Strong AI: The Gödel Problem

In my previous post, I alluded to an argument made by John Lucas and popularised by Roger Penrose against the possibility of AI, and this is that Gödel's Incompleteness Theorems suggest that even weak AI is impossible. We could never make a computer system that behaved intelligently.

Loosely put, Gödel's Incompleteness Theorems put fundamental limits on what can be achieved by working with formal systems.

In particular, some argue that they show that formal systems can never be as intelligent as human beings. In this post, I argue against this view and propose that humans are subject to the same limitations.

Strong AI: Naturalism and AI

In this article, I want to examine the issues presented by the problem of consciousness when examined from a naturalistic or physicalist point of view. What I present in this article is probably not a knock-down argument proving the computational theory of consciousness (Strong AI) within this framework. Rather it shows that the alternatives are rather problematic.

Strong AI: The Illusion of Real Consciousness

Perhaps we are no more conscious that the automatons we imagine in our thought experiments when considering questions about artificial intelligence and philosophy of mind.

In this view, all we have to explain is why we believe we are conscious, without explaining why we actually are. "Real consciousness" is an illusion, and consciousness is simply comprised of the functions it affords, namely the ability to be self-reflective, to deliberate, to perceive the world, etc., in such a way that the entity believes itself to have a subjective experience or "real consciousness".

If we allow the assumptions of Weak AI, namely that it should be possible in principle to create a computational artificial intelligence which has all the functionality of a human brain, then all of these abilities can be achieved. If we deny Strong AI, then we must suppose that the AI will falsely believe itself to be conscious.

If we understand how artificial intelligences might believe themselves to be conscious, then we can understand by analogy why biological intelligences might share those beliefs. In other words, if we have explained our belief that we are conscious (by analogy to our artificial intelligences), then what, exactly, remains to be explained?

Strong AI: Evolutionary Parsimony

In this post, I will attempt to make an argument for Strong AI from an evolutionary perspective. Please keep the assumptions stated in my previous post in mind.

Strong AI: The Story So Far

Let's take Strong AI as the viewpoint that the essential capabilities of the brain are computational, meaning that were we to reproduce these same computational functions in an artificial machine such as a silicon computer, then that machine would have a mind just as real, just as conscious as a human mind.

In my recent posts, I have argued against some common criticisms of this view.

I have shown how The Chinese Room may establish that a piece of computational hardware cannot become conscious, but it does not show that the software running on that hardware is unconscious.

I have shown that the concept of a philosophical zombie does nothing to cast doubt on Strong AI, for if Strong AI is true then philosophical zombies are probably logically incoherent. Philosophical zombies are nothing more than a restatement of the viewpoint that Strong AI is not true.

I have shown that qualia, with specific reference to Mary's Room, do not in themselves disprove physicalism, but are probably simply brain states which act as labels for certain percepts and concepts.

I have agreed with Alvin Plantinga that the mind and body are distinct entities (like hardware and software), but argue that this is a conclusion of no consequence which no thoughtful person should be surprised by and which does not imply that the soul can survive the destruction of the body.

I have also explained why I disagree with the assertion that semantics cannot be derived from syntax, and sketched how I think semantics can be viewed as a special case of syntax.

What I have not done yet is given some positive reasons for the suspicion that Strong AI is true. In my following posts I will attempt to do so.

In Defence of Strong AI: Meta-meaning

Yesterday's post was quite long and wide-ranging, with a lot of examples etc. It focused specifically on how it might be possible to get semantics from syntax, particularly with reference to The Chinese Room thought experiment.

However I feel that I could sum up my position more succinctly by looking at the meaning of the word "meaning" itself.

In Defence of Strong AI: Semantics from Syntax

Is it possible to get semantics from syntax?

If it were impossible to get semantics (meaning) from syntax (symbols and formal rules for manipulating them) then we probably wouldn't have bothered broadcasting the Arecibo image to the universe in the hope of communicating with aliens.

Without any way to explain the meaning of this image, it seems to consist of syntax alone. Whether it could be deciphered by aliens in practice or not, it at least seems possible in principle, which seems to suggest that it may be possible in some cases to derive semantics from syntax.

The assertion that you can't, that there is no way to get from syntax to semantics, is perhaps the strongest response from John Searle to the systems/virtual mind refutation of his Chinese Room thought experiment (as outlined in my post on the topic).

Searle illustrates his point by saying that if he is in The Chinese Room and has a formal system of rules (syntax) for manipulating Chinese words, he has no way to get from this syntax to the semantics of what is being said. If he has no way to do this, then how can the system do it?

In Searle's view, the systems/virtual mind reply to the Chinese Room is just hand-waving until this is explained.

Let's see if I can attempt to do just that.