I present and develop the view that omissions are de re possibilities of actual events. Omissions do not literally fail to occur; rather, they possibly occur. An omission is a tripartite metaphysical entity composed of an actual event, a possible event, and a contextually specified counterpart relation between them. This view resolves ontological, causal, and semantic puzzles about omissions, and also accounts for important data about moral responsibility for outcomes resulting from omissions.

Causation is one of philosophy's most venerable and thoroughly-analyzed concepts. However, the study of how ordinary people make causal judgments is a much more recent addition to the philosophical arsenal. One of the most prominent views of causal explanation, especially in the realm of harmful or potentially harmful behavior, is that unusual or counternormative events are accorded privileged status in ordinary causal explanations. This is a fundamental assumption in psychological theories of counterfactual reasoning, and has been transported to philosophy by (...) Hitchcock and Knobe (2009). A different view--the basis of the culpable control model of blame (CCM)--is that primary causal status is accorded to behaviors that arouse negative evaluative reactions, including behaviors that stem from nefarious motives, negligence or recklessness, a faulty character, or behaviors that lead to harmful or potentially harmful consequences. This paper describes four empirical studies that show consistent support for the CCM. (shrink)

Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual dependence or on physical connections. This paper argues that both approaches to causation are psychologically real, with different modes of explanation promoting judgments more or less consistent with each approach. Two sets of experiments isolate the (...) contributions of counterfactual dependence and physical connections in causal ascriptions involving events with people, artifacts, or biological traits, and manipulate whether the events are construed teleologically or mechanistically. The findings suggest that when events are construed teleologically, causal ascriptions are sensitive to counterfactual dependence and relatively insensitive to the presence of physical connections, but when events are construed mechanistically, causal ascriptions are sensitive to both counterfactual dependence and physical connections. The conclusion introduces an account of causation, an "exportable dependence theory," that provides a way to understand the contributions of physical connections and teleology in terms of the functions of causal ascriptions. (shrink)

We report three experiments investigating whether people’s judgments about causal relationships are sensitive to the robustness or stability of such relationships across a range of background circumstances. In Experiment 1, we demonstrate that people are more willing to endorse causal and explanatory claims based on stable (as opposed to unstable) relationships, even when the overall causal strength of the relationship is held constant. In Experiment 2, we show that this effect is not driven by a causal generalization’s actual scope of (...) application. In Experiment 3, we offer evidence that stable causal relationships may be seen as better guides to action. Collectively, these experiments document a previously underappreciated factor that shapes people’s causal reasoning: the stability of the causal relationship. (shrink)

This paper develops axiomatic foundations for a probabilistic-interventionist theory of causal strength. Transferring methods from Bayesian confirmation theory, I proceed in three steps: I develop a framework for defining and comparing measures of causal strength; I argue that no single measure can satisfy all natural constraints; I prove two representation theorems for popular measures of causal strength: Pearl's causal effect measure and Eells' difference measure. In other words, I demonstrate these two measures can be derived from a set of plausible (...) adequacy conditions. The paper concludes by sketching future research avenues. (shrink)

We critique the distinction Byrne makes between strong causes and enabling conditions, and its implications, on both theoretical and empirical grounds. First, we believe that the difference is psychological, not logical. Second, we disagree that there is a strict Third, we disagree that it is easier for people to generate causes than counterfactuals.

Does a person's liability to attack during a war depend on the nature of their individual causal contribution to the (unjust) threat posed? If so, how? The recent literature on the ethics of war has become increasingly focused on questions of this kind. According to some views on these matters, your liability hinges on the extent of your causal contribution: the larger your contribution to an unjust threat, the larger the amount of harm that we can impose on you in (...) order to avert the threat. Some philosophers have suggested that we can ground a quite general principle of civilian immunity on this basis. But, do causal contributions really come in degrees? Can we make sense of a graded notion of causal contribution that can be relevant to debates about liability in war? I argue there is good reason to be sceptical. The appearance that causal contributions come in degrees is just an illusion that can be explained away. (shrink)

This paper presents a drastically revised version of the theory of causality, based on analyses of causal processes and causal interactions, advocated in Salmon (1984). Relying heavily on modified versions of proposals by P. Dowe, this article answers penetrating objections by Dowe and P. Kitcher to the earlier theory. It shows how the new theory circumvents a host of difficulties that have been raised in the literature. The result is, I hope, a more satisfactory analysis of physical causality.

