Causal claims are context sensitive. According to the old orthodoxy (Mackie 1974, Lewis 1986, inter alia), the context sensitivity of causal claims is all due to conversational pragmatics. According to the new contextualists (Hitchcock 1996, Woodward 2003, Maslen 2004, Menzies 2004, Schaffer 2005, and Hall ms), at least some of the context sensitivity of causal claims is semantic in nature. I want to discuss the prospects for causal contextualism, by asking why causal claims are context sensitive, what they are sensitive (...) to, and where they are sensitive to it. (shrink)

Humans often attribute the things that happen to one or another actual cause. In this chapter, we survey some recent philosophical and psychological research on causal attribution. We pay special attention to the relation between graphical causal modeling and theories of causal attribution. We think that the study of causal attribution is one place where formal and experimental techniques nicely complement one another.

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)

The well-known formal semantics of conditionals due to Stalnaker Studies in logical theory, Blackwell, Oxford, 1968), Lewis, and Gärdenfors The logic and 1140 epistemology of scientific change, North-Holland, Amsterdam, 1978, Knowledge in flux, MIT Press, Cambridge, 1988) all fail to distinguish between trivially and nontrivially true indicative conditionals. This problem has been addressed by Rott :345–370, 1986) in terms of a strengthened Ramsey Test. In this paper, we refine Rott’s strengthened Ramsey Test and the corresponding analysis of explanatory relations. We (...) show that our final analysis captures the presumed asymmetry between explanans and explanandum much better than Rott’s original analysis. (shrink)

In this paper, we analyse actual causation in terms of production. The latter concept is made precise by a strengthened Ramsey Test semantics of conditionals: \ iff, after suspending judgement about A and C, C is believed in the course of assuming A. This test allows us to verify or falsify that an event brings about another event. Complementing the concept of production by a weak condition of difference-making gives rise to a full-fledged analysis of causation.

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.

Philosophers have already recognized the importance of causal preemption involving “positive” events. First, preemption with positive events raises problems for counterfactual theories of causation. Second, theories of moral and legal responsibility rely heavily on the concept of causation, so accurately assessing responsibility in preemption cases requires correctly assessing their causal structure. However, philosophers have not discussed preemption involving “negative” events or omissions. This paper argues that cases of preemptive omissions exist and have important implications for theories of causation and for (...) moral and legal responsibility. Of theoretical importance, the alterations made to counterfactual theories of causation to address preemption with positive events do not seem to work for accommodating preemptive omissions. Of practical importance, there have been actual legal cases involving preemptive omissions, and at least one such case was, this paper contends, decided incorrectly on erroneous causal grounds. This paper identifies what must happen for preemptive omissions to obtain. It then argues for the existence of preemptive omissions by constructing a series of cases and drawing structural parallels between preemption cases with positive events and cases with omissions. It ultimately presents a formula for generating preemptive omissions and examines both why “traditional” methods of generating preemption fail for omissions and why the proposed method avoids such concerns. (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)

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.

Explanations are backed by many different relations: causation, grounding, and arguably others too. But why are these different relations capable of backing explanations? In virtue of what are they explanatory? In this paper, I propose and defend a monistic account of explanation-backing relations. On my account, there is a single relation which backs all cases of explanation, and which explains why those other relations are explanation-backing.

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.

Necessity and sufficiency are the building blocks of all successful explanations. Yet despite their importance, these notions have been conceptually underdeveloped and inconsistently applied in explainable artificial intelligence, a fast-growing research area that is so far lacking in firm theoretical foundations. In this article, an expanded version of a paper originally presented at the 37th Conference on Uncertainty in Artificial Intelligence, we attempt to fill this gap. Building on work in logic, probability, and causality, we establish the central role of (...) necessity and sufficiency in XAI, unifying seemingly disparate methods in a single formal framework. We propose a novel formulation of these concepts, and demonstrate its advantages over leading alternatives. We present a sound and complete algorithm for computing explanatory factors with respect to a given context and set of agentive preferences, allowing users to identify necessary and sufficient conditions for desired outcomes at minimal cost. Experiments on real and simulated data confirm our method’s competitive performance against state of the art XAI tools on a diverse array of tasks. (shrink)

