Intuitions play an important role in the debate on the causal status of high‐level properties. For instance, Kim has claimed that his “exclusion argument” relies on “a perfectly intuitive … understanding of the causal relation.” We report the results of three experiments examining whether laypeople really have the relevant intuitions. We find little support for Kim's view and the principles on which it relies. Instead, we find that laypeople are willing to count both a multiply realized property and its realizers (...) as causes, and regard the systematic overdetermination implied by this view as unproblematic. (shrink)

How do people judge the degree of causal responsibility that an agent has for the outcomes of her actions? We show that a relatively unexplored factor -- the robustness of the causal chain linking the agent’s action and the outcome -- influences judgments of causal responsibility of the agent. In three experiments, we vary robustness by manipulating the number of background circumstances under which the action causes the effect, and find that causal responsibility judgments increase with robustness. In the first (...) experiment, the robustness manipulation also raises the probability of the effect given the action. Experiments 2 and 3 control for probability-raising, and show that robustness still affects judgments of causal responsibility. In particular, Experiment 3 introduces an Ellsberg type of scenario to manipulate robustness, while keeping the conditional probability and the skill deployed in the action fixed. Experiment 4, replicates the results of Experiment 3, while contrasting between judgments of causal strength and of causal responsibility. The results show that in all cases, the perceived degree of responsibility increases with the robustness of the action-outcome causal chain. (shrink)

Much recent work on explanation in the interventionist tradition emphasizes the explanatory value of stable causal generalizations—i.e., causal generalizations that remain true in a wide range of background circumstances. We argue that two separate explanatory virtues are lumped together under the heading of `stability’. We call these two virtues breadth and guidance respectively. In our view, these two virtues are importantly distinct, but this fact is neglected or at least under-appreciated in the literature on stability. We argue that an adequate (...) theory of explanatory goodness should recognize breadth and guidance as distinct virtues, as breadth and guidance track different ideals of explanation, satisfy different cognitive and pragmatic ends, and play different theoretical roles in helping us understand the explanatory value of mechanisms. Thus keeping track of the distinction between these two forms of stability yields a more accurate and perspicuous picture of the role that stability considerations play in explanation. (shrink)

Conviction Narrative Theory (CNT) is a theory of choice underradical uncertainty– situations where outcomes cannot be enumerated and probabilities cannot be assigned. Whereas most theories of choice assume that people rely on (potentially biased) probabilistic judgments, such theories cannot account for adaptive decision-making when probabilities cannot be assigned. CNT proposes that people usenarratives– structured representations of causal, temporal, analogical, and valence relationships – rather than probabilities, as the currency of thought that unifies our sense-making and decision-making faculties. According to CNT, (...) narratives arise from the interplay between individual cognition and the social environment, with reasoners adopting a narrative that feels “right” to explain the available data; using that narrative to imagine plausible futures; and affectively evaluating those imagined futures to make a choice. Evidence from many areas of the cognitive, behavioral, and social sciences supports this basic model, including lab experiments, interview studies, and econometric analyses. We identify 12 propositions to explain how the mental representations (narratives) interact with four inter-related processes (explanation, simulation, affective evaluation, and communication), examining the theoretical and empirical basis for each. We conclude by discussing how CNT can provide a common vocabulary for researchers studying everyday choices across areas of the decision sciences. (shrink)

When comparing the roles of the lightning strike and the dry climate in causing the forest fire, one might think that the lightning strike is more of a cause than the dry climate, or one might think that the lightning strike completely caused the fire while the dry conditions did not cause it at all. Psychologists and philosophers have long debated whether such causal judgments are graded; that is, whether people treat some causes as stronger than others. To address this (...) debate, we first reanalyzed data from four recent studies. We found that causal judgments were actually multimodal: although most causal judgments made on a continuous scale were categorical, there was also some gradation. We then tested two competing explanations for this gradation: the confidence explanation, which states that people make graded causal judgments because they have varying degrees of belief in causal relations, and the strength explanation, which states that people make graded causal judgments because they believe that causation itself is graded. Experiment 1 tested the confidence explanation and showed that gradation in causal judgments was indeed moderated by confidence: people tended to make graded causal judgments when they were unconfident, but they tended to make more categorical causal judgments when they were confident. Experiment 2 tested the causal strength explanation and showed that although confidence still explained variation in causal judgments, it did not explain away the effects of normality, causal structure, or the number of candidate causes. Overall, we found that causal judgments were multimodal and that people make graded judgments both when they think a cause is weak and when they are uncertain about its causal role. (shrink)

Recently, Ross and Woodward (2022) argued that the reversibility of an outcome – that is, whether the outcome can be undone – affects causal judgments. One prediction of their account is that reversibility affects causal judgments in latepreemption scenarios, where people typically judge that events that produce the outcome earlier are more causal than preempted alternative events that would have otherwise produced the outcome. Ross and Woodward’s account predicts that when the outcome is reversible, people would judge these events similarly (...) – as in standard overdetermination cases. In three experiments, we found no evidence that reversibility affects causal judgments in late-preemption cases. We discuss how these results affect the experimental philosophy and cognitive science of causation, causal modeling, and experimental jurisprudence. (shrink)

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. (shrink)

The Culpable Control Model assumes that causal judgments are irrational: a negative evaluative reaction to an agent would lead individuals to overestimate his causal contribution to a harm. However, the extent to which these judgments deviate from criteria of rationality remains unclear. The two present studies aimed at investigating conditions under which this effect occurs. Participants red a vignette in which the evaluative reaction was operationalized through the agent’s motives (blameworthy, laudable). We also varied the causal link between the agent’s (...) action and the outcome (strong, weak, preempted). In both studies, we found that negative motives influenced causal judgments when a strong action-outcome link could be established. In Study 2, we replicated the effect of motives on causal judgment in the weak link condition. However, participants consistently judged the agent as less causal when the link was weak (vs. strong), regardless of the agent’s motives. These findings show that both the presence and the strength of the actual causal link between the action and the outcome moderate the detrimental effect of negative evaluative reactions on causal judgments. Thus, common sense causal judgments seem to deviate relatively little from the criteria of rationality. (shrink)