Some omissions seem to be causes. For example, suppose Barry promises to water Alice’s plant, doesn’t water it, and that the plant then dries up and dies. Barry’s not watering the plant – his omitting to water the plant – caused its death. But there is reason to believe that if omissions are ever causes, then there is far more causation by omission than we ordinarily think. In other words, there is reason to think the following thesis true.

We report two Experiments to compare counterfactual thoughts about how an outcome could have been different and causal explanations about why the outcome occurred. Experiment 1 showed that people generate counterfactual thoughts more often about controllable than uncontrollable events, whereas they generate causal explanations more often about unexpected than expected events. Counterfactual thoughts focus on specific factors, whereas causal explanations focus on both general and specific factors. Experiment 2 showed that in their spontaneous counterfactual thoughts, people focus on normal events (...) just as often as exceptional events, unlike in directed counterfactual thoughts. The findings are consistent with the suggestion that counterfactual thoughts tend to focus on how a specific unwanted outcome could have been prevented, whereas causal explanations tend to provide more general causal information that enables future understanding, prediction, and intervention in a wide range of situations. (shrink)

How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in multiple agent contexts. We draw on the structural model account of actual causation (e.g., Halpern & Pearl, 2005) and its extension to responsibility judgments (Chockler & Halpern, 2004). We review the main (...) theoretical and empirical issues that arise from this literature and propose a novel model of intuitive judgments of responsibility. This model is a function of both pivotality (whether an agent made a difference to the outcome) and criticality (how important the agent is perceived to be for the outcome, before any actions are taken). The model explains empirical results from previous studies and is supported by a new experiment that manipulates both pivotality and criticality. We also discuss possible extensions of this model to deal with a broader range of causal situations. Overall, our approach emphasizes the close interrelations between causality, counterfactuals, and responsibility attributions. (shrink)

Causal judgments are widely known to be sensitive to violations of both prescriptive norms (e.g., immoral events) and statistical norms (e.g., improbable events). There is ongoing discussion as to whether both effects are best explained in a unified way through changes in the relevance of counterfactual possibilities, or whether these two effects arise from unrelated cognitive mechanisms. Recent work has shown that moral norm violations affect causal judgments of agents, but not inanimate artifacts used by those agents. These results have (...) been interpreted as showing that prescriptive norm violations only affect causal reasoning about intentional agents, but not the use of inanimate artifacts, thereby providing evidence that the effect of prescriptive norm violations arises from mechanisms specific to reasoning about intentional agents, and thus casting doubt on a unified counterfactual analysis of causal reasoning. Four experiments explore this recent finding and provide clear support for a unified counterfactual analysis. Experiment 1 demonstrates that these newly observed patterns in causal judgments are closely mirrored by judgments of counterfactual relevance. Experiment 2 shows that the relationship between causal and counterfactual judgments is moderated by causal structure, as uniquely predicted by counterfactual accounts. Experiment 3 directly manipulates the relevance of counterfactual alternatives and finds that causal judgments of intentional agents and inanimate artifacts are similarly affected. Finally, Experiment 4 shows that prescriptive norm violations (in which artifacts malfunction) affect causal judgments of inanimate artifacts in much the same way that prescriptive norm violations (in which agents act immorally) affect causal judgments of intentional agents. (shrink)

When agents violate norms, they are typically judged to be more of a cause of resulting outcomes. In this paper, we suggest that norm violations also affect the causality attributed to other agents, a phenomenon we refer to as "causal superseding." We propose and test a counterfactual reasoning model of this phenomenon in four experiments. Experiments 1 and 2 provide an initial demonstration of the causal superseding effect and distinguish it from previously studied effects. Experiment 3 shows that this causal (...) superseding effect is dependent on a particular event structure, following a prediction of our counterfactual model. Experiment 4 demonstrates that causal superseding can occur with violations of non-moral norms. We propose a model of the superseding effect based on the idea of counterfactual sufficiency. (shrink)

