We propose a new definition of actual causes, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficulties in the traditional account.

This paper explains what it is to believe something for a reason. My thesis is that you believe something for a reason just in case the reason non-deviantly causes your belief. In the course of arguing for my thesis, I present a new argument that reasons are causes, and offer an informative account of causal non-deviance.

Questions about the metaphysics of causation may be usefully divided as follows. First, there are questions about the nature of the causal relata, including (1.1) whether they are in spacetime immanence), (1.2) how fine grained they are individuation), and (1.3) how many there are adicity). Second, there are questions about the metaphysics of the causal relation, including (2.1) what is the difference between causally related and causally unrelated sequences connection), (2.2) what is the difference between sequences related as cause to (...) effect, and those related as effect to cause or as joint effects of a common cause direction), and (2.3) what is the difference between sequences involving the cause, and those involving mere conditions selection). (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.

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing (...) justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. (shrink)

According to orthodoxy, the most fundamental kind of causation involves one event causing another event. I argue against this event‐causal view. Instead, the most fundamental kind of causation is thing causation, which involves a thing causing a thing to do something. Event causation is reducible to thing causation, but thing causation is not reducible to event causation, because event causation cannot accommodate cases of fine‐grained causation. I defend my view from objections, including C. D. Broad's influential “timing” argument, and I (...) conclude with implications for agent‐causal theories of free will. (shrink)

The standard counterexamples to David Lewis’s account of intrinsicality involve two sorts of properties: identity properties and necessary properties. Proponents of the account have attempted to deflect these counterexamples in a number of ways. This paper argues that none of these moves are legitimate. Furthermore, this paper argues that no account along the lines of Lewis’s can succeed, for an adequate account of intrinsicality must be sensitive to hyperintensional distinctions among properties.

Omissions – any events, actions, or things that do not occur – are central to numerous debates in causation and ethics. This article surveys views on what omissions are, whether they are causally efficacious, and how they ground moral responsibility.

The basic idea of counterfactual theories of causation is that the meaning of causal claims can be explained in terms of counterfactual conditionals of the form “If A had not occurred, C would not have occurred”. While counterfactual analyses have been given of type-causal concepts, most counterfactual analyses have focused on singular causal or token-causal claims of the form “event c caused event e”. Analyses of token-causation have become popular in the last thirty years, especially since the development in the (...) 1970's of possible world semantics for counterfactuals. The best known counterfactual analysis of causation is David Lewis's (1973b) theory. However, intense discussion over thirty years has cast doubt on the adequacy of any simple analysis of singular causation in terms of counterfactuals. Recent years have seen a proliferation of different refinements of the basic idea to achieve a closer match with commonsense judgements about causation. (shrink)

This paper argues that non-identity actions are wrong because they _cause_ harm to people. While non-identity actions also typically benefit people, failure to act would similarly benefit someone, so considerations of benefit are ineligible to justify the harm. However, in some non-identity cases, failure to act would not benefit anyone: cases where one is choosing whether to procreate at all. These are the _hard_ non-identity cases. Not all "different-number" cases are hard. In some cases, we don't know whether acting would (...) result in more or fewer people; this paper argues that this _epistemic_ factor makes acting in these cases wrong. (shrink)

We offer a critical assessment of the “exclusion argument” against free will, which may be summarized by the slogan: “My brain made me do it, therefore I couldn't have been free”. While the exclusion argument has received much attention in debates about mental causation (“could my mental states ever cause my actions?”), it is seldom discussed in relation to free will. However, the argument informally underlies many neuroscientific discussions of free will, especially the claim that advances in neuroscience seriously challenge (...) our belief in free will. We introduce two distinct versions of the argument, discuss several unsuccessful responses to it, and then present our preferred response. This involves showing that a key premise – the “exclusion principle” – is false under what we take to be the most natural account of causation in the context of agency: the difference-making account. We finally revisit the debate about neuroscience and free will. (shrink)

Most philosophical accounts of causation take causal relations to obtain between individuals and events in virtue of nomological relations between properties of these individuals and events. Such views fail to take into account the consequences of the fact that in general the properties of individuals and events will depend upon mechanisms that realize those properties. In this paper I attempt to rectify this failure, and in so doing to provide an account of the causal relevance of higher-level properties. I do (...) this by critiquing one prominent model of higher-level properties—Kim’s functional model of reduction—and contrasting it with a mechanistic approach to higher-level properties and causation. (shrink)

