Judea Pearl on Causal Models vs Probabilistic Models.

(Pearl & others, 2000)

Causal models (assuming they are valid) are much more informative than probability models. A joint distribution tell us how probable events are and how probabilities would change with subsequent observations, but a causal model also tells us how those probabilities would change as a result of external interventions - such as those encountered in policy analysis, treatment management, or planning everyday activity. Such changes cannot be deduced from a joint distribution, even if fully specified.

~Judea Pearl