Tyler Cowen: belief

Transcript context

…This is interesting. When we started this out, one of the big puzzles that we had was, it’s fine to say that children are learning like scientists, but then the question became, how are scientists learning? When I started this project, a lot of the philosophers of science said, “Kuhn showed that there was nothing systematic you could say about that. It’s just sociology.” But interestingly, during the time that I’ve been working, there’s been this real change in the way that people think about philosophy of science. We have some good computational models of how scientific theory change works. It turns out that those apply to children as well. The specific thing that I’ve looked at is, what is it that scientists do? Here’s this big, hard problem. All we seem to get from the world are a bunch of photons at the back of our retina and disturbances of air in our ears, and yet, children know about people and things, and scientists know about quarks and quantum phenomena. How do we ever get from the data to the theory? One subcategory of that is, how do we ever get causal structure which is so important in science? How do we ever figure out what causes what just from a bunch of data that we have? What’s happened is that philosophers of science and computer scientists have found some systematic ways that you could talk about that. Scientists — I think, mostly, not necessarily consciously, but just as part of what they do — and little kids are looking at data and systematically figuring out what kind of structure out there in the world could have caused this pattern of data. That’s not the only thing, of course, that’s going on in science. There’re lots of other things, too, but it’s at least one central thing going on in science that we’ve started to really understand. Of course, it makes sense that scientists have the same brains that we had in the Pleistocene. Something in those brains must be enabling them to do what they do, in addition to all sorts of other institutional and social things. It’s something about this deep capacity to figure out the structure of the world — the world model, as the AI people say — from data. 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.…

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