Immoral Professors and Malfunctioning Tools: Counterfactual Relevance Accounts Explain the Effect of Norm Violations on Causal Selection

Calculated Comparisons: Manufacturing Societal Causal Judgments by Implying Different Counterfactual Outcomes

How do people come to opposite causal judgments about societal problems, such as whether a public health policy reduced COVID-19 cases? The current research tests an understudied cognitive mechanism in which people may agree about what actually happened (e.g., that a public health policy was implemented and COVID-19 cases declined), but can be made to disagree about the counterfactual, or what would have happened otherwise (e.g., whether COVID-19 cases would have declined naturally without intervention) via comparison cases. Across two preregistered studies (total N = 480), participants reasoned about the implementation of a public policy that was followed by an immediate decline in novel virus cases. Study 1 shows that people's judgments about the causal impact of the policy could be pushed in opposite directions by emphasizing comparison cases that imply different counterfactual outcomes. Study 2 finds that people recognize they can use such information to influence others. Specifically, in service of persuading others to support or reject a public health policy, people systematically showed comparison cases implying the counterfactual outcome that aligned with their position. These findings were robust across samples of U.S. college students and politically and socioeconomically diverse U.S. adults. Together, these studies suggest that implied counterfactuals are a powerful tool that individuals can use to manufacture others' causal judgments and warrant further investigation as a mechanism contributing to belief polarization.

The importance of epistemic intentions in ascription of responsibility

We investigate how people ascribe responsibility to an agent who caused a bad outcome but did not know he would. The psychological processes for making such judgments, we argue, involve finding a counterfactual in which some minimally benevolent intention initiates a course of events that leads to a better outcome than the actual one. We hypothesize that such counterfactuals can include, when relevant, epistemic intentions. With four vignette studies, we show that people consider epistemic intentions when ascribing responsibility for a bad outcome. We further investigate which epistemic intentions people are likely to consider when building counterfactuals for responsibility ascription. We find that, when an agent did not predict a bad outcome, people ascribe responsibility depending on the reasons behind the agents' lack of knowledge. People judge agents responsible for the bad outcome they caused when they could have easily predicted the consequences of their actions but did not care to acquire the relevant information. However, when this information was hard to acquire, people are less likely to judge them responsible.

Mutual entailment between causation and responsibility

The standard view in philosophy is that responsibility entails causation. Most philosophers treat this entailment claim as an evident insight into the ordinary concepts of responsibility and causation. Further, it is taken to be equally obvious that the reversal of this claim does not hold: causation does not entail responsibility. In contrast, Sytsma and Livengood have put forward an account of the use of ordinary causal attributions (statements like "X caused Y") that contends that they are typically used interchangeably with responsibility attributions (statements like "X is responsible for Y"). Put in terms of the concepts at play in these attributions, this account suggests that the reversal of the entailment claim may also hold, and, a fortiori, there would be mutual entailment between the ordinary concepts of responsibility and causation. Using the cancellability test, we report the results of three pre-registered studies providing empirical evidence that causation and responsibility are mutually entailed by each other.

The pervasive impact of ignorance

Norm violations have been demonstrated to impact a wide range of seemingly non-normative judgments. Among other things, when agents' actions violate prescriptive norms they tend to be seen as having done those actions more freely, as having acted more intentionally, as being more of a cause of subsequent outcomes, and even as being less happy. The explanation of this effect continue to be debated, with some researchers appealing to features of actions that violate norms, and other researcher emphasizing the importance of agents' mental states when acting. Here, we report the results of two large-scale experiments that replicate and extend twelve of the studies that originally demonstrated the pervasive impact of norm violations. In each case, we build on the pre-existing experimental paradigms to additionally manipulate whether the agents knew that they were violating a norm while holding fixed the action done. We find evidence for a pervasive impact of ignorance: the impact of norm violations on non-normative judgments depends largely on the agent knowing that they were violating a norm when acting. Moreover, we find evidence that the reduction in the impact of normality is underpinned by people's counterfactual reasoning: people are less likely to consider an alternative to the agent's action if the agent is ignorant. We situate our findings in the wider debate around the role or normality in people's reasoning.

