Online research in philosophy

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.

Arguments for A "fair" coin has probability 1/2. There is no physical probability attached to the coin, we can cheat on each toss (by sufficient control). My aim: The coin toss is fine-grained deterministic, but coarsgrained random.

On the received view, counterfactuals are analysed using the concept of closeness between possible worlds: the counterfactual 'If it had been the case that p, then it would have been the case that q' is true at a world w just in case q is true at all the possible p-worlds closest to w. The degree of closeness between two worlds is usually thought to be determined by weighting different respects of similarity between them. The question I consider in the paper is which weights attach to different respects of similarity. I start by considering Lewis's answer to the question and argue against it by presenting several counterexamples. I use the same examples to motivate a general principle about closeness: if a fact obtains in both of two worlds, then this similarity is relevant to the closeness between them if and only if the fact has the same explanation in the two worlds. I use this principle and some ideas of Lewis's to formulate a general account of counterfactuals, and I argue that this account can explain the asymmetry of counterfactual dependence. The paper concludes with a discussion of some examples that cannot be accommodated by the present version of the account and therefore necessitate further work on the details.

A ‘might’ counterfactual is a sentence of the form ‘If it had been the case that A, it might have been the case that C’. Recently, John Hawthorne has argued that the truth of many ‘might’ counterfactuals precludes the truth of most ‘would’ counterfactuals. I examine the semantics of ‘might’ counterfactuals, with one eye towards defusing this argument, but mostly with the aim of understanding this interesting class of sentences better.

If one flips an unbiased coin a million times, there are 2 1,000,000 series of possible heads/tails sequences, any one of which might be the sequence that obtains, and each of which is equally likely to obtain. So it seems (1) ‘If I had tossed a fair coin one million times, it might have landed heads every time’ is true. But as several authors have pointed out, (2) ‘If I had tossed a fair coin a million times, it wouldn’t have come up heads every time’ will be counted as true in everyday contexts. And according to David Lewis’ influential semantics for counterfactuals, (1) and (2) are contradictories. We have a puzzle. We must either (A) deny that (2) is true, (B) deny that (1) is true, or (C) deny that (1) and (2) are contradictories, thus rejecting Lewis’ semantics. In this paper I discuss and criticize the proposals of David Lewis and more recently J. Robert G. Williams which solve the puzzle by taking option (B). I argue that we should opt for either (A) or (C).

One criticism of David Lewis''s account of counterfactuals is that it sometimes assigns the wrong truth-value to a counterfactual when both antecedent and consequent happen to be true. Lewis has suggested a possible remedy to this situation, but commentators have found this to be unsatisfactory. I suggest an alternative solution which involves a modification of Lewis''s truth conditions, but which confines itself to the resources already present in his account. This modification involves the device of embedding one counterfactual within another. On the revised set of truth conditions, counterfactuals with true components are sometimes true and sometimes false, in a way that is more in keeping with our intuitive judgments about such statements.

In this note I discuss what seems to be a new kind of counterexample to Lewis’s account of counterfactuals. A coin is to be tossed twice. I bet on ‘Two heads’, and I win. Common sense says that (1) is false. But Lewis’s theory says that it is true. (1) If at least one head had come up, I would have won.

Sidney Morgenbesser brought to attention cases of the following form: (MC1) Chump tosses an indeterministic coin and, whilst it is in mid-air, calls heads. The coin lands tails, and Chump loses. His betting was causally independent of the coin’s fall. Chump seems right to say: ‘If I had bet tails, I would have won.’1 (MC2).

It is widely held that, as Morgenbesser’s case is usually taken to show, considerations of causal or probabilistic dependence should enter into the evaluation of counterfactuals. This paper challenges that idea. I present a modified version of Morgenbesser’s case and show how probabilistic approaches to counterfactuals are in serious trouble. Specifically, I show how probabilistic approaches run into a dilemma in characterizing probabilistic independence. The modified case also illustrates a difficulty in defining causal independence. I close with a suggestion for a strategy to handle this difficulty.

In assessing counterfactuals, should we consider circumstances which match the actual circumstances in all probablistically independent fact or all causally independent fact? Jonathan Schaffer argues the latter and claims that the former approach, advanced by me, cannot deal with the case of Morgenbesser’s coin. More generally, he argues that, where there is a difference between the two, his account yields our intuitive verdicts about the truth of counterfactuals where mine does not (Schaffer 2004: 307, n. 16). In this brief note, I explain how my approach deals with the case of Morgenbesser’s coin and argue that the situation is, in fact, the reverse. To keep things brief, I rely upon Schaffer’s paper for general explanation of the context of our debate.