It is often natural to compare two events by describing one as ‘more of a cause’ of some effect than the other. But what do such comparisons amount to, exactly? This paper aims to provide a guided tour of the recent literature on ‘degrees of causation’. Section 2 looks at what I call ‘dependence measures’, which arise from thinking of causes as difference‐makers. Section 3 looks at what I call ‘production measures’, which arise from thinking of causes as jointly sufficient (...) for their effects. Finally, section 4 examines the important question of whether there is any sense in which an agent is more responsible for an outcome in virtue of her action being more of a cause of it. I describe a puzzle that emerges from this question, and explore various strategies for resolving it. (shrink)

Are there ‘degrees of causation’? Yes and no: causation is not a scalar relation, but different causes can contribute to a causing of an effect to different extents. In this paper, I motivate a probabilistic analysis of an event’s degree of contribution to a causing of an effect and explore some of its consequences.

This guide accompanies the following article(s): Jackson, E., Philosophy Compass 15/6 (2020) pp. 1-13 10.1111/phc3.12668.x.

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. (shrink)

This article describes research pursued by members of the McDonnell Collaborative on Causal Learning. A number of members independently converged on a similar idea: one of the central functions served by claims of actual causation is to highlight patterns of dependence that are highly portable into novel contexts. I describe in detail how this idea emerged in my own work and also in that of the psychologist Tania Lombrozo. In addition, I use the occasion to reflect on the nature of (...) interdisciplinary collaboration in general and on the interaction between philosophy and psychology in particular. (shrink)

Much of the philosophical literature on causation has focused on the concept of actual causation, sometimes called token causation. In particular, it is this notion of actual causation that many philosophical theories of causation have attempted to capture.2 In this paper, we address the question: what purpose does this concept serve? As we shall see in the next section, one does not need this concept for purposes of prediction or rational deliberation. What then could the purpose be? We will argue (...) that one can gain an important clue here by looking at the ways in which causal judgments are shaped by people‘s understanding of norms. (shrink)

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—i.e., 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. (shrink)

People tend to judge more recent events, relative to earlier ones, as the cause of some particular outcome. For instance, people are more inclined to judge that the last basket, rather than the first, caused the team to win the basketball game. This recency effect, however, reverses in cases of overdetermination: people judge that earlier events, rather than more recent ones, caused the outcome when the event is individually sufficient but not individually necessary for the outcome. In five experiments (N (...) = 5507), we find evidence for the recency effect and the primacy effect for causal judgment. Traditionally, these effects have been a problem for counterfactual views of causal judgment. However, we argue that an extension of a recent counterfactual model of causal judgment explains both the recency and the primacy effect. In line with the predictions of our extended counterfactual model, we also find that, regardless of causal structure, people tend to imagine the counterfactual alternative to the more recent event rather than to the earlier one. Moreover, manipulating this tendency affects causal judgments in the ways predicted by this extended model: asking participants to imagine the counterfactual alternative to the earlier event weakens the interaction between recency and causal structure, and asking participants to imagine the counterfactual alternative to the more recent event strengthens the interaction between recency and causal structure. We discuss these results in relation to work on counterfactual thinking, causal modeling, and late-preemption. (shrink)

People generally accept that there is causation by omission—that the omission of some events cause some related events. But this acceptance elicits the selection problem, or the difficulty of explaining the selection of a particular omissive cause or class of causes from the causal conditions. Some theorists contend that dependence theories of causation cannot resolve this problem. In this paper, we argue that the appeal to norms adequately resolves the selection problem for dependence theories, and we provide novel experimental evidence (...) for it. (shrink)

People’s causal judgments are susceptible to the action effect, whereby they judge actions to be more causal than inactions. We offer a new explanation for this effect, the counterfactual explanation: people judge actions to be more causal than inactions because they are more inclined to consider the counterfactual alternatives to actions than to consider counterfactual alternatives to inactions. Experiment 1a conceptually replicates the original action effect for causal judgments. Experiment 1b confirms a novel prediction of the new explanation, the reverse (...) action effect, in which people judge inactions to be more causal than actions in overdetermination cases. Experiment 2 directly compares the two effects in joint-causation and overdetermination scenarios and conceptually replicates them with new scenarios. Taken together, these studies provide support for the new counterfactual explanation for the action effect in causal judgment. (shrink)

