Jim Manzi: Correlation, Causation, Understanding, and Predicting

Jim Manzi, curious as always (especially about how to evaluate government policies), tries to plumb the problem of causality. Here’s where he begins:

Consider two questions:

  1. – Does A cause B?
  2. – If I take action A, will it cause outcome B?

I don’t care about the first, or more precisely, I might care about it, but only as scaffolding that might ultimately help me to answer the second.

I’ll risk going Manichaean here in an effort at (simplistic) clarity: I think this encapsulates a key difference between scientists and engineers.

Scientists want to understand how something works — not just “does A cause B?” but “what is the mechanism whereby A causes B?” Successful prediction is valuable (mainly? only?) because it validates or invalidates that understanding. Their main goal is to build coherent theory and understanding. Prediction is a happy by-product and necessary corrective.

Engineers want to understand how something works so that they can predict things — and create things that capitalize on that predictive power. They’re perfectly happy if they can predict successfully without understanding why the prediction works. Coherent theory is generally necessary to achieve this — they need to understand how things work — but it’s not their ultimate goal. Theory is a necessary evil.

An assertion of causality requires both. You need to show that B follows A reliably, but to be confident of causation, you need to explain — really tell a story — about how that causality works.

Both of these approaches are necessary and proper, of course, and they’re complementary. But I’d suggest that theory — the goal of science and most scientists — is what really matters in the long run. It’s easy enough to predict that the sun will rise in the east every day. Successfully predicting that yields many happy benefits. But understanding why — heliocentrism, earth rotation, gravity, momentum, etc. — now that is really profound. That coherent theory provides engineers with their necessary evil, so they can create and capitalize on further successful predictions.

With his “I don’t care about the first,” Jim puts himself squarely in the “engineers” camp that I’ve (again simplistically) described. Don’t get me wrong: I’m quite certain that Jim Manzi is quite curious and hungry for understanding (even while he’s skeptical about our ability to understand how complex human systems work). But by putting himself in that camp, he is aligning himself with, and providing aid and comfort to, a group that actively distrusts and dislikes egghead elitist types with all their fancy theories about evolution and climate and yes, economics. He aligns himself with a group that doesn’t really care about understanding, that just wants to know “which button should I push?”

It’s a group that tends to come up with answers like “Just cut taxes.”

Cross-posted at Angry Bear.






6 responses to “Jim Manzi: Correlation, Causation, Understanding, and Predicting”

  1. Curt Avatar

    Not sure I agree with your take on Manzi here. He recognizes that it’s very hard to truly understand patterns, and he advises for lots of experiments to try to figure out what’s really going on, what really works. Problem for economics is that it’s hard to do any macro experiments. I don’t know his political stance, but intellectually I don’t think he stands for simplistic answers based on unverified ideas.

  2. The Arthurian Avatar

    Great post. The (only) important thing is to understand how it (the economy) works. Lacking this essential step, nothing remains but the assertion of assumptions.

    You said it really well.

  3. Jim Manzi Avatar
    Jim Manzi

    Thanks for the thoughtful comments. I published a book in May called Uncomtrolled, and roughly the first 100 pages are devoted to the philosophy of science it’s relation to understanding causality in human social systems. I spend a lot of time on the relationship between theory and experiment.

    Jim Manzi

  4. Curt Avatar

    It seems like your claim here is that the engineering mindset – ‘find patterns that work’ – leads to simplistic economic stances i.e. “one size fits all – just cut taxes”. I’d say this is just not very true. It’s valuable to come up with patterns that work even if you don’t completely understand why – and I don’t think engineers are fixated on “one size fits all”, particularly when evidence suggests cases where the pattern doesn’t work.

    I think “one size fits all” people are not all that interested in evidence, which is much more problematic than an engineering mindset.

  5. […] I said recently, science is about really understanding how things work — telling a convincing causative story […]

  6. […] stuff that you’d think Jim would have looked at and considered if he really wanted to understand what was going […]