Adding to @Bernhard 's answer, perhaps an example would help. Suppose we are interested in the relationship between height and weight in adult human males.
Statistically, we could use either height or weight as the dependent variable. The computer doesn't care. But it only makes sense to use weight as the DV. That "sense" comes from us and our knowledge of how people are, how we grow and so on and also from the notion that weight is more changeable than height.
We can sometimes rule out one direction of causation: It can't be that cancer causes smoking, if cancer happens later in time. (But that, alone, doesn't mean that the correlation between smoking and cancer implies causation).
More generally, we should not separate the statistics from the rest of the argument we are making. When we analyze data, we need to understand the data.