Probabilistic accounts of causality have long had trouble with ‘spurious’ evidential correlations. Such correlations are also central to the case for causal decision theory—the argument that evidential decision theory is inadequate to cope with certain sorts of decision problem. However, there are now several strong defences of the evidential theory. Here I present what I regard as the best defence, and apply it to the probabilistic approach to causality. I argue that provided a probabilistic theory appeals to the notions of (...) agency and effective strategy, it can avoid the problem of spurious causes. I show that such an appeal has other advantages; and argue that it is not illegitimate, even for a causal realist. (shrink)

One of the most striking features of causation is that causes typically precede their effects – the causal arrow is strongly aligned with the temporal arrow. Why should this be so? We offer an opinionated guide to this problem, and to the solutions currently on offer. We conclude that the most promising strategy is to begin with the de facto asymmetry of human deliberation, characterised in epistemic terms, and to build out from there. More than any rival, this subjectivist approach (...) promises to demystify the asymmetry, temporal orientation, and deliberative relevance of causal judgements. (shrink)