This paper provides a general introduction to the use of causal models in the metaphysics of causation, specifically structural equation models and directed acyclic graphs. It reviews the formal framework, lays out a method of interpretation capable of representing different underlying metaphysical relations, and describes the use of these models in analyzing causation.

We define a formal semantics of conditionals based on _normatively ideal worlds_. Such worlds are described informally by Armgardt (Gabbay D, Magnani L, Park W, Pietarinen A-V (eds) Natural arguments: a tribute to john woods, College Publications, London, pp 699–708, 2018) to address well-known problems of the counterfactual approach to causation. Drawing on Armgardt’s proposal, we use iterated conditionals in order to analyse causal relations in scenarios of multi-agent interaction. This results in a refined counterfactual approach to causal responsibility in (...) legal contexts, which solves overdetermination problems in an intuitively accessible manner. (shrink)

We aim to devise a Ramsey test analysis of actual causation. Our method is to define a strengthened Ramsey test for causal models. Unlike the accounts of Halpern and Pearl ([2005]) and Halpern ([2015]), the resulting analysis deals satisfactorily with both over- determination and conjunctive scenarios.

In this paper, we propose a regularity theory of causation. The theory aims to be reductive and to align with our pre‐theoretic understanding of the causal relation. We show that our theory can account for a wide range of causal scenarios, including isomorphic scenarios, omissions, and scenarios which suggest that causation is not transitive.

When evaluating theories of causation, intuitions should not play a decisive role, not even intuitions in flawlessly-designed thought experiments. Indeed, no coherent theory of causation can respect the typical person’s intuitions in redundancy (pre-emption) thought experiments, without disrespecting their intuitions in threat-and-saviour (switching/short-circuit) thought experiments. I provide a deductively sound argument for these claims. Amazingly, this argument assumes absolutely nothing about the nature of causation. I also provide a second argument, whose conclusion is even stronger: the typical person’s causal intuitions (...) are thoroughly unreliable. This argument proceeds by raising the neglected question: in what respects is information about intermediate and enabling variables relevant to reliable causal judgment? (shrink)

In many spheres, the law takes the legal concept of causation to correspond to the folk concept (the correspondence assumption). Courts, including the US Supreme Court, tend to insist on the "common understanding" and that which is "natural to say" (Burrage v. United States) when it comes to expressions relating to causation, and frequently refuse to clarify the expression to juries. As recent work in psychology and experimental philosophy has uncovered, lay attributions of causation are susceptible to a great number (...) of unexpected factors, some of which seem rather peripheral to causation. One of those is the norm effect (Knobe & Fraser, 2008): Agents who, in acting as they do, break a salient norm, are more likely to be considered as having caused a certain consequence than when they do not violate a norm. According to some (e.g., Alicke, 1992) this constitutes a bias. According to others (e.g., Sytsma, 2020), the folk concept of causation is sensitive to normative factors, and there’s nothing wrong with that. In this paper, we explore the question whether the norm effect should be considered a bias from the legal perspective on the one hand, and from the psychological perspective on the other. To do this, we test whether norms which are nonpertinent to the consequences or outright silly also impact causation judgements. The data from two preregistered experiments (total N=593) clearly show they do. This, we argue, makes the bias interpretation plausible from the psychological perspective, and both plausible and problematic from the legal perspective. It also shows that the law should abstain from unreflectively assuming conceptual correspondence between legal and ordinary language concepts. (shrink)

How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as being characterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in 'objective science', Sprenger and Hartmann explain the value of convincing evidence in terms (...) of a cycle of variations on the theme of representing rational degrees of belief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference—the leading theory of rationality in social science—with the practice of 21st century science. Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention to methodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners. (shrink)

Halpern and Hitchcock appealed to the normality of witness worlds to solve the problem of isomorphism in the Halpern-Pearl definition of actual causality. This paper first proposes a new isomorphism counterexample, called “bogus permission,” to show that their approach is unsuccessful. Then, to solve the problem of isomorphism, I propose a new improvement over the Halpern-Pearl definition by introducing default worlds. Finally, I demonstrate that my new definition can resolve more potential counterexamples than similar approaches in the current literature, including (...) the Lewisian causal dependence, Menziesian causal dependence, and modified version of the Halpern-Pearl definition. Some other advantages of my definition are also discussed. (shrink)

Incorporating normality ascriptions into counterfactual theories of causation was supposed to handle isomorphs. It doesn’t—conjoining isomorphs can produce cases that such ascriptions cannot resolve.