A cause is proportional to its effect when, roughly speaking, it is at the right level of detail. There is a lively debate about whether proportionality is a necessary condition for causation. One of the main arguments against a proportionality constraint on causation is that many ordinary and seemingly perfectly acceptable causal claims cite causes that are not proportional to their effects. In this paper, I suggest that proponents of a proportionality constraint can respond to this objection by developing an (...) idea that is present in Yablo’s early work on proportionality, but which has strangely been ignored by both Yablo and others in the subsequent debate. My suggestion is that proportionality—and, indeed, causation itself—is relative to a domain of events. At the metaphysical level, this means that the causal relation has an extra relatum—namely, a domain of events. At the level of language, it introduces a new way in which causal claims are context-sensitive: what is expressed by a causal claim depends on the contextually relevant domain of events. As I argue, this suggestion allows us to accommodate the truth of ordinary causal claims while extending the explanatory benefits of a proportionality constraint. (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.

The concept of causation plays a central role in many philosophical theories, and yet no account of causation has gained widespread acceptance among those who have investigated its foundations. Theories based on laws, counterfactuals, physical processes, and probabilistic dependence and independence relations (the list is by no means exhaustive) have all received detailed treatment in recent years---{}and, while no account has been entirely successful, it is generally agreed that the concept has been greatly clari{}ed by the attempts. In this magni{}cent (...) book, Woodward aims to give a uni{}ed account of causation and causal explanation in terms of the notion of a manipulation (or intervention, terms which can be read interchangeably). Not only does he produce in my view the most illuminating and comprehensive account of causation on o{}er, his theory also opens a great many avenues for future work in the area, and has rami{}cations for many other areas of philosophy. Making Things Happen ought to be of interest not only to philosophers of causation and philosophers of science, but to any philosopher whose concerns involve assumptions about the nature of causation, laws, or explanation. (shrink)

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)

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)

Grounding is often glossed as metaphysical causation, yet no current theory of grounding looks remotely like a plausible treatment of causation. I propose to take the analogy between grounding and causation seriously, by providing an account of grounding in the image of causation, on the template of structural equation models for causation.

Causation is widely assumed to be a binary relation: c causes e. I will argue that causation is a quaternary, contrastive relation: c rather than C* causes e rather than E*, where C* and E* are nonempty sets of contrast events. Or at least, I will argue that treating causation as contrastive helps resolve some paradoxes.

Bayes nets are formal representations of causal systems that many psychologists have claimed as plausible mental representations. One purported advantage of Bayes nets is that they may provide a theory of counterfactual conditionals, such as If Calvin had been at the party, Miriam would have left early. This article compares two proposed Bayes net theories as models of people's understanding of counterfactuals. Experiments 1-3 show that neither theory makes correct predictions about backtracking counterfactuals (in which the event of the if-clause (...) occurs after the event of the then-clause), and Experiment 4 shows the same is true of forward counterfactuals. An amended version of one of the approaches, however, can provide a more accurate account of these data. (shrink)

According to James Woodward’s influential interventionist account of causation, X is a cause of Y iff, roughly, there is a possible intervention on X that changes Y. Woodward requires that interventions be merely logically possible. I will argue for two claims against this modal character of interventions: First, merely logically possible interventions are dispensable for the semantic project of providing an account of the meaning of causal statements. If interventions are indeed dispensable, the interventionist theory collapses into a counterfactual theory (...) of causation. Thus, the interventionist theory is not tenable as a theory of causation in its own right. Second, if one maintains that merely logically possible interventions are indispensable, then interventions with this modal character lead to the fatal result that interventionist counterfactuals are evaluated inadequately. Consequently, interventionists offer an inadequate theory of causation. I suggest that if we are concerned with explicating causal concepts and stating the truth-conditions of causal claims we best get rid of Woodwardian interventions. (shrink)