Defenders of pragmatic encroachment in epistemology (or what I call practicalism) need to address two main problems. First, the view seems to imply, absurdly, that knowledge can come and go quite easily—in particular, that it might come and go along with our variable practical interests. We can call this the stability problem. Second, there seems to be no fully satisfying way of explaining whose practical interests matter. We can call this the “whose stakes?” problem. I argue that both problems can (...) be addressed in roughly the same terms. More exactly, I argue that by first clarifying the whose stakes? problem an answer to the stability problem naturally falls out. (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)

“Probabilistic Causation” designates a group of theories that aim to characterize the relationship between cause and effect using the tools of probability theory. The central idea behind these theories is that causes change the probabilities of their effects. This article traces developments in probabilistic causation, including recent developments in causal modeling. A variety of issues within, and objections to, probabilistic theories of causation will also be discussed.

If counterfactual dependence is sufficient for causation and if omissions can be causes, then all events have many more causes than common sense tends to recognize. This problem is standardly addressed by appeal to pragmatics. However, Carolina Sartorio [2010] has recently raised what I shall argue is a more interesting problem concerning omissions for counterfactual theories of causation—more interesting because it demands a more subtle pragmatic solution. I discuss the relationship between the idea that causes are proportional to their effects, (...) the idea that causation is contrastive, and the question of the dimensions along which causal explanations should be evaluated with respect to one another. (shrink)

The paper argues that dualism can explain mental causation and solve the exclusion problem. If dualism is combined with the assumption that the psychophysical laws have a special status, it follows that some physical events counterfactually depend on, and are therefore caused by, mental events. Proponents of this account of mental causation can solve the exclusion problem in either of two ways: they can deny that it follows that the physical effect of a mental event is overdetermined by its mental (...) and physical causes, or they can accept that the physical effect is overdetermined but claim that this is unproblematic because the case is sufficiently dissimilar to prototypical cases of overdetermination. (shrink)

On the received view, counterfactuals are analysed using the concept of closeness between possible worlds: the counterfactual 'If it had been the case that p, then it would have been the case that q' is true at a world w just in case q is true at all the possible p-worlds closest to w. The degree of closeness between two worlds is usually thought to be determined by weighting different respects of similarity between them. The question I consider in the (...) paper is which weights attach to different respects of similarity. I start by considering Lewis's answer to the question and argue against it by presenting several counterexamples. I use the same examples to motivate a general principle about closeness: if a fact obtains in both of two worlds, then this similarity is relevant to the closeness between them if and only if the fact has the same explanation in the two worlds. I use this principle and some ideas of Lewis's to formulate a general account of counterfactuals, and I argue that this account can explain the asymmetry of counterfactual dependence. The paper concludes with a discussion of some examples that cannot be accommodated by the present version of the account and therefore necessitate further work on the details. (shrink)

Laws of nature take center stage in philosophy of science. Laws are usually believed to stand in a tight conceptual relation to many important key concepts such as causation, explanation, confirmation, determinism, counterfactuals etc. Traditionally, philosophers of science have focused on physical laws, which were taken to be at least true, universal statements that support counterfactual claims. But, although this claim about laws might be true with respect to physics, laws in the special sciences (such as biology, psychology, economics etc.) (...) appear to have—maybe not surprisingly—different features than the laws of physics. Special science laws—for instance, the economic law “Under the condition of perfect competition, an increase of demand of a commodity leads to an increase of price, given that the quantity of the supplied commodity remains constant” and, in biology, Mendel's Laws—are usually taken to “have exceptions”, to be “non-universal” or “to be ceteris paribus laws”. How and whether the laws of physics and the laws of the special sciences differ is one of the crucial questions motivating the debate on ceteris paribus laws. Another major, controversial question concerns the determination of the precise meaning of “ceteris paribus”. Philosophers have attempted to explicate the meaning of ceteris paribus clauses in different ways. The question of meaning is connected to the problem of empirical content, i.e., the question whether ceteris paribus laws have non-trivial and empirically testable content. Since many philosophers have argued that ceteris paribus laws lack empirically testable content, this problem constitutes a major challenge to a theory of ceteris paribus laws. (shrink)

