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Comment by yters | Hacker News Reader

If intelligence is not computable then by definition deep learning is not capable of human intelligence. There are any reasons to think intelligence is beyond computation: Gödel's incompleteness theorems, no free lunch theorem, data processing inequality, Solomonoff induction and Kolmorov complexity is uncomputable, the halting problem, if the mind is code which program are you, all programs are finite yet we can think about infinity, split brain but unified consciousness, the inherent difference between third person and first person descriptions, reasoning about paradoxes, the ability to know we are wrong, the ability to write AI programs, the whole connectionist vs. modules problem Fodor points out, and probably many more.

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I don't want to get into a philosophical debate here, but please don't overstate the meaning of mathematical theorems.

For example, Gödel's incompleteness theorem is a technical result stating that certain definitions of "model theoretic truth" in classical set theory are incompatible with certain other notions of "truth as provability". Both the statement and its consequences have been so massively oversold for most of the past century that you should never use it in a discussion - think of it as a logical version of Godwin's law.

Similarly, no free lunch type theorems are formally the same as the statement that you cannot compress all n byte sequences into less than n bytes, which is really obvious for cardinality reasons. Again, there is no magic, just clever reductions.

The argument behind the halting problem also applies to your brain and anything that is somehow an abstract model of computation. More fundamentally, the fact that the self halting problem is undecidable is simply an instance of Cantor's theorem, it's not something that can be avoided.

Mathematical logic and therefore computers can be used to talk about infinity and more. Logical "paradoxes" are not a problem either. Some may be genuine proofs of inconsistency of some logical theories and others are simply theorems. The usage of the word "paradox" in natural language is simply imprecise.

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I could go on, but really I don't take offense at any particular point. What bothers me is that you seem to be overselling mathematical results to argue a non-mathematical point... If you really want to apply, e.g., Gödel type theorems to discussions about your brain, you would first have to argue that the assumptions of Gödel's theorems apply. For instance, you could argue that the definition of model based truth in Peano arithmetic is something that your brain can decide. Then it would follow that what your brain does is uncomputable.

Nobody has ever established that human intelligence is not computable. Human intelligence can't solve any of the well-defined problems you mention, or transcend the limitations of any of those theorems. Don't mistake the idea of an idealized perfect intelligence with the very limited and finite ones that we actually possess. Asking what God could do always leads to madness.

Some of what you mention are what I consider non-well-defined philosophical problems, which really have no bearing on the ability to create algorithms that could pass the Turing test and are outside of the scope of a discussion on the practicality of creating AGI.

No one has ever established human intelligence is computable. A number of the problems I mention just have no computable corollary. E.g. As far as computers are concerned there is no such thing as truth. For us humans to make that claim is inherently nonsensical (I.e. Is it true there is no truth?)

The default position here is that human intelligence is computable, since we have some 7.5 billion biological computers clearly implementing human intelligence. Arguments to the contrary typically rest on a belief in mind-body dualism (popularly disguised as "quantum effects" these days).

I see from another post of yours that you are religious, which is a common personal reason to assume a form of dualism as at least central tenets in the Abrahamic religions seem to require it. Do you see dualism necessary for your position of human intelligence being incomputable, and if so could you reference an argument you would find compelling also for readers whose religion (or lack thereof) does not necessitate dualism?

If you don't see dualism as necessary for the possibility of human intelligence being incomputable, could you open up your thinking on this?

I apologize for being so forward, but I worry some might read your comments without realizing that they might rely on unshared assumptions.

Yes, of course dualism is necessary. You have the causality wrong. I used to be a computational mind person an believe in monism. But the listed reasons have convinced me otherwise. Essentially computation cannot create information. So, if information exists then so does at least one uncomputable process, which obviously implies dualism. Same direction of causality for my religiosity. Since computationalism is untenable, then religion must be true, not visa versa for me.

Also you beg the question right at the beginning of your response.

Please at least read the Wikipedia articles on computability (https://en.wikipedia.org/wiki/Computability) and hypercomputation (https://en.wikipedia.org/wiki/Hypercomputation) before making arguments like this. There is literally zero evidence that anything in our known universe can perform hypercomputation - and that includes all quantum mechanical effects that we've been able to measure. So the Bayesian prior for human intelligence being computable is somewhere near 100%, and it would take very, very extreme evidence to contradict that.

"Is it true there is no truth?" is not even close to a compelling argument, there are rigorously defined notions of truth within any of the eminently computable logical frameworks that we use.

Humans seem to perform hyper computation all the time. Eg in programming we can decide a whole lot of programs halt. We seem to do something close to Solomonoff induction. Etc. computational presuppositions are the only reason to not find this compelling, and materialism and hard atheism are the only reasons to be committed to computationalism.

No, that's a misunderstanding of what hypercomputation is.

If you can write down or talk yourself through a proof of why a program will halt, you have solved a computable problem. By definition. When you say "we can decide a whole lot of programs halt", you're talking about plain Jane computation.

If you have knowledge that any program that I give you will or will not halt, then you're a hypercomputing oracle for the halting problem, and you can do magic, basically.

There's a world of difference between the two situations. And I'm fairly sure (but not positive) that there's no way for you to prove in finite space and time that you are an oracle for the halting problem.

Edit: for more on that last bit, see https://pdfs.semanticscholar.org/19f9/0c34cdda43efdcf0831b2f...

Regarding truth, no program can know if it is consistent, so truth goes right out the window.

I think the major problem is to think of "intelligence" as a problem in "computation".

We are so used to this framing, that it may seem foreign. Others will argue, that in principle it is a problem of computability but in extreme almost every problem is, but that is not necessarily how we frame other problems. I'd say "intelligence" is a control problem (as in controlling a robot). This framing, though subtle, makes the entire problem quite different. You no longer talk about computability but you talk about survival in "high temperature thermal bath" (or otherwise called "physical reality"), full of unpredictability and dangerous stuff.

When you frame it like this, it is clear we have not even began to address the problem properly, not to even mention solving it.

Aren't other problems getting framed that way, too? Car driving is not inherently a problem in computation, but is becoming one. Robotic control (or other control problems) are certainly being solved by computation.

Perhaps treating AI as a derivative of the control branch of computation could practically help speed up progress in some areas, but it shouldn't fundamentally change its nature.

Well this is exactly my point. A lot of problems are currently framed as computation problem. As much as it might be useful for some, I'd argue that we should be careful with this.

We get all the great marvels of deep learning, but robots remain stupid as bricks over 30 years of Moore's law. To me this (Moravec's paradox) is a signal that we are doing something wrong, and typically we do things wrong when they are not framed properly.

Ironically, the frame problem is one of those things AI cannot solve. The myopic belief in computational intelligence is a result of our materialism, which in turn is a result of our unwillingness to acknowledge God and live according to His will, which is ultimately best for us.

This is Penrose's argument. One issue with this line of thinking is that it confuses a system which produces infallible proofs and the human brain. None of those theorems actually apply to people; we may gain quite a bit by being wrong sometimes.

We aren't infallible, but that is different than the inconsistency of a formal system. Insistency means the very concept of truth is nonsensical, since an inconsistent system can prove everything. It is fallacious to equivocate the two.

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