Ed,
I wasn't trying to justify or promote a 'divide'. The two worlds must be
better off in collaboration, surely? I merely point out that there are
fundamental limits as to how computer science (CS) can inform/validate
basic/physical science - (in an AGI context, brain science). Take the
Baars/Franklin "IDA" project. Baars invents 'Global Workspace' = a
metaphor of apparent brain operation. Franklin writes one. Afterwards,
you're standing next to to it, wondering as to its performance. What
part of its behaviour has any direct bearing on how a brain works? It
predicts nothing neuroscience can poke a stick at. All you can say is
that the computer is manipulating abstractions according to a model of
brain material. At best you get to be quite right and prove nothing. If
the beastie also underperforms then you have seeds for doubt that also
prove nothing.
CS as 'science' has always had this problem. AGI merely inherits its
implications in a particular context/speciality. There's nothing bad or
good - merely justified limits as to how CS and AGI may interact via
brain science.
----------------
I agree with your :
"/At the other end of things, physicists are increasingly viewing
physical reality as a computation, and thus the science of computation
(and communication which is a part of it), such as information theory,
have begun to play an increasingly important role in the most basic of
all sciences./"
I would advocate physical reality (all of it) as /literally /computation
in the sense of information processing. Hold a pencil up in front of
your face and take a look at it... realise that the universe is
'computing a pencil'. Take a look at the computer in front of you: the
universe is 'computing a computer'. The universe is literally computing
YOU, too. The computation is not 'about' a pencil, a computer, a human.
The computation IS those things. In exactly this same sense I want the
universe to 'compute' an AGI (inorganic general intelligence). To me,
then, this is /not/ manipulating abstractions ('aboutnesses') - which is
the sense meant by CS generally and what actually happens in reality in CS.
So despite some agreement as to words - it is in the details we are
likely to differ. The information processing in the natural world is not
that which is going on in a model of it. As Edelman said(1) "/A theory
to account for a hurricane is not a hurricane/". In exactly this way a
computational-algorithmic process "about" intelligence cannot a-priori
be claimed to be the intelligence of that which was modelled. Or - put
yet another way: That {THING behaves 'abstract- RULE-ly'} does not
entail that {anything manipulated according to abstract-RULE will become
THING}. The only perfect algorithmic (100% complete information content)
description of a thing is the actual thing, which includes all
'information' at all hierarchical descriptive levels, simultaneously.
--------------------
I disagree with:
"But the brain is not part of an eternal verity. It is the result of
the engineering of evolution. "
Unless I've missed something ... The natural evolutionary 'engineering'
that has been going on has /not/ been the creation of a MODEL
(aboutness) of things - the 'engineering' has evolved the construction
of the /actual/ things. The two are not the same. The brain is indeed
'part of an eternal verity' - it is made of natural components operating
in a fashion we attempt to model as 'laws of nature'. Those models,
abstracted and shoehorned into a computer - are not the same as the
original. To believe that they are is one of those Occam's Razor
violations I pointed out before my xmas shopping spree (see previous-1
post).
-----------------------
Anyway, for these reasons, folks who use computer models to study human
brains/consciousness will encounter some difficulty justifying, to the
basic physical sciences, claims made as to the equivalence of the model
and reality. That difficulty is fundamental and cannot be 'believed
away'. At the same time it's not a show-stopper; merely something to be
aware of as we go about our duties. This will remain an issue - the only
real, certain, known example of a general intelligence is the human. The
intelligence originates in the brain. AGI and brain science must be
literally joined at the hip or the AGI enterprise is arguably
scientifically impoverished wishful thinking. Which is pretty much what
Ben said...although as usual I have used too many damned words!
I expect we'll just have to agree to disagree... but there you have it :-)
colin hales
(1) Edelman, G. (2003). Naturalizing consciousness: A theoretical
framework. Proc Natl Acad Sci U S A, 100(9), 5520--24.
Ed Porter wrote:
Colin,
From a quick read, the gist of what your are saying seems to be that
AGI is just "engineering", i.e., the study of what man can make and
the properties thereof, whereas "science" relates to the eternal
verities of reality.
But the brain is not part of an eternal verity. It is the result of
the engineering of evolution.