There are many ways of attaching two objects together: for example, they can be connected, linked, tied or bound together; and the connection, link, tie or bind can be made of chain, rope, or cement. Every one of these binding methods has been used as a metaphor for causation. What is the real significance of these metaphors? They express a commitment to a certain way of thinking about causation, summarized in the following thesis: ‘In any concrete situation, there is an (...) objective fact of the matter as to whether two events are in fact bound by the causal relation. It is the aim of philosophical inquiry to analyze this objective relation.’ Through a variety of examples, I hope to cast doubt on this seemingly innocuous thesis. The problem lies not with the word ‘objective’, but with the word ‘the’. The goal of a philosophical account of causation should not be to capture the causal relation, but rather to capture the many ways in which the events of the world can be bound together. 1 The metaphors 2 Unpacking the metaphors 3 Theories of causation 4 The two assassins 5 The birth control pills 6 The smoker-protector gene 7 The bicycle thief 8 Further examples 8.1 Indeterminism 8.2 Probability-lowering causes 8.3 Parts vs wholes 8.4 Symmetric overdetermination 8.5 Delayers 8.6 Causation by omission 8.7 Double prevention/disconnection 8.8 Preemptive prevention 8.9 Quantitative variables 9 Conclusion. (shrink)

Experimental philosophers have empirically challenged the connection between intuition and philosophical expertise. This paper reviews these challenges alongside other research findings in cognitive science on expert performance and argues for three claims. First, evidence taken to challenge philosophical expertise may also be explained by the well-researched failures and limitations of genuine expertise. Second, studying the failures and limitations of experts across many fields provides a promising research program upon which to base a new model of philosophical expertise. Third, a model (...) of philosophical expertise based on the limitations of genuine experts may suggest a series of constraints on the reliability of professional philosophical intuition. Even when the experts all agree, they may well be mistaken. — Bertrand Russell, On the Value of Scepticism. (shrink)

For a long time, regularity accounts of causation have virtually vanished from the scene. Problems encountered within other theoretical frameworks have recently induced authors working on causation, laws of nature, or methodologies of causal reasoning – as e.g. May (Kausales Schliessen. Eine Untersuchung über kausale Erklärungen und Theorienbildung. Ph.D. thesis, Universität Hamburg, Hamburg, 1999), Ragin (Fuzzy-set social science. Chicago: University of Chicago Press, 2000), Graßhoff and May (Causal regularities. In W. Spohn, M. Ledwig, & M. Esfeld (Eds.), Current issues in (...) causation (pp. 85–114). Paderborn: Mentis, 2001), Swartz (The concept of physical law (2nd ed.). http://www.sfu.ca/philosophy/physical-law/, 2003), Halpin (Erkenntnis, 58, 137–168, 2003) – to direct their attention back to regularity theoretic analyses. In light of the latest proposals of regularity theories, the paper at hand therefore reassesses the criticism raised against regularity accounts since the INUS theory of causation of Mackie (The cement of the universe. A study of causation. Oxford: Clarendon Press, 1974). It is shown that most of these objections target strikingly over-simplified regularity theoretic sketches. By outlining ways to refute these objections it is argued that the prevalent conviction as to the overall failure of regularity theories has been hasty. (shrink)

I argue that causation is a contrastive relation: c-rather-than-C* causes e-rather-than-E*, where C* and E* are contrast classes associated respectively with actual events c and e. I explain why this is an improvement on the traditional binary view, and develop a detailed definition. It turns out that causation is only well defined in ‘uniform’ cases, where either all or none of the members of C* are related appropriately to members of E*.

This paper examines the relationship between physical theories of causation and theories of difference-making. It is plausible to think that such theories are compatible with one another as they are aimed at different targets: the former, an empirical account of actual causal relations; the latter, an account that will capture the truth of most of our ordinary causal claims. The question then becomes: what is the relationship between physical causation and difference-making? Is one kind of causal fact more fundamental than (...) the other? This paper defends causal foundationalism: the view that facts about difference-making are dependent on the obtaining of facts about physical causation. However, the paper's main goal is to clarify the structure of the debate. At the end of the paper, it is shown how settling the issue about the relationship between physical theories of causation and theories of difference-making has more than mere intrinsic interest in unifying the very different pursuits that have been undertaken in the philosophy of causation. It can help to break a stalemate that has arisen in the current debate about mental causation. (shrink)

