 Note that the Causal Markov Condition tells us that certain causal structures give rise to relations of conditional probabilistic independence. The Causal Markov Condition never entails probabilistic dependence. For purposes of causal inference, the Causal Markov Condition is often supplemented by a further principle governing when probabilistic dependence is to be expected. One such principle is the Faithfulness Condition (Spirtes et al. 2000) which says that only the probabilistic independencies entailed by the Causal Markov Condition are present. Looked at another way, the Faithfulness Condition says that when we find a relation of conditional probabilistic independence, we should infer a causal structure that entails that independence relation rather than one that doesn’t.