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.

Many philosophers insist that the most plausible solution to the exclusion problem is to adopt the so-called ‘autonomy approach’, which denies either upward or downward causation between mental and physical properties. But the question of whether the autonomy approach is compatible with respectable theories of causation has seldom been discussed in the literature. This paper considers two influential theories of causation, the counterfactual account and the regularity account. I argue that neither the counterfactual theory nor the regularity theory can support the autonomy approach – while the counterfactual approach fails to block downward causation, the regularity approach is unable to refute upward causation.

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.

Jonardon Ganeri, Paul Noordhof, and Murali Ramachandran (1996) have proposed a new counterfactual analysis of causation. We argue that this – the PCA-analysis – is incorrect. In section 1, we explain David Lewis’s first counterfactual analysis of causation, and a problem that led him to propose a second. In section 2 we explain the PCA-analysis, advertised as an improvement on Lewis’s later account. We then give counterexamples to the necessity (section 3) and sufficiency (section 4) of the PCA-analysis.

Counterfactual analyses of causation can provide elegant analyses of many cases of causation. However, they fail to give intuitively correct analyses of cases involving a commonplace variety of late preemptive causation. I argue that a small emendation can solve the problem.

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 a recent paper Causal Asymmetry, Douglas Ehring has proposed an intriguing solution to the vexing problem of causal asymmetry. The aim of this paper is to show that his theory is not satisfactory. Moreover, the examples that I use in showing the defect of Ehring's theory also indicate that the counterfactual analysis of causation has a problem that cannot be remedied by Marshall Swain's suggested refinement of the counterfactual analysis of causation in Causation and Distinct Events.

Recently Stephen Barker has raised stimulating objections to the thesis that, roughly speaking, if two events stand in a relation of counterfactual dependence, they stand in a causal relation. As Ned Hall says, however, this thesis constitutes the strongest part of the counterfactual analysis of causation. Therefore, if successful, Barker’s objections will undermine the cornerstone of the counterfactual analysis of causation, and hence give us compelling reasons to reject the counterfactual analysis of causation. I will argue, however, that they do not withstand scrutiny.

Over the past few decades analyses of causation have proliferated in almost immeasurable abundance, and with two things in common; firstly, they make much of counterfactual dependence, and secondly, none of them successfully handle all the pre-emption cases. In this thesis, I fore-mostly investigate David Lewis’ promising counterfactual analyses of causation (along with many others), and provide an extensive examination of pre-emption cases. I also offer my own counterfactual analysis of causation, which I argue can handle the problematic pre-emption cases, and therein succeed where so many other prominent analyses of causation have failed. I then conclude with some morals for the continuing debate.