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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