Conditionals somehow express conditional beliefs. However, conditional belief is a bi-propositional attitude that is generally not truth-evaluable, in contrast to unconditional belief. Therefore, this article opts for an expressivistic semantics for conditionals, grounds this semantics in the arguably most adequate account of conditional belief, that is, ranking theory, and dismisses probability theory for that purpose, because probabilities cannot represent belief. Various expressive options are then explained in terms of ranking theory, with the intention to set out a general interpretive scheme (...) that is able to account for the most variegated usage of conditionals. The Ramsey test is only the first option. Relevance is another, familiar, but little understood item, which comes in several versions. This article adds a further family of expressive options, which is able to subsume also counterfactuals and causal conditionals, and indicates at the end how this family allows for partial recovery of truth conditions for conditionals. (shrink)

Empirical research has recently emerged as a key method for understanding the nature of causation, and our concept of causation. One thread of research aims to test intuitions about the nature of causation in a variety of classic cases. These experiments have principally been used to try to resolve certain debates within analytic philosophy, most notably that between proponents of transference and dependence views of causation. The other major thread of empirical research on our concept of causation has investigated the (...) role that normative considerations play in causal judgments. These experimental results suggest that philosophical accounts of our concept of causation should take a broader view of what might be relevant. For both lines of research, we describe some of the significant experiments and outline key philosophical morals that have been drawn, all while pointing out various limitations. We conclude by considering other kinds of empirical research that should be philosophically interesting for those studying the nature of causation and our concept of causation. In particular, we point towards the need for philosophical research about causal perception, causal reasoning, and causal learning, as well as ways in which this research could play a role in prescriptive metaphysics. (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)

We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) "neuron" and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial system state since state changes are relevant, but (...) most current accounts ignore state changes through time; (5) more generally, there is no reason to think that philosophical judgements about these sorts of cases are normative; but (6) there is a dearth of relevant psychological research that bears on whether various philosophical accounts are descriptive. Our skepticism is not directed towards the possibility of a correct account of actual causation; rather, we argue that standard methods will not lead to such an account. A different approach is required. (shrink)

Recent studies indicate that indicative conditionals like "If people wear masks, the spread of Covid-19 will be diminished" require a probabilistic dependency between their antecedents and consequents to be acceptable (Skovgaard-Olsen et al., 2016). But it is easy to make the slip from this claim to the thesis that indicative conditionals are acceptable only if this probabilistic dependency results from a causal relation between antecedent and consequent. According to Pearl (2009), understanding a causal relation involves multiple, hierarchically organized conceptual dimensions: (...) prediction, intervention, and counterfactual dependence. In a series of experiments, we test the hypothesis that these conceptual dimensions are differentially encoded in indicative and counterfactual conditionals. If this hypothesis holds, then there are limits as to how much of a causal relation is captured by indicative conditionals alone. Our results show that the acceptance of indicative and counterfactual conditionals can become dissociated. Furthermore, it is found that the acceptance of both is needed for accepting a causal relation between two co-occurring events. The implications that these findings have for the hypothesis above, and for recent debates at the intersection of the psychology of reasoning and causal judgment, are critically discussed. Our findings are consistent with viewing indicative conditionals as answering predictive queries requiring evidential relevance (even in the absence of direct causal relations). Counterfactual conditionals in contrast target causal relevance, specifically. Finally, we discuss the implications our results have for the yet unsolved question of how reasoners succeed in constructing causal models from verbal descriptions. (shrink)

The paper builds on the basically Humean idea that A is a cause of B iff A and B both occur, A precedes B, and A raises the metaphysical or epistemic status of B given the obtaining circumstances. It argues that in pursuit of a theory of deterministic causation this ‘status raising’ is best explicated not in regularity or counterfactual terms, but in terms of ranking functions. On this basis, it constructs a rigorous theory of deterministic causation that successfully deals (...) with cases of overdetermination and pre-emption. It finally indicates how the account's profound epistemic relativization induced by ranking theory can be undone. Introduction Variables, propositions, time Induction first Causation Redundant causation Objectivization. (shrink)

