Colin Hales wrote:
>
> Hi!
> Assumptions assumption assumptions....take a look: You said:
>
> "Why would you say that? Computer simulations can certainly produce results you didn't already know about, just look at genetic algorithms."
>
> OK. here's the rub... "You didn't already know about...".
> Just exactly 'who' (the 'you') is 'knowing' in this statement?
> You automatically put an external observer outside my statement.
Of course, I was talking about the humans running the program, which I assumed is what you meant by "you" in the statement "If you could compute a scientist you would already know everything!" If there is no fundamental barrier to simple computer programs like genetic algorithms coming up with results we didn't expect or know about in advance, I see no fundamental reason why you couldn't have vastly more complex computer programs simulating entire human brains, and these programs would act just like regular biological brains, coming up with ideas that neither external observers watching them nor they themselves (assuming they are conscious just like us) knew about in advance.
> My observer is the knower. There is no other knower: The scientist who gets to know is the person I am talking about! There's nobody else around who gets to decide what is known... you put that into my story where there is none.
Like I said, when you wrote "If you could compute a scientist you would already know everything", I assumed the "you" referred to a person watching the program run, not to the program itself. But if you want to eliminate this and just have one conscious being, I see no reason why the program itself couldn't be conscious, and couldn't creatively invent knew ideas it didn't know before they occurred to it, just like a biological human scientist can do.
>
> A genetic algorithm (that is, a specific kind of computationalist manipulation of abstract symbols) cannot be a scientist. Even the 'no free lunch' theorem, proves that without me adding anything....
No it doesn't. The free lunch program only applies when you sum over all possible fitness landscapes, most of which would look completely random (i.e. nearby points on the landscape are no more likely to have nearby fitness values than are distant points--see the diagram of a random fitness landscape in section 5.3 of the article at
http://www.talkreason.org/articles/choc_nfl.cfm#nflt ), whereas if you're dealing with the subclass of relatively smooth fitness landscapes that describe virtually all the sorts of problems we're interested in (where being close to an optimal solution is likely to be better than being far from it), then genetic algorithms can certainly do a lot better than most other types of algorithms.
Anyway, I didn't say that a genetic algorithm can "be a scientist", just that if "you" are a human observer watching it run, it can come up with things that you didn't already know. I think a very detailed simulation of a human brain at the synaptic level, of the kind that is meant when people discuss "mind uploading" (see
http://en.wikipedia.org/wiki/Mind_uploading ) should in principle be capable of displaying all the same abilities as the biological brain it's a simulation of, including scientific abilities. Anyone who believes in scientific reductionism--that the behavior of complex systems is ultimately due to the sum of interactions of all its parts, which interact in lawlike ways--should grant that this sort of thing must be possible *in principle*, whether or not we are ever actually able to achieve it as a technical matter.
>but just to seal the lid on it....I would defy any computationalist artefact based on abstract symbol manipulation to come up with a "law of nature" ...
I take it you reject the idea that the brain is an "artefact" whose large-scale behavior ultimately boils down to the interaction of all its constituent atoms, which interact according to laws which can be approximated arbitrarily well by a computer simulation? (if space and time are really continuous the approximation can never be perfect, but it can be arbitrarily close)
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Received on Mon Sep 01 2008 - 23:31:21 PDT