It has recently been argued that normative considerations play an important role in causal cognition. For instance, when an agent violates a moral rule and thereby produces a negative outcome, she will be judged to be much more of a cause of the outcome, compared to someone who performed the same action but did not violate a norm. While there is a substantial amount of evidence reporting these effects, it is still a matter of debate how this evidence is to (...) be interpreted. In this paper, we engage with the three most influential classes of explanations, namely, (a) the Norm‐Sensitive Cognitive Process View, (b) the Normative Concept View, and (c) the Pragmatics View. We will outline how these theories explain the empirical results and in what ways they differ. We conclude with a reflection on how well these strategies do overall and what questions they still leave unanswered. (shrink)

Some have argued that our intuitive reactions to a number of cases of moral responsibility can only be preserved at the expense of a unified account of moral responsibility for acts and omissions. I argue against this conclusion, proposing that a plausible condition on responsibility, the Causal Condition can, when properly elaborated, justify the relevant intuitive data.

Markus (2021) argues that the causal modelling frameworks of Pearl and Rubin are not ‘strongly equivalent’, in the sense of saying ‘the same thing in different ways’. Here I rebut Markus’ arguments against strong equivalence. The differences between the frameworks are best illuminated not by appeal to their causal semantics, but rather reflect pragmatic modelling choices.

Absences pose a dilemma for theories of causation. Allowing them to be causes seems to make theories too permissive (Lewis, 2000). Banning them from being causes seems to make theories too restrictive (Schaffer, 2000, 2004). An increasingly popular approach to this dilemma is to acknowledge that norms can affect which absences count as causes (e.g., Thomson, 2003; McGrath, 2005; Henne et al., 2017; Willemsen, 2018). In this article, I distinguish between two influential implementations of such ‘abnormality’ approaches and argue that (...) so-called ‘double-prevention mechanisms’ provide counterexamples against both. (shrink)

There is ample evidence that violations of injunctive norms impact ordinary causal attributions. This has struck some as deeply surprising, taking the ordinary concept of causation to be purely descriptive. Our explanation of the findings—the responsibility view—rejects this: we contend that the concept is in fact partly normative, being akin to concepts like responsibility and accountability. Based on this account, we predicted a very different pattern of results for causal attributions when an agent violates a statistical norm. And this pattern (...) has been borne out by the data. These predictions were based on the responsibility attributions that we would make. In this paper, I extend these previous findings, testing responsibility attributions. The results confirm the basis of our predictions, showing the same pattern of effects previously found for causal attributions for both injunctive norms and statistical norms. In fact, the results for responsibility attributions are not statistically significantly different from those previously found for causal attributions. I argue that this close correspondence lends further credence to the responsibility view over competing explanations of the impact of norms on causal attributions. (shrink)

I argue that there are some causal relata for which it is indeterminate whether one caused the other. Positing indeterminacy in causation helps us defend contested principles in the logic of causation and makes possible new ways of thinking about the theoretical impact of symmetric causal overdetermination. I close by discussing amendments of current theories of causation that would help explain causal indeterminacy.

I argue that there are some causal relata for which it is indeterminate whether one caused the other. Positing indeterminacy in causation helps us defend contested principles in the logic of causation and makes possible new ways of thinking about the theoretical impact of symmetric causal overdetermination. I close by discussing amendments of current theories of causation that would help explain causal indeterminacy.

I argue that there are some causal relata for which it is indeterminate whether one caused the other. Positing indeterminacy in causation helps us defend contested principles in the logic of causation and makes possible new ways of thinking about the theoretical impact of symmetric causal overdetermination. I close by discussing amendments of current theories of causation that would help explain causal indeterminacy.

Causal selection and priority are at the heart of discussions of the causal parity thesis, which says that all causes of a given effect are on a par, and that any justified priority assigned to a given cause results from causal explanatory interests. In theories of causation that provide necessary and sufficient conditions for the truth of causal claims, status as cause is an either/or issue: either a given cause satisfies the conditions or it does not. Consequently, assessments of causal (...) parity and priority require more resources, which can either be additional or part of the causal analysis itself. While adding resources in terms of a theory of causal explanation has been standard, here we develop a unified conceptual analysis that includes a range of different precise causal concepts that allows for assessments of causal priority in terms of different kinds of causal relevance. (shrink)