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. (shrink)

This paper aims to bridge philosophical and psychological research on causation, counterfactual thought, and the problem of backtracking. Counterfactual approaches to causation such as that by Lewis have ruled out backtracking, while on prominent models of causal inference interventionist counterfactuals do not backtrack. However, on various formal models, certain backtracking counterfactuals end up being true, and psychological evidence shows that people do sometimes backtrack when answering counterfactual questions in causal contexts. On the basis of psychological research, I argue that while (...) ordinarily both kinds of counterfactuals may be employed, non-backtracking counterfactuals are more easily used in causal inference because they are consistent with temporal order information embedded in the mental simulation heuristic, and they match reasoners’ experience of causation. While this approach is incompatible with the ambitions of counterfactual theories that seek to establish the non-backtracking interpretation as the only legitimate one, it can provide support for perspectival views on causation and open further inquiry on the functions of causal and counterfactual thought in the context of causal models. (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)

Partial explanations are everywhere. That is, explanations citing causes that explain some but not all of an effect are ubiquitous across science, and these in turn rely on the notion of degree of explanation. I argue that current accounts are seriously deficient. In particular, they do not incorporate adequately the way in which a cause’s explanatory importance varies with choice of explanandum. Using influential recent contrastive theories, I develop quantitative definitions that remedy this lacuna, and relate it to existing measures (...) of degree of causation. Among other things, this reveals the precise role here of chance, as well as bearing on the relation between causal explanation and causation itself. (shrink)

Judea Pearl (2000) has recently advanced a theory of token causation using his structural equations approach. This paper examines some counterexamples to Pearl's theory, and argues that the theory can be modified in a natural way to overcome them.

It is natural to think of causes as difference-makers. What exact difference causes make, however, is an open question. In this paper, I argue that the right way of understanding difference-making is in terms of causal processes: causes make a difference to a causal process that leads to the effect. I will show that this way of understanding difference-making nicely captures the distinction between causing an outcome and helping determine how the outcome happens and, thus, explains why causation is not (...) transitive. Moreover, the theory handles tricky cases that are problematic for competing accounts of difference-making. (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)

Several prominent, contemporary theories of actual causation maintain that in order for something to count as an actual cause (in the circumstances) of some known effect, the potential cause must be a difference-maker with respect to the effect in some restricted range of circumstances. Although the theories disagree about how to restrict the range of circumstances that must be considered in deciding whether something counts as an actual cause of a known effect, the theories agree that at least some counterfactual (...) circumstances must be considered. I argue that the theories are still too permissive in the range of counterfactual circumstances they admit for consideration, and I present simple counter-examples that make use of this overpermissiveness. (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)

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)

Plural definite descriptions across many languages display two well-known properties. First, they can give rise to so-called non-maximal readings, in the sense that they ‘allow for exceptions’. Second, while they tend to have a quasi-universal quantificational force in affirmative sentences, they tend to be interpreted existentially in the scope of negation. Building on previous works, we offer a theory in which sentences containing plural definite expressions trigger a family of possible interpretations, and where general principles of language use account for (...) their interpretation in various contexts and syntactic environments. Our theory solves a number of problems that these previous works encounter, and has broader empirical coverage in that it offers a precise analysis for sentences that display complex interactions between plural definites, quantifiers and bound variables, as well as for cases involving non-distributive predicates. The resulting proposal is briefly compared with an alternative proposal by Križ, which has similar coverage but is based on a very different architecture and sometimes makes subtly different predictions. (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)

Much of the modern philosophy of causation has been governed by two ideas: (i) causes make their effects inevitable; (ii) a cause is something that makes a difference to whether its effect occurs. I focus on explaining the origin of idea (ii) and its connection to (i). On my view, the frequent attempts to turn (ii) into an analysis of causation are wrongheaded. Patterns of difference-making aren't what makes causal claims true. They merely provide a useful test for causal claims. (...) Moreover, what justifies us in using them as a test is idea (i). That's how (i) and (ii) are connected. (shrink)

One of the most popular arguments in favor of dualism is the zombie-conceivability argument. It is often argued that the possibility of zombies would entail that mental properties are epiphenomenal. This paper attempts to defuse the argument, offering a model of dualist mental causation which can serve as a basis for a modified, interactionist-friendly zombie argument.