When one takes an intersectional perspective on patterns of oppression and domination, it becomes clear that familiar forms of systemic injustice, such as misogyny and anti-Black racism, are inseparable. Some feminist theorists conclude, from this, that the systems behind these injustices cannot be individuated—for example, that there isn’t patriarchy and white supremacy, but instead only white supremacist patriarchy. This chapter offers a different perspective. Philosophers have long observed that a statue and a lump of clay can be individuated although inseparable, (...) and that statues and lumps of clay do different explanatory and predictive work for the same causal outcomes. This chapter suggests that the same is true of systems such as patriarchy and white supremacy. These systems, like the injustices they produce, are inseparable. But they can be individuated, and when they are individuated, they do different explanatory and predictive work. (shrink)

The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that (...) an examination of the structure of these problem cases suggests a different treatment, one which avoids the costs of extant probabilistic analyses. (shrink)

Recent papers by a number of philosophers have been concerned with the question of whether natural selection is a causal process, and if it is, whether the causes of selection are properties of individuals or properties of populations. I shall argue that much confusion in this debate arises because of a failure to distinguish between causal productivity and causal relevance. Causal productivity is a relation that holds between events connected via continuous causal processes, while causal relevance is a relationship that (...) can hold between a variety of different kinds of facts and the events that counterfactually depend upon them. I shall argue that the productive character of natural selection derives from the aggregation of individual processes in which organisms live, reproduce and die. At the same time, a causal explanation of the distribution of traits will necessarily appeal both to causally relevant properties of individuals and to causally relevant properties that exist only at the level of the population. (shrink)

This paper examines three views of what an omission or an instance of refraining is. The view advanced is that in many cases, an omission is simply an absence of an action of some type. However, generally one’s not doing a certain thing counts as an omission only if there is some norm, standard, or ideal that calls for one’s doing that thing.

The most compelling extant accounts of explanation casts all explanations as causal. Yet there are sciences, theoretical population biology in particular, that explain their phenomena by appeal to statistical, non-causal properties of ensembles. I develop a generalised account of explanation. An explanation serves two functions: metaphysical and cognitive. The metaphysical function is discharged by identifying a counterfactually robust invariance relation between explanans event and explanandum. The cognitive function is discharged by providing an appropriate description of this relation. I offer examples (...) of explanations from portfolio theory and population genetics that meet this characterisation. In each case the invariance relation holds between a statistical property of an ensemble and a change in structure of the ensemble. In neither case, however, does the statistical property cause the outcome it explains. There are genuine statistical, non-causal scientific explanations. (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)

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)

The majority of the currently flourishing theories of actual causation are located in a broadly counterfactual framework that draws on structural equations. In order to account for cases of symmetric overdeterminiation and preemption, these theories resort to rather intricate analytical tools, most of all, to what Hitchcock has labeled explicitly nonforetracking counterfactuals. This paper introduces a regularity theoretic approach to actual causation that only employs material conditionals, standard Boolean minimization procedures, and a stability condition that regulates the behavior of causal (...) models under model expansions. Notwithstanding its lightweight analytical toolbox, this regularity theory performs at least as well as the structural equations accounts with their heavy appliances. (shrink)

The key idea of the interventionist account of causation is that a variable A causes a variable B if and only if B would change if A were manipulated in the appropriate way. This paper raises two problems for Woodward's (2003) version of interventionism. The first is that the conditions it imposes are not sufficient for causation, because these conditions are also satisfied by non-causal relations of nomological dependence expressed in association laws. Such laws ground a relation of mutual manipulability (...) that is incompatible with the asymmetry of causation. Several ways of defending the interventionist account are examined and found unsatisfying. The second problem is that it often seems to be impossible, in a model that contains variables linked by an association law, to satisfy the conditions imposed on interventions on such variables. Various ways to solve this second problem, most importantly the analysis of manipulability in terms of difference making, are examined. Given that none solves the problem, I conclude that the interventionist conditions are neither sufficient nor necessary for causation. It is suggested that they provide an analysis of nomological dependence, which may be supplemented with the notion of a causal process to yield an analysis of causation. (shrink)

