Causation and Evolution

James Bronzan sent me a follow-up e-mail to my post based on his earlier comment. He agreed to let me quote it:

But again, it still seems to me that there’s likely a reason that we look for instances of causation to be associated with instances of correlation precisely because they are.  It turned out to be a good evolutionary strategy to do this — we adapted to the way the world is.  (Grossly coarse example: it was useful to go beyond “man, every time someone happens to eat that berry, he or she dies,” to “perhaps eating that berry causes death.”)…

Of course it doesn’t require that they be this way, or indeed that there aren’t other effects of causation that we don’t detect whatsoever.  But I’d posit that those effects didn’t turn out to be useful in decision making linked to survival, which suggests (to me, anyway) that the causation-correlation link is more prevalent or stronger.

I agree with James’ perspective to a point. I might even be caught making the same or similar arguments some day. But today I’ve decided to differ, if only slightly, for entertainment value. Plus I’d like to think I add an important nuance or two in what follows.

We actually can’t say that we are reacting to correlation when we intuit causation. Correlation is such a precise measure and, therefore, is only meaningful when talking about statistical analysis. I don’t believe our berry-eating ancestors were running regressions in their heads. Few of us do that today.

When it comes to statistical analysis and quantitative studies, one can speak precisely about correlation and causation. Linear models and their Gaussian assumptions reduce everything to correlations. There’s nothing left. The tools are blind to all else, though they’re very helpful when we have a theory upon which we choose to rely. Even in cases where models are not linear and assumptions of Gaussianity are relaxed, our intuition (by which I mean that of researchers) is based on the linear/Gaussian/causal world, so some of its distortions remain.

But back to the non-research, intuitive world we inhabit. On what do we base our causal inferences? It is correlations (maybe) but could be more or less than that. It is some vague interpretation of sensory data, I know not what. Yes it is evolved and therefore is (or was, rather) of great utility for reproduction.

Is it of great utility today and for other purposes? Yes, but it also leads to errors, a subset of which we notice. But very few cases in which it is applied casually are in areas relevant to reproduction. So there is this muscle we use in domains beyond that in which it was strengthened by evolution.

What can we say about the degree to which correlation (or whatever we do) is associated with causation in such domains? I think strictly speaking not much. We have only our bias and intuition. Beyond that I’m willing to say, “I don’t know.” Not everyone is comfortable with giving the unknown that much scope. It isn’t necessary that we do. But very often it is important if we do. Noticing this causality bias really can be an eye opener. Though if one goes too far it becomes hard to know anything.

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