results show that people simulate possibilities that are centered on what actually happened-effectively ruling out the hypothetical simulation hypothesis (see also Gerstenberg, 2022 for convergent evidence for causal judgments involving only one candidate cause).…”

Section: Counterfactual Samplingmentioning

confidence: 77%

“…Our theory belongs to a general framework that views causation as a matter of counterfactual dependence (Woodward, 2006;Halpern & Pearl, 2005;Lewis, 1973a;Woodward, 2003;Gerstenberg, 2022;Wells & Gavanski, 1989;Krasich et al, n.d.). According to counterfactual theories, "C caused E" means (roughly) that if C had not happened, then E would not have happened either.…”

Section: The Function Of Causal Selectionmentioning

confidence: 99%

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Counterfactuals and the logic of causal selection

Quillien¹,

Lucas²

2022

Preprint

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Everything that happens has a multitude of causes, but people make causal judgments effortlessly. How do people select one particular cause (e.g. the lightning bolt that set the forest ablaze) out of the set of factors that contributed to the event (the oxygen in the air, the dry weather. . . )? Cognitive scientists have suggested that people make causal judgments about an event by simulating alternative ways things could have happened. We argue that this counterfactual theory explains many features of human causal intuitions, given two simple assumptions. First, people tend to imagine counterfactual possibilities that are both a priori likely and similar to what actually happened. Second, people judge that a factor C caused effect E if C and E are highly correlated across these counterfactual possibilities. In a reanalysis of existing empirical data, and a set of new experiments, we find that this theory uniquely accounts for people’s causal intuitions.

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Section: Counterfactual Samplingmentioning

confidence: 77%

Section: The Function Of Causal Selectionmentioning

confidence: 99%

Counterfactuals and the logic of causal selection

Quillien¹,

Lucas²

2022

Preprint

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“…where O = 0 o i =0 expresses the counterfactual probability of a team loss if player i failed, assuming that in fact the team won (O = 1). We adopt this notation for expressing counterfactuals from Pearl (2000) (see also Gerstenberg, 2022). Intuitively, this model computes a player's expected credit, assuming that credit = 1 whenever their action was pivotal for the team win.…”

Section: The Credit Modelmentioning

confidence: 99%

Making a positive difference: Criticality in groups

Lagnado¹,

Zultan²

2023

Preprint

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How critical are individual members perceived to be for their group's performance? In this paper, we show that judgments of criticality are intimately linked to considering responsibility. Prospective responsibility attributions in groups are relevant across many domains and situations, and have the potential to influence motivation, performance, and allocations of resources. We develop various models that differ in how the relationship between criticality and responsibility is conceptualized. To test our models, we experimentally vary the task structure (disjunctive, conjunctive, and mixed) and the abilities of the group members (which affects their probability of success). We show that both factors influence criticality judgments, and that a model which construes criticality as anticipated credit best explains participants' judgments. Unlike prior work that has defined criticality as anticipated responsibility for both success and failures, our results suggest that people only consider the possible outcomes in which an individual contributed to a group success, but disregard group failure.

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“…Recently, Gerstenberg (2022) addressed the question of whether counterfactual simulations are necessary for understanding people's causal judgments about physical events, or whether hypothetical simulations suffice. The difference between hypotheticals and counterfactuals is subtle but important.…”

Section: Introductionmentioning

confidence: 99%

That was close! A counterfactual simulation model of causal judgments about decisions

Sridhar²

2022

Preprint

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How do people make causal judgments about other's decisions? Prior work has argued that judging causation requires going beyond what actually happened and simulating what would have happened in a relevant counterfactual situation. Here, we extend the counterfactual simulation model of causal judgments for physical events, to explain judgments about other agents' decisions. In our experiments, an agent chooses what path to take to reach a goal. In Experiment 1, participants either made hypothetical judgments about whether the agent would succeed were it to take a certain path, or counterfactual judgments about whether the agent would have succeeded had it taken a different path. In Experiment 2, participants made causal judgments about whether the agent succeeded or failed because of the path that it took. Our computational model accurately captured participants' judgments in both experiments and we find that causal judgments are better explained by counterfactuals rather than hypotheticals.

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What would have happened? Counterfactuals, hypotheticals, and causal judgments

Cited by 4 publications

References 72 publications

Counterfactuals and the logic of causal selection

Counterfactuals and the logic of causal selection

Making a positive difference: Criticality in groups

That was close! A counterfactual simulation model of causal judgments about decisions

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