What would have happened? Counterfactuals, hypotheticals and causal judgements

How do people make causal judgements? In this paper, I show that counterfactual simulations are necessary for explaining causal judgements about events, and that hypotheticals do not suffice. In two experiments, participants viewed video clips of dynamic interactions between billiard balls. In Experiment 1, participants either made hypothetical judgements about whether ball B would go through the gate if ball A were not present in the scene, or counterfactual judgements about whether ball B would have gone through the gate if ball A had not been present. Because the clips featured a block in front of the gate that sometimes moved and sometimes stayed put, hypothetical and counterfactual judgements came apart. A computational model that evaluates hypotheticals and counterfactuals by running noisy physical simulations accurately captured participants' judgements. In Experiment 2, participants judged whether ball A caused ball B to go through the gate. The results showed a tight fit between counterfactual and causal judgements, whereas hypotheticals did not predict causal judgements. I discuss the implications of this work for theories of causality, and for studying the development of counterfactual thinking in children. This article is part of the theme issue 'Thinking about possibilities: mechanisms, ontogeny, functions and phylogeny'.

It's not what you did, it's what you could have done

We are more likely to judge agents as morally culpable after we learn they acted freely rather than under duress or coercion. Interestingly, the reverse is also true: Individuals are more likely to be judged to have acted freely after we learn that they committed a moral violation. Researchers have argued that morality affects judgments of force by making the alternative actions the agent could have done instead appear comparatively normal, which then increases the perceived availability of relevant alternative actions. Across five studies, we test the novel predictions of this account. We find that the degree to which participants view possible alternative actions as normal strongly predicts their perceptions that an agent acted freely. This pattern holds both for perceptions of the prescriptive normality of the alternatives (whether the actions are good) and descriptive normality of the alternatives (whether the actions are unusual). We also find that manipulating the prudential value of alternative actions or the degree to which alternatives adhere to social norms, has a similar effect to manipulating whether the actions or their alternatives violate moral norms. This pattern persists even when what is actually done is held constant, and these effects are explained by changes in the perceived normality of the alternatives. Together, these results suggest that across contexts, participants' force judgments depend not on the morality of the actual action taken, but on the normality of possible alternatives. More broadly, our results build on prior work that suggests a unifying role of normality and counterfactuals across many areas of high-level human cognition.

An interaction effect of norm violations on causal judgment

Existing research has shown that norm violations influence causal judg- ments, and a number of different models have been developed to explain these effects. One such model, the necessity/sufficiency model, predicts an interac- tion pattern in people's judgments. Specifically, it predicts that when people are judging the degree to which a particular factor is a cause, there should be an interaction between (a) the degree to which that factor violates a norm and (b) the degree to which another factor in the situation violates norms. A study of moral norms (N=1000) and norms of proper functioning (N=3000) revealed robust evidence for the predicted interaction effect. The implications of these patterns for existing theories of causal judgments is discussed.

Double Prevention, Causal Judgments, and Counterfactuals

Mike accidentally knocked against a bottle. Seeing that the bottle was about to fall, Jack was just about to catch it when Peter accidentally knocked against him, making Jack unable to catch it. Jack did not grab the bottle, and it fell to the ground and spilled. In double-prevention cases like these, philosophers and nonphilosophers alike tend to judge that Mike knocking into the bottle caused the beer to spill and that Peter knocking into Jack did not cause the beer to spill. This difference in causal judgment is a difficult puzzle for counterfactual theories of causal judgment; if each event had not happened, the outcome would not have, yet there is a difference in people's causal judgments. In four experiments and three supplemental experiments, we confirm this difference in causal judgments. We also show that differences in people's counterfactual thinking can explain this difference in their causal judgments and that recent counterfactual models of causal judgment can account for these patterns. We discuss these results in relation to work on counterfactual thinking and causal modeling.

Causal Judgment in the Wild: Evidence from the 2020 U.S. Presidential Election

When explaining why an event occurred, people intuitively highlight some causes while ignoring others. How do people decide which causes to select? Models of causal judgment have been evaluated in simple and controlled laboratory experiments, but they have yet to be tested in a complex real-world setting. Here, we provide such a test, in the context of the 2020 U.S. presidential election. Across tens of thousands of simulations of possible election outcomes, we computed, for each state, an adjusted measure of the correlation between a Biden victory in that state and a Biden election victory. These effect size measures accurately predicted the extent to which U.S. participants (N = 207, preregistered) viewed victory in a given state as having caused Biden to win the presidency. Our findings support the theory that people intuitively select as causes of an outcome the factors with the largest standardized causal effect on that outcome across possible counterfactual worlds.

