Daniel Hausman and James Woodward claim to prove that the causal Markov condition, so important to Bayes-nets methods for causal inference, is the ‘flip side’ of an important metaphysical fact about causation—that causes can be used to manipulate their effects. This paper disagrees. First, the premise of their proof does not demand that causes can be used to manipulate their effects but rather that if a relation passes a certain specific kind of test, it is causal. Second, the proof is invalid. Third, the kind of testability they require can easily be had without the causal Markov condition
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