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
-------------------------------------------
agi
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