Counterfactuals and Causal Relevance

Mind, 1997

On David Lewis's original analysis of causation, c causes e only if c is linked to e by a chain of distinct events such that each event in the chain (counterfactually) depends on the former one. But, this requirement precludes the possibility of late pre-emptive causation, of causation by fragile events, and of indeterministic causation. Lewis proposes three different strategies for accommodating these three kinds of cases, but none of these turn out to be satisfactory. I offer a single analysis of causation that resolves these problems in one go but which respects Lewis's initial insights. One distinctive feature of my account is that it accommodates indeterministic causation without resorting to probabilities.

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 is rooted in pragmatic 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 not. Consequently, assessments of causal parity and priority require more resources, which can either be additional or part of the causal analysis itself. Adding resources has been standard, but here we develop a unified analysis that includes a range of different precise causal concepts, which allows for assessments of causal priority in terms of different kinds of causal relevance.

Among the many philosophers who hold that causal facts 1 are to be explained in terms of-or more ambitiously, shown to reduce to-facts about what happens, together with facts about the fundamental laws that govern what happens, the clear favorite is an approach that sees counterfactual dependence as the key to such explanation or reduction. The paradigm examples of causation, so advocates of this approach tell us, are examples in which events c and e-the cause and its effect-both occur, but: had c not occurred, e would not have occurred either. From this starting point ideas proliferate in a vast profusion. But the remarkable disparity among these ideas should not obscure their common foundation. Neither should the diversity of opinion about the prospects for a philosophical analysis of causation obscure their importance. For even those philosophers who see these prospects as dim-perhaps because they suffer post-Quinean queasiness at the thought of any analysis of any concept of interest-can often be heard to say such things as that causal relations among events are somehow "a matter of" the patterns of counterfactual dependence to be found in them.

Noûs, 2008

In this paper I put forward a probabilistic analysis of the notion of cause. I argue that for an event A to be a cause of an event C is for A to have some positive causal impact on C. I provide a probabilistic analysis of the notion of some positive causal impact, mainly in terms of the concept of a strict increaser, and argue that, roughly, for A to have some positive causal impact on C is for there to be a strict increaser for A and C. I relate the notion of some positive causal impact to my account of counterfactuals. Finally, I contrast my account with the theories of D. Lewis and W. Salmon. Lewis's theory of cause is a counterfactual theory. 1 Lewis's conception of counterfactuals (Lewis, 1973) was originally developed for a deterministic world. On this account, one orders possible worlds by the relation of intuitive overall similarity, and the counterfactual is (non-vacuously) true iff the consequent is true in all the antecedent-worlds in some sphere (centered around the world in which the counterfactual is assessed, and which includes some antecedentworlds). This theory faced robust counterexamples, in particular counterfactuals which have generally been taken to come out true on Lewis's theory, though they shouldn't. One, for instance, is the false counterfactual 'Had I been at least an inch taller than I am, I would have been exactly an inch taller.'The most notorious counterexample involves the counterfactual 'Had Nixon pushed the nuclear button, there would have been no nuclear blast'. These counterfactuals are patently false, but come out true on Lewis's theory, one should think, since there are antecedent-worlds in which the consequent is true which are more intuitively similar to the actual world than the antecedent-worlds in which the consequent is false. Lewis consequently modified his original theory by abandoning the reliance on intuitive overall similarity, and moved to a conception of weights and priorities for similarity (Lewis, 1979) 4 on which the overall similarity relation is not

Axiomathes, 2005

The article deals with one particular problem created by the counterfactual analysis of causality à la Lewis, namely the context-sensitivity problem or, as I prefer to call it, the background condition problem. It appears that Lewis’ counterfactual definition of causality cannot distinguish between proper causes and mere causal conditions – i.e. factors necessary for the effect to occur, but commonly not seen as causally efficacious. The proposal is put forward to amend the Lewis definition with a condition, based on the notion of cotenability, which would eliminate the problem. It is shown that the corrected definition of causality leads to the transitivity of the causal relation. Possible objections to the proposed solution, involving the assumption of indeterminism and the preemption cases, are given a thorough consideration.

Siegal, Elitzur and Nora Boneh (eds.), Perspectives on Causation, Springer., 2020

Counterfactual conditionals are used extensively in causal reasoning. This observation has motivated a philosophical tradition that aims to provide a counterfactual analysis of causation. However, such analyses have come under pressure from a proliferation of counterexamples and from evidence that suggests that the truth-conditions of counterfactuals are themselves causal. I offer an alternative account of the role of counterfactuals in causal thought that is consistent with these data: counterfactuals are used in a common method of causal reasoning related to John Stuart Mill's method of difference. The method uses background beliefs about causal relationships, history, and the natural laws to establish a new causal claim. Counterfactuals serve as a convenient tool for stating certain intermediate conclusions in this reasoning procedure, and that is part of what makes counterfactuals useful. This account yields a functional explanation of why our language contains a construction with the truth-conditions of counterfactuals. 3 For an interesting alternative explanation of the connection between causation and counterfactuals, see Maudlin (2004). 4 I do not claim that that is the only function of counterfactual conditionals. They clearly also serve other purposes, e.g. in making practical decisions.