Causal queries about singular cases, which inquire whether specific events were causally connected, are prevalent in daily life and important in professional disciplines such as the law, medicine, or engineering. Because causal links cannot be directly observed, singular causation judgments require an assessment of whether a co‐occurrence of two events c and e was causal or simply coincidental. How can this decision be made? Building on previous work by Cheng and Novick (2005) and Stephan and Waldmann (2018), we propose a (...) computational model that combines information about the causal strengths of the potential causes with information about their temporal relations to derive answers to singular causation queries. The relative causal strengths of the potential cause factors are relevant because weak causes are more likely to fail to generate effects than strong causes. But even a strong cause factor does not necessarily need to be causal in a singular case because it could have been preempted by an alternative cause. We here show how information about causal strength and about two different temporal parameters, the potential causes' onset times and their causal latencies, can be formalized and integrated into a computational account of singular causation. Four experiments are presented in which we tested the validity of the model. The results showed that people integrate the different types of information as predicted by the new model. (shrink)

Recently, there has been a large amount of support for the idea that causal claims can be sensitive to normative considerations. Previous work has focused on the concept of actual causation, defending the claim that whether or not some token event c is a cause of another token event e is influenced by both statistical and prescriptive norms. I focus on the policy debate surrounding alternative energies, and use the causal modelling framework to show that in this context, people’s normative (...) commitments don’t just affect the causal claims they are willing to endorse, but also their understanding of the causal structure. In the context of the alternative energy debate, normative considerations affect our understanding of the causal structure by influencing our judgements about which variables should be held fixed, and therefore which variables should be relegated to the background of a causal model. In cases of extreme disagreement, normative commitments can also affect which causal structure we think should be instantiated. Thus, focusing on a new context has revealed a previously unexplored sense in which normative factors are incorporated into causal reasoning. (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)

How do we determine whether some candidate causal factor is an actual cause of some particular outcome? Many philosophers have wanted a view of actual causation which fits with folk intuitions of actual causation and those who wish to depart from folk intuitions of actual causation are often charged with the task of providing a plausible account of just how and where the folk have gone wrong. In this paper, I provide a range of empirical evidence aimed at showing just (...) how and where the folk go wrong in determining whether an actual causal relation obtains. The evidence suggests that folk intuitions of actual causation are generated by two epistemically defective processes. I situate the empirical evidence within a background discussion of debunking, arguing for a two-pronged debunking explanation of folk intuitions of actual causation. I conclude that those who wish to depart from folk intuitions of actual causation should not be compelled to square their account of actual causation with the verdicts of the folk. In the dispute over actual causation, folk intuitions deserve to be rejected. (shrink)

Many philosophers maintain that causation is to be explicated in terms of a kind of dependence between cause and effect. These “dependence” theories are opposed by “production” accounts which hold that there is some more fundamental causal “oomph”. A wide range of experimental research on everyday causal judgments seems to indicate that ordinary people operate primarily with a dependence-based notion of causation. For example, people tend to say that absences and double preventers are causes. We argue that the impression that (...) commonsense causal discourse is largely dependence-based is the result of focusing on a very narrow class of causal verbs. Almost all of the vignette-based experimental work on causal judgment has been prosecuted using the word “cause”. But much ordinary causal discourse involves special causal verbs, such as “burn” and “crack”. We find that these verbs display a quite different pattern from the verb “cause”. For instance, for absences and double preventers (Studies 1-3), we find that while people are inclined to say that X caused Y to burn, turn, crack or start, they are less inclined to think that X burned, turned, cracked or started Y. In Study 4, we find that for chains involving a distal and proximal event, people are inclined to say that the distal event is not a special cause of the outcome, though it is a “cause” of the outcome. Together, we find a surprising double dissociation between “cause” and a stock of special causal verbs. We conclude by suggesting that much commonsense causal judgment, which heavily trades in special causal verbs, might be better captured by production-based accounts of causation. (shrink)

Conditionalization is a norm that governs the rational reallocation of credence. I distinguish between factive and non-factive formulations of Conditionalization. Factive formulations assume that the conditioning proposition is true. Non-factive formulations allow that the conditioning proposition may be false. I argue that non-factive formulations provide a better foundation for philosophical and scientific applications of Bayesian decision theory. I furthermore argue that previous formulations of Conditionalization, factive and non-factive alike, have almost universally ignored, downplayed, or mishandled a crucial causal aspect of (...) Conditionalization. To formulate Conditionalization adequately, one must explicitly address the causal structure of the transition from old credences to new credences. I offer a formulation of Conditionalization that takes these considerations into account, and I compare my preferred formulation with some prominent formulations found in the literature. (shrink)

