Non-reductive interventionist theories of causation and methodologies of causal reasoning embedded in that theoretical framework have become increasingly popular in recent years. This paper argues that one variant of an interventionist account of causation, viz. the one presented, for example, in Woodward (2003), is unsuited as a theoretical fundament of interventionist methodologies of causal reasoning, because it renders corresponding methodologies incapable of uncovering a causal structure in a finite number of steps. This finding runs counter to Woodward's own assessment and (...) to other recent studies which presume that Woodward's version of interventionism is effectively applicable to uncover causal structures, e.g. Campbell (2007) or Shapiro and Sober (2007). (shrink)

Understanding probabilities as something other than point values has often been motivated by the need to find more realistic models for degree of belief, and in particular the idea that degree of belief should have an objective basis in “statistical knowledge of the world.” I offer here another motivation growing out of efforts to understand how chance evolves as a function of time. If the world is “chancy” in that there are non-trivial, objective, physical probabilities at the macro-level, then the (...) chance of an event e that happens at a given time is \ until it happens. But whether the chance of e goes to one continuously or not is left open. Discontinuities in such chance trajectories can have surprising and troubling consequences for probabilistic analyses of causation and accounts of how events occur in time. This, coupled with the compelling evidence for quantum discontinuities in chance’s evolution, gives rise to a “continuity bind” with respect to chance probability trajectories. I argue that a viable option for circumventing the continuity bind is to understand the probabilities “imprecisely,” that is, as intervals rather than point values. I then develop and motivate an alternative kind of continuity appropriate for interval-valued chance probability trajectories. (shrink)

Analyses of singular causation often make use of the idea that a cause increases the probability of its effect. Of particular salience in such accounts are the values of the probability function of the effect, conditional on the presence and absence of the putative cause, analysed around the times of the events in question: causes are characterized by the effect’s probability function being greater when conditionalized upon them. Put this way, it becomes clearer that the ‘behaviour’ of probability functions in (...) small intervals about the times in question ought to be of concern. In this article, I make an extended case that causal theorists employing the ‘probability raising’ idea should pay attention to the continuity question. Specifically, if the probability functions are ‘jumping about’ in ways typical of discontinuous functions, then the stability of the relevant probability increase is called into question. The rub, however, is that sweeping requirements for either continuity or discontinuity are problematic and, as I argue, this constitutes a ‘continuity bind’. Hence more subtle considerations and constraints are needed, two of which I consider: utilizing discontinuous first derivatives of continuous probability functions, and abandoning point probability for imprecise probability. _1_ Introduction _2_ Probability Trajectories and Continuity _2.1_ Probability trajectories _2.2_ Causation as discontinuous jumps _2.3_ Against systematic discontinuity _3_ Broader Discontinuity Concerns _4_ The Continuity Bind _4.1_ Retaining continuity with discontinuous first derivatives _4.2_ Imprecise probability trajectories _5_ Concluding Remarks Appendix. (shrink)

According to some scholars, while sets of greenhouse gases emissions generate harms deriving from climate change, which can be mitigated through collective actions, individual emissions and mitigation activities seem to be causally insufficient to cause harms. If so, single individuals are neither responsible for climate harms, nor they have mitigation duties. If this view were true, there would be collective responsibility for climate harms without individual responsibility and collective mitigation duties without individual duties: this is puzzling. This paper explores a (...) way to solve this puzzle. First, it will be argued that individual emissions, though not proper and full-fledged causes, causally contribute to raise the probability of climate harms. As a consequence, individuals are in fact responsible for their expected contributions to climate harms – this is contributive responsibility for likely outcomes. Second, it will be argued that people have responsibility also for the possible impacts of their individual emissions on climate harms. People can plausibly be regarded as individually responsible for the possible outcomes of their actions in close possible alternative worlds – this is robust responsibility. Non-causal individual responsibility for climate harms is plausible, and the puzzle may be solved. (shrink)

There are, by now, many rival, sophisticated philosophical accounts of causation that qualify as ‘metaphysically reductive’. This is a good thing: these collective efforts have vastly improved our understanding of causation over the last 30 years or so. They also put us in an excellent position to reflect on some central methodological questions: What exactly is the point of offering a metaphysical reduction of causation? What philosophical scruples ought to guide the pursuit of such a reduction? Finally, how should answers (...) to these latter questions affect one’s assessment of the main contemporary approaches? That’s what we investigate in this essay. Section 1 lays out our presuppositions. Section 2 reviews a sample of philosophical accounts. Then comes the main event: Section 3 looks in detail at the foregoing methodological questions, closing with a reconsideration of our sample accounts, in light of what we’ve found. (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)

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)

An influential tradition in the philosophy of causation has it that all token causal facts are, or are reducible to, facts about difference-making. Challenges to this tradition have typically focused on pre-emption cases, in which a cause apparently fails to make a difference to its effect. However, a novel challenge to the difference-making approach has recently been issued by Alyssa Ney. Ney defends causal foundationalism, which she characterizes as the thesis that facts about difference-making depend upon facts about physical causation. (...) She takes this to imply that causation is not fundamentally a matter of difference-making. In this paper, I defend the difference-making approach against Ney’s argument. I also offer some positive reasons for thinking, pace Ney, that causation is fundamentally a matter of difference-making. (shrink)

