In a Bayesian model there's no such thing as having no priors, that's the problem with arguing against Bayesian human reasoning with a model that can't capture the richness of human priors (which means modelling all relevant knowledge and intuition, including innate human instincts). And human priors include very strongly-held ones like "the world is basically comprehensible, governed by rules that we can discover and understand." We cannot prove that, but to the extent that we are wrong about it, all cogitation is useless, so we assume it.
Our beliefs about "what is a bowl" include that it is an instrumental concept created by other agents similar to us in order to facilitate communication. This justifies very strong priors that it will be a simple concept and easy to generalize from small numbers of examples, at least for us. All this just by virtue of being a common word. So I don't see any way to argue that human behaviour is non-Bayesian here unless one ignores relevant prior information or ignores the decision theory question "what is the consequence of being wrong about what a bowl is".
In a Bayesian model there's no such thing as having no priors, that's the problem with arguing against Bayesian human reasoning with a model that can't capture the richness of human priors (which means modelling all relevant knowledge and intuition, including innate human instincts). And human priors include very strongly-held ones like "the world is basically comprehensible, governed by rules that we can discover and understand." We cannot prove that, but to the extent that we are wrong about it, all cogitation is useless, so we assume it.
Our beliefs about "what is a bowl" include that it is an instrumental concept created by other agents similar to us in order to facilitate communication. This justifies very strong priors that it will be a simple concept and easy to generalize from small numbers of examples, at least for us. All this just by virtue of being a common word. So I don't see any way to argue that human behaviour is non-Bayesian here unless one ignores relevant prior information or ignores the decision theory question "what is the consequence of being wrong about what a bowl is".