Frankfurt‐style cases suggest that an agent's moral responsibility for an action supervenes on the causal history of that action—at least when epistemic considerations are held constant. However, PAP‐style cases suggest that moral responsibility does not supervene on causal history, for judgments concerning an agent's responsibility for an action are also sensitive to the presence of alternative—and causally idle—possibilities. I appeal to the causal modeling tradition and the definitions of actual causation that derive therefrom in an attempt to resolve this contradiction. (...) I show that even the weakest definitions of actual causation proposed in the literature establish that some PAP‐style cases constitute genuine counterexamples to the supervenience thesis. I consider several responses to these counterexamples on behalf of the defenders of supervenience and show that they fail. Our best current thinking on causation thus appears to be inconsistent with an intuitive and widely held claim concerning the nature of moral responsibility. (shrink)

Past work has demonstrated that people’s moral judgments can influence their judgments in a number of domains that might seem to involve straightforward matters of fact, including judgments about freedom, causation, the doing/allowing distinction, and intentional action. The present studies explore whether the effect of morality in these four domains can be explained by changes in the relevance of alternative possibilities. More precisely, we propose that moral judgment influences the degree to which people regard certain alternative possibilities as relevant, which (...) in turn impacts intuitions about freedom, causation, doing/allowing, and intentional action. Employing the stimuli used in previous research, Studies 1a, 2a, 3a, and 4a show that the relevance of alternatives is influenced by moral judgments and mediates the impact of morality on non-moral judgments. Studies 1b, 2b, 3b, and 4b then provide direct empirical evidence for the link between the relevance of alternatives and judgments in these four domains by manipulating (rather than measuring) the relevance of alternative possibilities. Lastly, Study 5 demonstrates that the critical mechanism is not whether alternative possibilities are considered, but whether they are regarded as relevant. These studies support a unified framework for understanding the impact of morality across these very different kinds of judgments. (shrink)

A series of recent studies have explored the impact of people's judgments regarding physical law, morality, and probability. Surprisingly, such studies indicate that these three apparently unrelated types of judgments often have precisely the same impact. We argue that these findings provide evidence for a more general hypothesis about the kind of cognition people use to think about possibilities. Specifically, we suggest that this aspect of people's cognition is best understood using an idea developed within work in the formal semantics (...) tradition, namely the notion of modality. On the view we propose, people may have separate representations for physical, moral and probabilistic considerations, but they also integrate these various considerations into a unified representation of modality. (shrink)

Pre-emption cases have been taken by almost everyone to imply the unviability of the simple counterfactual theory of causation. Yet there is ample motivation from scientific practice to endorse a simple version of the theory if we can. There is a way in which a simple counterfactual theory, at least if understood contrastively, can be supported even while acknowledging that intuition goes firmly against it in pre-emption cases—or rather, only in some of those cases. For I present several new pre-emption (...) cases in which causal intuition does not go against the counterfactual theory, a fact that has been verified experimentally. I suggest an account of framing effects that can square the circle. Crucially, this account offers hope of theoretical salvation—but only to the counterfactual theory of causation, not to others. Again, there is (admittedly only preliminary) experimental support for this account. (shrink)

This paper proposes a framework for representing in Bayesian terms the idea that analogical arguments of various degrees of strength may provide inductive support to yet untested scientific hypotheses. On this account, contextual information plays a crucial role in determining whether, and to what extent, a given similarity or dissimilarity between source and target may confirm an empirical hypothesis over a rival one. In addition to showing confirmation by analogy compatible with the adoption of a Bayesian standpoint, the proposal outlined (...) in this paper reveals a close agreement between the fulfillment of Hesse’s (Models and analogies in science, University of Notre Dame Press, 1963) criteria for analogical arguments capable of inductive support and the attribution of confirmatory power by the lights of Bayesian confirmation theory. In this sense, the Bayesian representation not only enriches a framework, Hesse’s, of enduring relevance for understanding scientific activity, but may offer something akin to a proof of concept of it. (shrink)

According to what I call theidentity view, omissions are actual events. For example, the nominal ‘Ali's non-jogging’ denotes whatever Ali is doing at the time she is said not to be jogging. Some have objected that omissions (and more generally absences) cannot be events, since the two do not have the same causal relations. I show how advocates of the identity view can offer a pragmatic account of the data the objection relies on.