I argue that there are non-trivial objective chances (that is, objective chances other than 0 and 1) even in deterministic worlds. The argument is straightforward. I observe that there are probabilistic special scientific laws even in deterministic worlds. These laws project non-trivial probabilities for the events that they concern. And these probabilities play the chance role and so should be regarded as chances as opposed, for example, to epistemic probabilities or credences. The supposition of non-trivial deterministic chances might seem to (...) land us in contradiction. The fundamental laws of deterministic worlds project trivial probabilities for the very same events that are assigned non-trivial probabilities by the special scientific laws. I argue that any appearance of tension is dissolved by recognition of the level-relativity of chances. There is therefore no obstacle to accepting non-trivial chance-role-playing deterministic probabilities as genuine chances. (shrink)

Philosophical theories of causation are commonly judged by their ability to correctly determine whether there is a causal relation present in intuitively clear example scenarios. If the theories survive this test, they are then used to answer big philosophical questions about causation. This Method of Examples is attractive because it seems to allow us to determine the quality of a theory of causation independently of answering the big philosophical questions; which is good, since it means that we can then non-circularly (...) use the theories judged to be best to answer those questions. However, the current article argues that this virtue of the Method of Examples is an illusion. In particular, I argue that the necessary step of judging whether a proposed analysis of causation is reductive can only be taken after many of the most vexing philosophical questions about causation have already been answered. It is then shown that a rejection of the methodological supremacy of the Method of Examples leads to a more pluralistic method of judging theories of causation, a pluralism that benefits non-standard approaches like interventionism and agency theories. (shrink)

In their article 'Causes and Explanations: A Structural-Model Approach. Part I: Causes', Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of 'actual cause'. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation.

ABSTRACT Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of ‘actual cause’. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation. 1Introduction 2Preemption 3Structural Equation Models 4The Halpern and Pearl Definition of ‘Actual Cause’ 5Preemption Again 6The Probabilistic Case 7Probabilistic Causal Models 8A Proposed Probabilistic Extension of Halpern and Pearl’s Definition 9Twardy and Korb’s Account 10Probabilistic (...) Fizzling 11Conclusion. (shrink)

An actual cause of some token effect is itself a token event that helped to bring about that effect. The notion of an actual cause is different from that of a potential cause – for example a pre-empted backup – which had the capacity to bring about the effect, but which wasn't in fact operative on the occasion in question. Sometimes actual causes are also distinguished from mere background conditions: as when we judge that the struck match was a cause (...) of the fire, while the presence of oxygen was merely part of the relevant background against which the struck match operated. Actual causation is also to be distinguished from type causation: actual causation holds between token events in a particular, concrete scenario; type causation, by contrast, holds between event kinds in scenario kinds. (shrink)

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)

“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.

The discovery of high-level causal relations seems a central activity of the special sciences. Those same sciences are less successful in formulating strict laws. If causation must be underwritten by strict laws, we are faced with a puzzle, which might be dubbed the 'no strict laws' problem for high-level causation. Attempts have been made to dissolve this problem by showing that leading theories of causation do not in fact require that causation be underwritten by strict laws. But this conclusion has (...) been too hastily drawn. Philosophers have tended to equate non-strict laws with ceteris paribus laws. I argue that there is another category of non-strict law that has often not been properly distinguished: namely, minutiae rectus laws. If, as it appears, many special science laws are minutiae rectus laws, then this poses a problem for their ability to underwrite causal relations in a way that their typically ceteris paribus nature does not. I argue that the best prospect for resolving the resurgent 'no strict laws' problem is to argue that special science laws are in fact typically probabilistic, rather than being minutiae rectus laws. (shrink)

A common objection to probabilistic theories of causation is that there are prima facie causes that lower the probability of their effects. Among the many replies to this objection, little attention has been given to Mellor's (1995) indirect strategy to deny that probability-lowering factors are bona fide causes. According to Mellor, such factors do not satisfy the evidential, explanatory, and instrumental connotations of causation. The paper argues that the evidential connotation only entails an epistemically relativized form of causal attribution, not (...) causation itself, and that there are clear cases of explanation and instrumental reasoning that must appeal to negatively relevant factors. In the end, it suggests a more liberal interpretation of causation that restores its connotations. Una objeción común a las teorías probabilísticas de la causalidad es que aparentemente existen causas que disminuyen la probabilidad de sus efectos. Entre las muchas respuestas a esta objeción, se le ha dado poca atención a la estrategia indirecta de D. H. Mellor (1995) para negar que un factor que disminuya la probabilidad de un efecto sea una causa legítima. Según Mellor, tales factores no satisfacen las connotaciones evidenciales, explicativas e instrumentales de la causalidad. El artículo argumenta que la connotación evidencial sólo implica una forma epistémicamente relativizada de atribución causal y no la causalidad misma, y que hay casos claros de explicación y razonamiento instrumental que deben apelar a factores negativamente relevantes. Se sugiere una interpretación más liberal de la causalidad que reinstaura sus connotaciones. (shrink)