Alison Gopnik: belief

Transcript context

…Are human scientists ever Bayesian? I think of them as not very Bayesian at all, that they’re mostly pretty stubborn. It’s interesting. One of the things that we’ve looked at is whether little kids are Bayesian, and you might be even more surprised to find that little kids are actually being pretty rational Bayesian, but a lot of it depends on how you ask. If you asked a three-year-old, “Do you think that this pattern of conditional dependencies is giving you a confounding causal structure?” They would probably not give you a very sensible answer. Even when you ask scientists that, they don’t give you a very sensible answer. But when you look at their actual practice, what you see is that, in fact, kids, for example, are Bayesian, and so are scientists. Now, the thing is that, in fact, in many respects, kids are better Bayesians than scientists, but a lot of it depends on your prior. If you have, as they say, a very peaked prior, you have a lot of experience, you have a lot of reason to believe that this prior assumption is right, then it’s rational not to change it when you just have a little bit of evidence. You should require a lot of evidence to overturn something that you have a lot of confirmation for. It’s interesting that the kids, actually, are better at solving problems that involve unusual outcomes than the scientists are. I think what happens in science — we’ve just been doing some work about this — is that there’s also a social factor, where having a big distribution of people who are more likely to go with the prior versus people who are more likely to go with the evidence, which seems to be true in science, that collectively can get you to the right answer. There’s no arbitrary principle you can have about when should you abandon the theory and when should you hold onto it. I think of the kids as much more Bayesian than the scientists, and here’s what worries me about the scientists. When they revise their views, the direction in which they move is almost always predictable. If they’re, say, thinking over decades, how much does the money supply matter? They’ll move a bit in the direction of thinking it matters. Then they’ll move a bit more. Then finally, they might decide, well, it matters quite a bit. It shouldn’t be predictable if they’re Bayesian. It should be more like a random walk. Basically, they’re stubborn. Then what I observe, if they’re proven to be wrong, they don’t usually admit it, whereas a child might. They just start working on something else. That, too, is a funny way of dealing with being wrong, right?…

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