No because you can never know for sure that there isn't a latent factor C which is the real causal factor and A is merely correlating with it (if we presume causality to exist at all, which is a pretty standard assumption).
We can compose DAGs that control for the factors we do know about, but it's impossible to exhaust or even know all possible latent processes that are impacting the outcome.
E.g. to show that A does not cause B, while B (or a latent factor B correlates with) causes A?
When people say that the study can equally be interpretted as cannabis disorder causes depression and as depression causes cannabis disorder, can't statistics show that these two hypothesys are not equal?
