Online research in philosophy

A quite popular approach to solving the Causal Exclusion Problem is to adopt a counterfactual theory of causation. In this paper, I distinguish three versions of the Causal Exclusion Argument. I argue that the counterfactualist approach can block the first two exclusion arguments, because the Causal Inheritance Principle and the Upward Causation Principle upon which the two arguments are based respectively are problematic from the perspective of the counterfactual account of causation. However, I attempt to show that the counterfactualist approach is unable to refute a sophisticated version (i.e. the third version) of the exclusion argument in that the Downward Causation Principle, a premise of the third exclusion argument, is actually implied by the counterfactual theory of causation. Therefore, even if other theories of causation might help the non-reductive physicalist to solve the exclusion problem, the counterfactual theory of causation cannot.

Jonathan Schaffer (2004 ) proposes an ingenious amendment to David Lewis's semantics for counterfactuals. This amendment explicitly invokes the notion of causal independence, thus giving up Lewis's ambitions for a reductive counterfactual account of causation. But in return, it rescues Lewis's semantics from extant counterexamples. I present a new counterexample that defeats even Schaffer's amendment. Further, I argue that a better approach would be to follow the causal modelling literature and evaluate counterfactuals via an explicit postulated causal structure. This alternative approach easily resolves the new counterexample, as well as all the previous ones. Up to now, its perceived drawback relative to Lewis's scheme has been its non-reductiveness. But since the same drawback applies equally to Schaffer's amended scheme, this becomes no longer a point of comparative disadvantage.

Counterfactual analysis of causation between particular events, combined with standard semantics for counterfactual conditionals, cannot express the idea that the cause is sufficient for the effect. Several authors have suggested that a more complex pattern of nested counterfactual conditionals is a better candidate for expressing the idea of causal connection. The most systematic account is developed by Kadri Vihvelin. She argues that a complex pattern of causal dependence, expressed by embedded conditionals, covers all the cases of causation and still yields an account of causal asymmetry. But the new account relies heavily on the use of backtracking conditionals, and no criterion is given for their evaluation. I will try to show that Vihvelin’s proposal is not superior to the standard account because it overlooks the disadvantages of a liberal theory of causal relata.

In this paper I wish to argue that counterfactual analyses of causation are inadequate. I believe the counterfactuals that are involved in counterfactual analyses of causation are often false, and thus the theories do not provide an adequate account of causation. This is demonstrated by the presentation of a counterexample to the counterfactual analyses of causation. I then present a unified theory of causation that is based upon probability and counterfactuals. This theory accounts for both deterministic and indeterministic causation, and is not subject to many of the traditional problems facing theories of causation.

Nancy Cartwright offers an account of causal powers, and argues that it explains some important general features of scientific method. Patricia Cheng argues that this theory is superior as a psychological theory of learning to standard models of conditioning. I extend and develop the theory, and argue that it provides the best explanation of a number of problem cases for philosophical theories of causation, including preemption, overdetermination and puzzles about transitivity. Hitchcock and Halpern & Pearl on ‘actual causes’ Problems and morals 2.1 Puzzles about prevention 2.2 Counterfactuals Causal powers 3.1 Generative causal power 3.2 Preventative causal power Net and component powers ‘Actual’ or ‘successful’ causes Solutions to puzzle cases Conclusion.

It seems to be generally accepted that (a) counterfactual conditionals are to be analysed in terms of possible worlds and inter-world relations of similarity and (b) causation is conceptually prior to counterfactuals. I argue here that both (a) and (b) are false. The argument against (a) is not a general metaphysical or epistemological one but simply that, structurally speaking, possible worlds theories are wrong: this is revealed when we try to extend them to cover the case of probabilistic counterfactuals. Indeed a type of counterfactual probability exists which cannot be expressed in possible worlds terms at all. The argument against (b) emerges when we look at the form of an adequate account of both probabilistic and non-probabilistic counterfactuals. I do this by sketching and defending an approach to counterfactuals that, first, invoke a generalized notion of cause as primitive and, secondly, is algorithmic in form: counterfactuals are evaluated algorithmically in terms of other counterfactuals, without vicious circularity. Structures like possible worlds do not play a role either in general truth-conditions or in evaluation. They are simply the wrong sorts of structures.

Mackie, J. L. Causes and conditions.--Taylor, R. The metaphysics of causation.--Scriven, M. Defects of the necessary condition analysis of causation.--Kim, J. Causes and events: Mackie on causation.--Anscombe, G. E. M. Causality and determination.--Davidson, D. Causal relations.--Wright, G. H. von. On the logic and epistemology of the causal relation.--Ducasse, C. J. On the nature and the observability of the causal relation.--Sellars, W. S. Counterfactuals.--Chisholm, R. M. Law statements and counterfactual inference.--Rescher, N. Belief-contravening suppositions and the problem of contrary-to-fact conditionals.--Stalnaker, R. A theory of conditionals.--Lewis, D. Causation.--Kim, J. Causes and counterfactuals.

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.

If we seek to analyse causation in terms of counterfactual conditionals then we must assume that there is a class of counterfactuals whose members (i) are all and only those we need to support our judgements of causation, (ii) have truth-conditions specifiable without any irreducible appeal to causation. I argue that (i) and (ii) are unlikely to be met by any counterfactual analysis of causation. I demonstrate this by isolating a class of counterfactuals called non-projective counterfactuals, or NP-counterfactuals, and indicate how counterfactual analyses of causation must appeal to them to account for the correct causal judgements we make. I show that the truth-conditions of NP-counterfactuals are specifiable only by irreducible appeal to causation. A dilemma then holds: if counterfactual analyses of causation eschew appeal to NP-counterfactuals they are empirically inadequate, but if they appeal to NP-counterfactuals they are circular and thus conceptually inadequate.

In the artificial intelligence literature a promising approach to counterfactual reasoning is to interpret counterfactual conditionals based on causal models. Different logics of such causal counterfactuals have been developed with respect to different classes of causal models. In this paper I characterize the class of causal models that are Lewisian in the sense that they validate the principles in Lewis’s well-known logic of counterfactuals. I then develop a system sound and complete with respect to this class. The resulting logic is the weakest logic of causal counterfactuals that respects Lewis’s principles, sits in between the logic developed by Galles and Pearl and the logic developed by Halpern, and stands to Galles and Pearl’s logic in the same fashion as Lewis’s stands to Stalnaker’s.