This paper introduces a new family of cases where agents are jointly morally responsible for outcomes over which they have no individual control, a family that resists standard ways of understanding outcome responsibility. First, the agents in these cases do not individually facilitate the outcomes and would not seem individually responsible for them if the other agents were replaced by non-agential causes. This undermines attempts to understand joint responsibility as overlapping individual responsibility; the responsibility in question is essentially joint. Second, (...) the agents involved in these cases are not aware of each other's existence and do not form a social group. This undermines attempts to understand joint responsibility in terms of actual or possible joint action or joint intentions, or in terms of other social ties. Instead, it is argued that intuitions about joint responsibility are best understood given the Explanation Hypothesis, according to which a group of agents are seen as jointly responsible for outcomes that are suitably explained by their motivational structures: something bad happened because they didn’t care enough; something good happened because their dedication was extraordinary. One important consequence of the proposed account is that responsibility for outcomes of collective action is a deeply normative matter. (shrink)

In Making Things Happen, James Woodward influentially combines a causal modeling analysis of actual causation with an interventionist semantics for the counterfactuals encoded in causal models. This leads to circularities, since interventions are defined in terms of both actual causation and interventionist counterfactuals. Circularity can be avoided by instead combining a causal modeling analysis with a semantics along the lines of that given by David Lewis, on which counterfactuals are to be evaluated with respect to worlds in which their antecedents (...) are realized by miracles. I argue, pace Woodward, that causal modeling analyses perform just as well when combined with the Lewisian semantics as when combined with the interventionist semantics. Reductivity therefore remains a reasonable hope. (shrink)

It is tempting to analyse causality in terms of just one of the indicators of causal relationships, e.g., mechanisms, probabilistic dependencies or independencies, counterfactual conditionals or agency considerations. While such an analysis will surely shed light on some aspect of our concept of cause, it will fail to capture the whole, rather multifarious, notion. So one might instead plump for pluralism: a different analysis for a different occasion. But we do not seem to have lots of different concepts of cause (...) – just one eclectic notion. The resolution of this conundrum, I think, requires us to accept that our causal beliefs are generated by a wide variety of indicators, but to deny that this variety of indicators yields a variety of concepts of cause. This focus on the relation between evidence and causal beliefs leads to what I call epistemic causality. Under this view, certain causal beliefs are appropriate or rational on the basis of observed evidence; our notion of cause can be understood purely in terms of these rational beliefs. Causality, then, is a feature of our epistemic representation of the world, rather than of the world itself. This yields one, multifaceted notion of cause. (shrink)

I argue, contrary to standard claims, that accomplice liability need not be a causal relation. One can be an accomplice to another’s crime without causally contributing to the criminal act of the principal. This is because the acts of aid and encouragement that constitute the basis for accomplice liability typically occur in contexts of under- and over-determination, where causal analysis is confounded. While causation is relevant to justifying accomplice liability in general, only potential causation is necessary in particular cases. I (...) develop this argument through the example of the role of U.S. legal officials in abetting the acts of unlawful interrogation that have taken place since 2001. I also suggest that there may be a limited justification for ex post ratificatory accomplice liability. (shrink)

Experimental studies suggest that people’s ordinary causal judgments are affected not only by statistical considerations but also by moral considerations. One way to explain these results would be to construct a model according to which people are trying to make a purely statistical judgment but moral considerations somehow distort their intuitions. The present paper offers an alternative perspective. Specifically, the author proposes a model according to which the very same underlying mechanism accounts for the influence of both statistical and moral (...) considerations. On this model, it appears that ordinary causal judgments are quite different from the sorts of judgments one might find in the systematic sciences.Keywords: Causation; Causal cognition; Experimental philosophy; Cognitive science. (shrink)

Hall has recently argued that there are two concepts of causality, picking out two different kinds of causal relation. McGrath, and Hitchcock and Knobe, have recently argued that the facts about causality depend on what counts as a “default” or “normal” state, or even on the moral facts. In the light of these claims you might be tempted to agree with Skyrms that causal relations constitute, metaphysically speaking, an “amiable jumble”, or with Cartwright that ‘causation’, though a single word, encompasses (...) many different kinds of things. This paper argues, drawing on the author’s recent work on explanation, that the evidence adduced in support of causal pluralism can be accommodated easily by a unified theory of causality—a theory according to which all singular causal claims concern the same fundamental causal network. (shrink)

Hall [(2007), Philosophical Studies, 132, 109–136] offers a critique of structural equations accounts of actual causation, and then offers a new theory of his own. In this paper, I respond to Hall’s critique, and present some counterexamples to his new theory. These counterexamples are then diagnosed.