A counterfactual simulation model of causation by omission

When do people say that an event that did not happen was a cause? We extend the counterfactual simulation model (CSM) of causal judgment (Gerstenberg, Goodman, Lagnado, & Tenenbaum, 2021) and test it in a series of three experiments that look at people's causal judgments about omissions in dynamic physical interactions. The problem of omissive causation highlights a series of questions that need to be answered in order to give an adequate causal explanation of why something happened: what are the relevant variables, what are their possible values, how are putative causal relationships evaluated, and how is the causal responsibility for an outcome attributed to multiple causes? The CSM predicts that people make causal judgments about omissions in physical interactions by using their intuitive understanding of physics to mentally simulate what would have happened in relevant counterfactual situations. Prior work has argued that normative expectations affect judgments of omissive causation. Here we suggest a concrete mechanism of how this happens: expectations affect what counterfactuals people consider, and the more certain people are that the counterfactual outcome would have been different from what actually happened, the more causal they judge the omission to be. Our experiments show that both the structure of the physical situation as well as expectations about what will happen affect people's judgments.

A simple definition of 'intentionally'

Cognitive scientists have been debating how the folk concept of intentional action works. We suggest a simple account: people consider that an agent did X intentionally to the extent that X was causally dependent on how much the agent wanted X to happen (or not to happen). Combined with recent models of human causal cognition, this definition provides a good account of the way people use the concept of intentional action, and offers natural explanations for puzzling phenomena such as the side-effect effect. We provide empirical support for our theory, in studies where we show that people's causation and intentionality judgments track each other closely, in everyday situations as well as in scenarios with unusual causal structures. Study 5 additionally shows that the effect of norm violations on intentionality judgments depends on the causal structure of the situation, in a way uniquely predicted by our theory. Taken together, these results suggest that the folk concept of intentional action has been difficult to define because it is made of cognitive building blocks, such as our intuitive concept of causation, whose logic cognitive scientists are just starting to understand.

Causal judgments about atypical actions are influenced by agents' epistemic states

A prominent finding in causal cognition research is people's tendency to attribute increased causality to atypical actions. If two agents jointly cause an outcome (conjunctive causation), but differ in how frequently they have performed the causal action before, people judge the atypically acting agent to have caused the outcome to a greater extent. In this paper, we argue that it is the epistemic state of an abnormally acting agent, rather than the abnormality of their action, that is driving people's causal judgments. Given the predictability of the normally acting agent's behaviour, the abnormal agent is in a better position to foresee the consequences of their action. We put this hypothesis to test in four experiments. In Experiment 1, we show that people judge the atypical agent as more causal than the normally acting agent, but also judge the atypical agent to have an epistemic advantage. In Experiment 2, we find that people do not judge a causal difference if no epistemic advantage for the abnormal agent arises. In Experiment 3, we replicate these findings in a scenario in which the abnormal agent's epistemic advantage generalises to a novel context. In Experiment 4, we extend these findings to mental states more broadly construed and develop a Bayesian network model that predicts the degree of outcome-oriented mental states based on action normality and epistemic states. We find that people infer mental states like desire and intention to a greater extent from abnormal behaviour when this behaviour is accompanied by an epistemic advantage. We discuss these results in light of current theories and research on people's preference for abnormal causes.

The trajectory of counterfactual simulation in development

Young children often struggle to answer the question "what would have happened?" particularly in cases where the adult-like "correct" answer has the same outcome as the event that actually occurred. Previous work has assumed that children fail because they cannot engage in accurate counterfactual simulations. Children have trouble considering what to change and what to keep fixed when comparing counterfactual alternatives to reality. However, most developmental studies on counterfactual reasoning have relied on binary yes/no responses to counterfactual questions about complex narratives and so have only been able to document when these failures occur but not why and how. Here, we investigate counterfactual reasoning in a domain in which specific counterfactual possibilities are very concrete: simple collision interactions. In Experiment 1, we show that 5- to 10-year-old children (recruited from schools and museums in Connecticut) succeed in making predictions but struggle to answer binary counterfactual questions. In Experiment 2, we use a multiple-choice method to allow children to select a specific counterfactual possibility. We find evidence that 4- to 6-year-old children (recruited online from across the United States) do conduct counterfactual simulations, but the counterfactual possibilities younger children consider differ from adult-like reasoning in systematic ways. Experiment 3 provides further evidence that young children engage in simulation rather than using a simpler visual matching strategy. Together, these experiments show that the developmental changes in counterfactual reasoning are not simply a matter of whether children engage in counterfactual simulation but also how they do so. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Norms Affect Prospective Causal Judgments

People more frequently select norm-violating factors, relative to norm-conforming ones, as the cause of some outcome. Until recently, this abnormal-selection effect has been studied using retrospective vignette-based paradigms. We use a novel set of video stimuli to investigate this effect for prospective causal judgments-that is, judgments about the cause of some future outcome. Four experiments show that people more frequently select norm-violating factors, relative to norm-conforming ones, as the cause of some future outcome. We show that the abnormal-selection effects are not primarily explained by the perception of agency (Experiment 4). We discuss these results in relation to recent efforts to model causal judgment.