 Conditioning on a variable involves analyzing the values of other variables for a given value of the conditioned variable.In the first example, conditioning on B implies that observations for a given value of B should show no dependence between A and C. If such a dependence exists, then the model is incorrect.Non-causal models cannot make such distinctions, because they do not make causal assertions.