On Sat, Feb 5, 2011 at 12:27 PM, Colin Hales
<c.ha...@pgrad.unimelb.edu.au> wrote:

>  I think perhaps the key to this can be seen in your requirement...
> " Doing this is equivalent to constructing a human level AI, since the
> simulation could be given information and would respond just as a human
> would given the same information."
> I would say this is not a circumstance that exemplified human level
> intellect. Consider a human encounter with something totally unknown but
> human and AI. Who is there to provide 'information'? If the machine is like
> a human it shouldn't need someone there to spoon feed it answers. We let the
> AGI loose to encounter something neither human nor AGI has encountered
> before. That is a real AGI. The AGI can't "be given" the answers. You may be
> able to provide a software model of how to handle novelty. This requires a
> designers to say, in software, "everything you don't know is to be known
> like this ....". This, however, is not AGI (human). It is merely AI. It may
> suffice for a planetary rover with a roughly known domain of unknowns of a
> certain kind. But when it encounters a cylon that rips it widgets off it
> won't be able to characterize it like a human does. Such behaviour is not an
> instance of a human encounter with the unknown.

I am considering a special type of AI, an upload of a human brain. A
"bottom up" AI, if you like. SPICE allows you to simulate a complex
circuit by adding together simpler components. You can construct a
simulated amplifier out of simulated transistors, resistors,
capacitors etc., then input a simulated signal, and observe the
simulated output. You construct an uploaded brain out of simulated
neurons, input a simulated signal to simulated sense organs, and
observe the simulated output to simulated muscles. The input signal
could be a question and the output signal couldbe verbal output in
response to the question. If the SPICE model is a good one its output
would be the same as the output of a real circuit given the same
input. If the brain upload model is a good one its response to
questions would be the same as the responses of a biological brain.
For example, you could tell it the result of experiments, it would
come up with a hypothesis, propose further experiments for you to do,
then modify the hypothesis depending on the result of those
experiments. There is no specific novelty-handling model: the upload
is merely an accurate model of brain behaviour, and the
novelty-handling emerges from this. The analogy is that the SPICE
software does not have a specific model for what to when the input is
sine wave, what to do when the input is a square wave, and so on, but
rather the appropriate output is produced for any input given just the
models of the components and their connections.

> Humans literally encounter the unknown in our qualia - an intracranial
> phenomenon. Qualia are the observation. We don't encounter the unknown in
> the single or collective behaviour of our peripheral nerve activity. Instead
> we get a unified assembly of perceptual fields erected intra-cranially from
> the peripheral feeds, within which the actual distal world is faithfully
> represented well enough to do science.
> These perceptual fields are not always perfect. The perceptual fields can be
> fooled. You can perhaps say that a software-black-box-scientist could guess
> (Bayesian stabs in the dark). But those stabs in the dark are guesses at (a)
> how the peripheral siganlling measurement activity will behave, or perhaps
> (b) a guess at the contents of a human-model-derived software representation
> of the external world. Neither (a) or (b) can be guaranteed identical to the
> human qualia version of the the external distal world _in a situation of
> encounter with radical novelty (that a human AI designer has never
> encountered). This observational needs of a scientist are a rather useful
> way to cut through to the core of these issues.
> The existence or nature of 'qualia' that give rise to (by grounding in
> observation) empirical laws, are not predicted by any of those empirical
> laws. However, the CONTENTS of qualia _are_ predicted. The system
> presupposes their existence in an observer. The only way to get qualia,
> then, is to do what a brain actually does, not what a model (empirical laws)
> of the brain does. Even if we 100% locate and model the atomic-level
> correlates of consciousness (qualia), that MODEL of correlates is NOT the
> thing that makes qualia. It's just a model of it. We are  not a model of a
> thing. We are, literally, something else, the actual natural world that
> merely appears to behave (in our qualia) like a model. In the case of the
> brilliant model "electromagnetism", our brains have electromagnetism
> predicted by the model. My PhD thesis is all about it. Humans get to BE
> whatever it is that behaves electromagnetically. Conflating these two things
> (BEing and APPEARing) is the bottom line of the
> COMP is true belief.
> Note that none of this discussion need even broach issue of the natural
> world AS computation (of or not of the kind of computation happening in a
> digital computer made of the natural world). This latter issue might be
> useful to understand the 'why' of qualia origins. But it changes nothing in
> a decision process leading to real AGI.
> BTW my obsession with AGI originates in the practical need to make a
> 'generic AI making machine'. One AGI makes all domain specific AI.

I don't accept that computers cannot have the same qualia as brains,
but even if that is true, it is possible to do science without direct
observation. A written description of the results of an experiment is

Stathis Papaioannou

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