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It doesn't assume that -- it rests solely on the idea that brains are physical objects. This is empirically verified by every single experiment run on a human brain. More generally, it's been borne out on every noun that interacts with the physical world.
"Humans aren't computers" is irrelevant. Brains are physical arrangements of atoms that are capable of intelligently solving problems. This assumes nothing.
(For completeness: you may be completely right about 2. You're sort-of-right about 3, in that the assumption was made and the assumption was mistaken. But I don't think you're right that the current approach avoids singularity. There are absolutely recursive feedback loops in improving the current implementation of AI, because improving AI is made out of tasks, and we can get AI to do tasks. But you're right that the original thesis had a much more directly integrated feedback loop.)
The human brain is made up of very different materials than a datacenter. It is entirely possible that the physical structure of the brain is necessary to create intelligence, and that this structure requires materials which certain properties. Maybe a digital simulation will just always require orders of magnitude more data and power than the real, physical thing.
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This is missing the part where the human brain is an exceptionally well-tuned physical object shaped by millenia of evolutionary pressures that arguably constitute a training set vastly bigger than the laws of physics as we currently understand them say is possible to match with an artifical model, much less do any meaningful computation with.
It is also missing the part where the human brain is the most complicated object in the universe, as it is the only currently known object capable of of understanding these questions well enough to even ask them. And even it does not fully understand itself.
That's a bit too restricted: animal brains in general are extraordinarily skilled at learning what's necessary for success in their environments.
Phrasing it in terms of human brains make it seem some spectacular, rare success of evolution, and let's you rest on anthropocentric biases. But what about other primates? Dogs, rats, birds, cuttlefish? Some have radically different architectures than mammal brains, and yet they're extremely intelligent, moreso than humans, within the demands of their particular niche.
The question should be whether AI is able to match the intelligence of any animal that has a CNS. Can an AI be as smart as a pigeon? Currently, it's not, within the scope of the physical world and the rewards the pigeon is seeking. That's something that's interesting and under considered.
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Not true: a group of human brains, or a human + tools|AI, or humans + tools|AI, are smarter and more complicated.
Panpsychism is not a parsimonious theory.
Why not?
The question that spawned this thread
is much less important if AI can’t, but a single human-AI hybrid can. For example
Some radiologists would always be employed, but much less who work much more efficiently.
We could even get exponentially increasing intelligence, although only by directly linking an AI chip to a human brain.
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