I don’t understand what point you’re making with the computer, as we seem to be in complete agreement there. Nothing about the notion of ideals and definitions suggests that computers can’t have them or their equivalent. It’s obvious enough that computers can represent them, as you demonstrated with your example of natural numbers. It’s obvious enough that neurons and synapses can encode these things, and that they can fire in patterned ways based on them because… well that’s what neurons do, and neurons seem to be doing to bulk of the heavy lifting as far as thinking goes.
Where we disagree is in saying that all concepts that our neurons recognize are equivalent and that they should be reasoned about in the same way. There are clearly some notions that we recognize as being valid only after seeing sufficient evidence. For these notions, I think bayesian reasoning is perfectly well-suited. There are also clearly notions we recognize as being valid for which no evidence is required. For these, I think we need something else. For these notions, only usefulness is required, and sometimes not even that. Bayesian reasoning cannot deal with this second kind because their acceptability has nothing to do with evidence.
You argue that this second kind is irrelevant because these things exist solely in people’s minds. The problem is that the same concepts recur again and again in many people minds. I think I would agree with you if we only ever had to deal with a physical world in which people’s minds did not matter all that much, but that’s not the world we live in. If you want to be able to reliably convey your ideas to others, if you want to understand how people think at a more fundamental level, if you want your models to be useful to someone other than yourself, if you want to develop ideas that people will recognize as valid, if you want to generalize ideas that other people have, if you want your thoughts to be integrated with those of a community for mutual benefit, then you cannot ignore these abstract patterns because these abstract patterns constitute such a vast amount of how people think.
It also, incidentally, has a tremendous impact on how your own brain thinks and the kinds of patterns your brain lets you consciously recognize. If you want to do better generalizing your own ideas in reliable and useful ways, then you need to understand how they work.
For what it’s worth, I do think there are physically-grounded reasons for why this is so.
I don’t understand what point you’re making with the computer, as we seem to be in complete agreement there. Nothing about the notion of ideals and definitions suggests that computers can’t have them or their equivalent. It’s obvious enough that computers can represent them, as you demonstrated with your example of natural numbers. It’s obvious enough that neurons and synapses can encode these things, and that they can fire in patterned ways based on them because… well that’s what neurons do, and neurons seem to be doing to bulk of the heavy lifting as far as thinking goes.
Where we disagree is in saying that all concepts that our neurons recognize are equivalent and that they should be reasoned about in the same way. There are clearly some notions that we recognize as being valid only after seeing sufficient evidence. For these notions, I think bayesian reasoning is perfectly well-suited. There are also clearly notions we recognize as being valid for which no evidence is required. For these, I think we need something else. For these notions, only usefulness is required, and sometimes not even that. Bayesian reasoning cannot deal with this second kind because their acceptability has nothing to do with evidence.
You argue that this second kind is irrelevant because these things exist solely in people’s minds. The problem is that the same concepts recur again and again in many people minds. I think I would agree with you if we only ever had to deal with a physical world in which people’s minds did not matter all that much, but that’s not the world we live in. If you want to be able to reliably convey your ideas to others, if you want to understand how people think at a more fundamental level, if you want your models to be useful to someone other than yourself, if you want to develop ideas that people will recognize as valid, if you want to generalize ideas that other people have, if you want your thoughts to be integrated with those of a community for mutual benefit, then you cannot ignore these abstract patterns because these abstract patterns constitute such a vast amount of how people think.
It also, incidentally, has a tremendous impact on how your own brain thinks and the kinds of patterns your brain lets you consciously recognize. If you want to do better generalizing your own ideas in reliable and useful ways, then you need to understand how they work.
For what it’s worth, I do think there are physically-grounded reasons for why this is so.