They're different questions to some extent. In the statistical literature on causality, the counterfactual definition is almost universally accepted: if you do

They're different questions to some extent. In the statistical literature on causality, the counterfactual definition is almost universally accepted: if you do X then Y happens, but if you wouldn't have done X, Y wouldn't have happened. So the main challenge that statisticians are tackling is not the ontological question of whether causality can really be said to exist in the world, but rather the practical question of how to make measurements performed at different times, in different places, on different people, using different machinery, as comparable as possible.