Causal contextualism holds that sentences of the form ‘c causes e’ have context-sensitive truth-conditions. We consider four arguments invoked by Jonathan Schaffer in favor of this view. First, he argues that his brand of contextualism helps solve puzzles about transitivity. Second, he contends that how one describes the relata of the causal relation sometimes affects the truth of one’s claim. Third, Schaffer invokes the phenomenon of contrastive focus to conclude that causal statements implicitly designate salient alternatives to the cause and (...) effect. Fourth, he claims that the appropriateness of a causal statement depends on what is contextually taken for granted or made salient. We show that causal invariantism can explain these linguistic data at least as well as contextualism. We then argue that pace Schaffer, some causal sentences are always correct and can never be plausibly denied, regardless of the context. (shrink)

Rubin and Pearl offered approaches to causal effect estimation and Lewis and Pearl offered theories of counterfactual conditionals. Arguments offered by Pearl and his collaborators support a weak form of equivalence such that notation from the rival theory can be re-purposed to express Pearl’s theory in a way that is equivalent to Pearl’s theory expressed in its native notation. Nonetheless, the many fundamental differences between the theories rule out any stronger form of equivalence. A renewed emphasis on comparative research can (...) help to guide applications, further develop each theory, and better understand their relative strengths and weaknesses. (shrink)

In the last decade, several researchers have proposed theories of actual causation that make use of structural equations and directed graphs. Many of these researchers are committed to a widely-endorsed folk attribution desideratum, according to which an important constraint on the acceptability of a theory of actual causation is agreement between the deliverances of the theory with respect to specific cases and the reports of untutored individuals about those same cases. In the present article, we consider a small collection of (...) related theories of actual causation, including a purely structural theory and two theories that supplement the structural equations with considerations of defaults, typicality, and normality. We argue that each of these three theories are meant to satisfy the FAD, and then we present empirical evidence that they fail to do so for several variations on a simple scenario from the literature. Drawing on our previous work on the responsibility view of folk causal attribitons, we conclude by offering a solution that allows the latter two theories to satisfy the FAD for these cases. The solution is to give up on concerns with typicality and focus on injunctive norms in supplementing the graphical modeling machinery. (shrink)

Many theories of actual causation implicitly endorse the claim that if c is an actual cause of e, then either c causes e directly or every intermediary by which c indirectly causes e is itself both an actual cause of e and also an actual effect of c. We think this compositionality constraint is plausible. However, as we show, it is not always satisfied by the causal attributions ordinary people make. We conclude by considering what philosophers working on causation should (...) do when the deliverances of their theories diverge from what ordinary people say. (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)

People often think of objects teleologically. For instance, we might understand a hammer in terms of its purpose of driving in nails. But how should we understand teleological thinking in the first place? This paper separates mere teleology (simply ascribing a telos) and teleological explanation (thinking something is explained by its telos) by examining cases where an object was designed for one purpose but is now widely used for a different purpose. Across four experiments, we show that teleology judgments and (...) teleological explanation judgments are dissociable, and identify three factors that influenced teleology judgments (and one that did not). (shrink)

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)

Virtue Reliabilism holds that knowledge is a cognitive achievement—an epistemic success that is creditable to the cognitive abilities of the knowing subject. Beyond this consensus, there is much disagreement amongst proponents of virtue reliabilism about the conditions under which the credit-relation between an epistemic success and a person’s cognitive abilities holds. This paper aims to establish a new and attractive view of this crucial relation in terms of difference-making. We will argue that the resulting theory, Difference-Making Virtue Epistemology, can deal (...) with cases of epistemic luck and testimonial knowledge while revealing the common core of knowledge and other achievements. (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’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)

There have been several recent attempts to model ordinary intuitions about actual causation by combining a counterfactual definition of the causal relation with an abnormality-based account of causal judgments. In these models, the underlying psychological theory is that people automatically focus on abnormal events when judging the actual causes of an effect. This approach has enabled authors such as Halpern and Hitchcock to capture an impressive array of ordinary causal intuitions. However, in this paper I demonstrate how these abnormality-based accounts (...) still systematically fail to predict ordinary causal judgments in specific types of scenarios: those in which the effect is normal. I will argue that the reason for this is that the underlying psychological theory is wrong: the idea that intuitive actual causes are abnormal events is only partially correct. To model ordinary judgments more realistically, researchers working in this area must adopt a more plausible underlying psychological theory: the correspondence hypothesis about judgments of actual causation. One of the consequences of this correspondence hypothesis is that normal effects are judged to have normal causes. (shrink)