International Journal of Philosophical Studies, 2007

The counterfactual analysis of causation has focused on one particular counterfactual conditional, taking as its starting point the suggestion that C causes E iff (~C □→ ~E). In this paper, some consequences are explored of reversing this counterfactual, and developing an account starting with the idea that C causes E iff (~E □→ ~C). This suggestion is discussed in relation to the problem of preemption. It is found that the “reversed” counterfactual analysis can handle even the most difficult cases of preemption with only minimal complications. The paper closes with a discussion of the wider philosophical implications of developing a reversed counterfactual analysis, especially concerning the differentiation of causes from causal conditions, causation by absences, and the extent to which causes suffice for their effects.

2001

A, B and C occurred at t 1 , t 2 and t 3 respectively. Intuitively, A was not a cause of C-the fact that x's finger was cut off at t 1 was not a cause of the fact that x's finger was functional at t 3. 5 But, again intuitively, A was a cause of B-the fact that x's finger was cut off at t 1 was a cause of the fact that the surgeon connected the finger at t 2 ; and, again, intuitively, B was a cause of C-the fact that the surgeon connected the finger at t 2 was a cause of the fact that x's finger was functional at t 3. Hence cause transitivity fails. 6 The events in this example are specified in sentential formulation. But this is an incidental feature of the presentation of the example. The example holds just as well in nominalized form. Thus, the injury was a cause of the surgery, and the surgery was a cause of the functionality of the finger at t 3 ; but the injury was not a cause of the functionality of the finger at t 3. The force of the example is thus not dependent on whether narrow or broad event individuation is employed. The force of this example of the nontransitivity of cause also holds regardless of whether the world is assumed to be deterministic or indeterministic: cause is non-transitive in either case. This example is, in particular, a counterexample to Lewis's counterfactual analysis of cause. Had the surgeon not connected x's finger (at t 2), the finger would not have been functional at t 3 ; 7 and had x's finger not been cut off (at t 1), the surgeon would not have connected it at t 2. Hence ∼A > ∼B and ∼B > ∼C are true. On Lewis's analysis, it should follow that A is a cause of C; but A is not a cause of C. 8 Some purported counterexamples to cause transitivity do not, however, bring out the hard core of the failure of cause transitivity. Thus, consider a McDermott-type example, 9 in which a terrorist x placed a bomb, to be set off by x's pressing a button of a remote-control device. However, before x managed to press the button: A-a dog bit x's right forefinger. Unable to use his injured forefinger, and despite his pain: Bx pressed the button with his left forefinger, and consequently: C-the bomb exploded. Indeed, A is a cause of B and B of C, but A is not a cause of C. This example, however, does not bring out the heart of the transitivity failure distinctive of being a cause since it trades on transitivity failure

2018

We explore the relationships between causal rules and counterfactuals, as well as their relative representation capabilities, in the logical framework of the causal calculus. It will be shown that, though counterfactuals are readily definable on the basis of causal rules, the reverse reduction is achievable only up to a certain logical threshold (basic equivalence). As a result, we will argue that counterfactuals cannot distinguish causal theories that justify different claims of actual causation, which could be seen as the main source of the problem of ‘structural equivalents’ in counterfactual approaches to causation. This will lead us to a general conclusion about the primary role of causal rules in representing causation.

Philosophical Studies, 2010

I argue that one central aspect of the epistemology of causation, the use of causes as evidence for their effects, is largely independent of the metaphysics of causation. In particular, I use the formalism of Bayesian causal graphs to factor the incremental evidential impact of a cause for its effect into a direct cause-to-effect component and a backtracking component. While the ''backtracking'' evidence that causes provide about earlier events often obscures things, once we our restrict attention to the cause-to-effect component it is true to say promoting (inhibiting) causes raise (lower) the probabilities of their effects. This factoring assumes the same form whether causation is given an interventionist, counterfactual or probabilistic interpretation. Whether we think about causation in terms of interventions and causal graphs, counterfactuals and imaging functions, or probability raising against the background of causally homogenous partitions, if we describe the essential features of a situation correctly then the incremental evidence that a cause provides for its effect in virtue of being its cause will be the same. Keywords Causal inference Á Incremental evidence Á Bayesian causal graph Á Markov condition Á Imaging Á Backtracking counterfactual Á Probabilistic causation My topic is the epistemology of causation. Philosophical discussions of causation usually focus on metaphysics: Is causation merely constant conjunction? Is it a projection of human habits of inference? Do causal claims presuppose the truth of general laws? What is the relation between causation and our ability to manipulate events? How are causal and counterfactual claims related? While these are important questions, it is no part of my purpose here to answer them. First, I don't