Recently, there have been several attempts to generalize the counterfactual theory of causal explanations to mathematical explanations. The central idea of these attempts is to use conditionals whose antecedents express a mathematical impossibility. Such countermathematical conditionals are plugged into the explanatory scheme of the counterfactual theory and—so is the hope—capture mathematical explanations. Here, I dash the hope that countermathematical explanations simply parallel counterfactual explanations. In particular, I show that explanations based on countermathematicals are susceptible to three problems counterfactual explanations do (...) not face. These problems seriously challenge the prospects for a counterfactual theory of explanation that is meant to cover mathematical explanations. (shrink)

John Campbell has claimed that the interventionist account of causation must be amended if it is to be applied to causation in psychology. The problem, he argues, is that it follows from the so-called ‘surgical’ constraint that intervening on psychological states requires the suspension of the agent’s rational autonomy. In this paper, I argue that the problem Campbell identifies is in fact an instance of a wider problem for interventionism, extending beyond psychology, which I call the problem of ‘abrupt transitions’. (...) I then defend a solution to the problem, which replaces the surgical constraint with a weaker constraint on interventions that nevertheless does all the work the surgical constraint was designed to do. I conclude by exploring some interesting consequences of this weaker constraint for causation in psychology. (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)

Recent accounts of actual causation are stated in terms of extended causal models. These extended causal models contain two elements representing two seemingly distinct modalities. The first element are structural equations which represent the or mechanisms of the model, just as ordinary causal models do. The second element are ranking functions which represent normality or typicality. The aim of this paper is to show that these two modalities can be unified. I do so by formulating two constraints under which extended (...) causal models with their two modalities can be subsumed under so called which contain just one modality. These two constraints will be formally precise versions of Lewissystem of weights or priorities” governing overall similarity between possible worlds. (shrink)

In this paper I will argue that what makes our ordinary judgements about token causation true can be explicated in terms of interferences into quasi-inertial processes. These interferences and quasi-inertial processes can in turn be fully explicated in scientific terms. In this sense the account presented here is reductive. I will furthermore argue that this version of a process-theory of causation can deal with the traditional problems that process theories have to face, such as the problem of misconnection and the (...) problem of disconnection as well as with a problem concerning the mis-classification of pre-emption cases. (shrink)

Jonathan Schaffer introduced a new type of causal structure called 'trumping'. According to Schaffer, trumping is a species of causal preemption. Both Schaffer and I have argued that causation has a contrastive structure. In this paper, I analyze the structure of trumping cases from the perspective of contrastive causation, and argue that the case is much more complex than it first appears. Nonetheless, there is little reason to regard trumping as a species of causal preemption.

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)

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)

This paper presents an attempt to integrate theories of causal processes—of the kind developed by Wesley Salmon and Phil Dowe—into a theory of causal models using Bayesian networks. We suggest that arcs in causal models must correspond to possible causal processes. Moreover, we suggest that when processes are rendered physically impossible by what occurs on distinct paths, the original model must be restricted by removing the relevant arc. These two techniques suffice to explain cases of late preëmption and other cases (...) that have proved problematic for causal models. (shrink)

Structural equations have become increasingly popular in recent years as tools for understanding causation. But standard structural equations approaches to causation face deep problems. The most philosophically interesting of these consists in their failure to incorporate a distinction between default states of an object or system, and deviations therefrom. Exploring this problem, and how to fix it, helps to illuminate the central role this distinction plays in our causal thinking.

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)