Recent work in psychology and experimental philosophy has shown that judgments of actual causation are often influenced by consideration of defaults, typicality, and normality. A number of philosophers and computer scientists have also suggested that an appeal to such factors can help deal with problems facing existing accounts of actual causation. This article develops a flexible formal framework for incorporating defaults, typicality, and normality into an account of actual causation. The resulting account takes actual causation to be both graded and (...) comparative. We then show how our account would handle a number of standard cases. 1 Introduction2 Causal Models3 The HP Definition of Actual Causation4 The Problem of Isomorphism5 Defaults, Typicality, and Normality6 Extended Causal Models7 Examples7.1 Omissions7.2 Knobe effects7.3 Causes versus background conditions7.4 Bogus prevention7.5 Causal chains7.6 Legal doctrines of intervening causes7.7 Pre-emption and short circuits8 Conclusion. (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)

This paper outlines a theory and computer implementation of causal meanings and reasoning. The meanings depend on possibilities, and there are four weak causal relations: A causes B, A prevents B, A allows B, and A allows not‐B, and two stronger relations of cause and prevention. Thus, A causes B corresponds to three possibilities: A and B, not‐A and B, and not‐A and not‐B, with the temporal constraint that B does not precede A; and the stronger relation conveys only the (...) first and last of these possibilities. Individuals represent these relations in mental models of what is true in the various possibilities. The theory predicts a number of phenomena, and, contrary to many accounts, it implies that the meaning of causation is not probabilistic, differs from the meaning of enabling conditions, and does not depend on causal powers or mechanisms. The theory also implies that causal deductions do not depend on schemas or rules. (shrink)

This paper examines Wesley Salmon's "process" theory of causality, arguing in particular that there are four areas of inadequacy. These are that the theory is circular, that it is too vague at a crucial point, that statistical forks do not serve their intended purpose, and that Salmon has not adequately demonstrated that the theory avoids Hume's strictures about "hidden powers". A new theory is suggested, based on "conserved quantities", which fulfills Salmon's broad objectives, and which avoids the problems discussed.

In many people, caffeine causes slight muscle tremors, particularly in their hands. In general, the Caffeine → Muscle Tremors causal connection is a noisy one: someone can drink coffee and experience no hand shaking, and there are many other factors that can lead to muscle tremors. Now suppose that Jane drinks several cups of coffee and then notices that her hands are trembling; an obvious question is: did this instance of coffee drinking cause this instance of hand-trembling? Structurally similar questions (...) arise throughout everyday life: Did this pressing of the ‘k’ key cause this change in the pixels on the computer monitor? Did these episodes of smoking cause this lung cancer? Did this studying cause this test score? And so on. These questions all ask about singular causation in a particular situation, in contrast with general causation across multiple cases. They are thus particularly salient in situations in which we care about that specific case, as in many legal contexts, social interactions, physical explanations of anomalous events, and more. (shrink)

It has long been known that people’s causal judgments can have an impact on their moral judgments. To take a simple example, if people conclude that a behavior caused the death of ten innocent children, they will therefore be inclined to regard the behavior itself as morally wrong. So far, none of this should come as any surprise. But recent experimental work points to the existence of a second, and more surprising, aspect of the relationship between causal judgment and moral (...) judgment. It appears that the relationship can sometimes go in the opposite direction. That is, it appears that our moral judgments can sometimes impact our causal judgments. (Hence, we might first determine that a behavior is morally wrong and then, on that basis, arrive at the conclusion that it was the cause of various outcomes.). (shrink)

People often reason about omissions. One line of research shows that people can distinguish between the semantics of omissive causes and omissive enabling conditions: for instance, not flunking out of college enabled you (but didn’t cause you) to graduate. Another line of work shows that people rely on the normative status of omissive events in inferring their causal role: if the outcome came about because the omission violated some norm, reasoners are more likely to select that omission as a cause. (...) We designed a novel paradigm that tests how norms interact with the semantics of omissive enabling conditions. The paradigm concerns the circuitry of a mechanical device that plays music. Two experiments used the paradigm to stipulate norms and present a distinct set of possibilities to participants. Participants chose which causal verb best described the operations of the machine. The studies revealed that participants’ responses are best predicted by their tendency to consider the semantics of omissive relations. In contrast, norms had little to no effect in participants’ responses. We conclude by marshaling the evidence and considering what role norms may play in people’s understanding of omissions. (shrink)