You misunderstand the result Penrose has shown. There are plenty of aperiodic tessellations of the plane that can be computationally generated. The issue is whether a computer can, in all cases, determine if a set of shapes can tile aperiodically.
I don't understand the second bit. But, no. Computability has very specific definition. Getting a solution to an uncomputable problem isn't generally hard. It is trivial to create a program that will solve the halting problem for an infinite class of cases. The issue is that such solutions can be shown not to be general over all cases.
> is that we have no way of proving that qualia won't exist for an artificial intelligence
You misunderstood my objection. The issue is not whether we can prove such a thing, but can we differentiate between different information processing systems in arguments that qualia exist at all. You assume qualia is a thing that brains do. On what basis do you assume anyone other than you have them, such that implies that no other systems do?
Qualia is one of those topics academics tend to roll their eyes at when it is brought up. Because it appears to do a lot, but in most cases is a variation of 'because I feel like it should be true'.
Ultimately these arguments come down to qualia. But there is no reason to think qualia is a) present in other brains except your own, but b) not present in any non-brain information processing system. Philosophers of mind have tried to make that argument, but end up appealing to intuition.
In terms of computability, folks like Boden and Sloman showed in the 90s that emotion is compatible with computability. Even more so, that emotion is implementable in symbolic computation. Of course, one could declare such systems have no qualia of emotion. But can you do more than declare that, while not simultaneously creating arguments that could apply to other brains?
I get you are working on intuition. But there's fifty years of actual research been done on this. Waving your hands and appealing to your 'humble opinion' isn't how scholarship works.
> the brain does far more than performing computation
In your opinion? Can you be more specific, and give examples of things the brain does that are not computable?
This is trivially true in some senses, neurones have analogue responses, that the biology does a good (but not perfect) job of thresholding. But then, the same thing can be said of transistors. It's just we're able to engineer their analogue responses out much more successfully than evolution has. It is also true that the brain is connected to a much broader system which is undoubtedly analogue (i.e. the body), but then again, it isn't clear that isn't true of any non-abstracted computer.
Comparing theoretical and idealised computing to embodied brains might feel insightful, but it doesn't actually resolve any of the real issues in the philosophy of AI.
Also, a BS in CS isn't a good minimum qualification for competency in the philosophy of AI. I wouldn't read much into that.
Nope. Can I suggest you read Penrose again with a little more critical thought.
There are problems it is possible to prove are not computable. But can you prove that human beings can solve them?
Tessellation of the infinite plane? Please demonstrate a person that can solve this (i.e. not that they have a > 99.9% chance of being able to do it, or that you can show they can start out pretty successfully and you assume they'll always stay ahead of the game).
Bear in mind when working out if a computer can solve a given problem (i.e. is it mathematically computable), we're not trying to work out if it can ever solve it, or even if it can solve it in infinitely many cases, or even in an arbitrarily high proportion of cases. We're working out if it can be proven that it is (not) guaranteed to find a correct solution in all cases. There's just no way to make those judgements of a human being.
So instead, mathematical analysis of computation is compared against intuition arguments from the evidence that human beings have good, reliable strategies for solving some of them. Unsurprisingly, the brain comes off pretty well in that comparison!
Penrose was big on handwaving and appeal to quantum magic, but not very good on the specific arguments to back up his claim.
I found this article to be a huge bag of misconceptions about AI, computation, and the actual claims of AI professionals. As an argument against hyperbolic media mischaracterisation, it might be reasonable. But like Penrose, it manages a long and condescending argument from intuition that fails to take seriously the actual claims being made.
I don't understand the second bit. But, no. Computability has very specific definition. Getting a solution to an uncomputable problem isn't generally hard. It is trivial to create a program that will solve the halting problem for an infinite class of cases. The issue is that such solutions can be shown not to be general over all cases.