At the other end of things, physicists are increasingly viewing
physical reality as a computation, and thus the science of computation
(and communication which is a part of it), such as information theory,
have begun to play an increasingly important role in the most basic of
all sciences.
And to the extent that the study of the human mind is a "science",
then the study of the types of computation that are done in the mind
is part of that science, and AGI is the study of many of the same
functions.
So your post might explain the reason for a current cultural divide,
but it does not really provide a justification for it. In addition,
if you attend events at either MIT's brain study center or its AI
center, you will find many of the people who are there are from the
other of these two centers, and that there is a considerable degree of
cross-fertilization there that I have heard people at such event
describe the benefits of.
Ed Porter
-----Original Message-----
*From:* Colin Hales [mailto:c.ha...@pgrad.unimelb.edu.au]
*Sent:* Monday, December 22, 2008 6:19 PM
*To:* agi@v2.listbox.com
*Subject:* Re: [agi] SyNAPSE might not be a joke ---- was ----
Building a machine that can learn from experience
Ben Goertzel wrote:
On Mon, Dec 22, 2008 at 11:05 AM, Ed Porter <ewpor...@msn.com
<mailto:ewpor...@msn.com>> wrote:
Ben,
Thanks for the reply.
It is a shame the brain science people aren't more interested in AGI.
It seems to me there is a lot of potential for cross-fertilization.
I don't think many of these folks have a principled or deep-seated
**aversion** to AGI work or anything like that -- it's just that
they're busy people and need to prioritize, like all working scientists
There's a more fundamental reason: Software engineering is not
'science' in the sense understood in the basic physical sciences.
Science works to acquire models of empirically provable critical
dependencies (apparent causal necessities). Software engineering never
delivers this. The result of the work, however interesting and
powerful, is a model that is, at best, merely a correlate of some
a-priori 'designed' behaviour. Testing to your own specification is a
normal behaviour in computer science. This is /not/ the testing done
in the basic physical science - they 'test' (empirically examine)
whatever is naturally there - which is, by definition, a-priori unknown.
No matter how interesting it may be, software tells us nothing about
the actual causal dependencies. The computer's physical hardware
(semiconductor charge manipulation), configured as per the software,
is the actual and ultimate causal necessitator of all the natural
behaviour of hot rocks inside your computer. Software is MANY:1
redundantly/degenerately related to the physical (natural world)
outcomes. The brilliantly useful 'hardware-independence' achieved by
software engineering and essentially analogue electrical machines
behaving 'as-if' they were digital - so powerful and elegant -
actually places the status of the software activities outside the
realm of any claims as causal.
This is the fundamental problem that the basic physical sciences have
with computer 'science'. It's not, in a formal sense a 'science'. That
doesn't mean CS is bad or irrelevant - it just means that it's value
as a revealer of the properties of the natural world must be accepted
with appropriate caution.
I've spent 10's of thousands of hours testing software that drove all
manner of physical world equipment - some of it the size of a 10
storey building. I was testing to my own/others specification.
Throughout all of it I knew I was not doing science in the sense that
scientists know it to be. The mantra is "correlation is not causation"
and it's beaten into scientist pups from an early age. Software is a
correlate only - it 'causes' nothing. In critical argument revolving
around claims in respect of software as causality - it would be
defeated in review every time. A scientist, standing there with an
algorithm/model of a natural world behaviour, knows that the model
does not cause the behaviour. However, the scientist's model
represents a route to predictive efficacy in respect of a unique
natural phenomenon. Computer software does not predict the causal
origination of the natural world behaviours driven by it. 10 compilers
could produce 10 different causalities on the same computer. 10
different computers running the same software would produce 10
different lots of causality.
That's my take on why the basic physical sciences may be
under-motivated to use AGI as a route to the outcomes demanded of
their field of interest = 'Laws/regularities of /Nature/'. It may be
that computer 'science' generally needs to train people better in
their understanding of science. As an engineer with a foot in both
camps it's not so hard for me to see this.
Randalf Beer called software "tautologous" as a law of nature... I
think it was here:
Beer, R. D. (1995). A Dynamical-Systems Perspective on Agent
Environment Interaction. Artificial Intelligence, 72(1-2), 173-215.
I have a .PDF if anyone's interested...it's 3.6MB though.
cheers
colin hales
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