Ben,
I am
coming to understand that it is not a small matter of little importance, this
notion that a computer program can achieve anything that should properly be
called "intelligence". There is more than a philosophical difference here,
between you and I.
It is
a question also of what one attempts to do and what one does not spend (other
people's) energy on.
You
see, for me complexity is defined in a way that must produce a halting condition
for a computer program, simply because complexity (defined by Kugler from his
study of Rosen) is exactly when "a = a" can not be
determined.
By
definition the computer program can not see and can not compute anything that
has any degree of complexity to it - despite what the academic computer
science professors say. Computer science has no grounding in
observational science, except in the limited sence of never looking at the
natural world (at all - ever).
It is
turtles all the way down. Period. And there is only so many of these
turtles before one get to the final abstraction of being "on" or "off".
Stratified complexity will make this clear - and finding and holding to this
clarity is what the Manhattan Project must be about. This is not a small
matter. It is a matter of putting computer science in it place after
several decades of complete domination over all of things.
When
one looks closely one sees that the issue is not computer science but
"abstraction". Computer science works because abstractions produce the
programming languages and the hard reification of electromagnetic waves into on
and off states. This is engineering to produce an engineering
tool. Each "on" is "exactly" the same as any other "on".
But in
natural reality we have something called similarity - but we do not have
"exactness" ever. No two "things" are ever exactly the same. Rosen
did not state it this way exactly, at least I have not found a way to quote him;
but Peter Kugler's work on Rosen's literature lead me to see that the category
error (mistaking a formal system for a natural system) was the CAUSE of the
confusion around AI. I then traced this cause further into what I have
come to call the religion of scientific reductionism, and to a IT industry whose
production of snake oil is only rivaled by the "medicine men" who traveled from
town to town in the early west selling tonics.
The
very Nation is in some trouble over the failure of IT to produce any sort of
real "information exchanges" . Some of this failure is due to the wrong
mindedness of the AI camp and of the reductionist at NSF, NIST and DARPA that
are focused on professional careers and not on the development of true
science.
I do
agree with you about so many things, and it is a shear joy to know
you.
When
you say:
"
I see the Manhattan Project for KM has
having five main
aspects:
1* Actually building a huge integrative database out of
existing structured databases
2* Creating tools for creating structured data out of
unstructured data (e.g. text)
3* Creating tools for browsing the integrative
database
4* Creating tools to encourage humans to
collaboratively and individually insert new knowledge into the
database
5* Creating computational tools to create new data out
of old, and put it in the database
AI plays a role in 3 and 5.
But for starters, it may be that 1, 3 and 4 are our
greatest concerns. They're "easy" technically yet difficult to execute
politically & socially...
In this picture, Paul's and my disagreement on the
relation of intelligence & computation is really a small
matter. It has to do with the amount of power that can be achieved in
5, via computational intelligence alone without significant human
participation.
"
I
would argue that the most important aspect is the design of cognitive
neuroscience grounded science of Human Information Interaction (or as it is
being called, HII). It is clear that the man/machine interface has much to
gain by the improvement of data aggregation and convolution processes, (such as
those by Novamente, CCM/LSI, and Primentia and other new methods) as well
as by the improvement of the cognitive skill that humans might develop based on
what the computer programs can actually do.
So I
recognize that there is a great need for the Novamente engine and for work like
the work I am doing on Latent Semantic Indexing and generalized LSI. But I
would change each of the five aspects to read:
1* Actually building a huge integrative database out of
existing structured databases
--> Develop
schema-independent means for communicating and storing both semi-structured and
structured data.
2* Creating tools for creating structured data out of
unstructured data (e.g. text)
--> This is the
Implicit to Explicit Ontology conversion process that I have recently called
"Differential Ontology", but this process must have human decisions within EACH
phase of a loop Implicit - Explicit ----> Explicit to Implicit..
The reasons are many, but avoiding false sense making is the more
important. Computer programs to not exist, in the world, and can not
achieve a pragmatic axis...and thus the machine ontology can be come anything
including something that has no relationship to any part of the natural
world. Without a topic map type reification process (that must involve
humans) then the ontology has no way of making the fine adjustments that are so
clear to a natural intelligence.
3* Creating tools for browsing the integrative
database
--> I would say that
this issue goes away if other issues are addressed proper. Thee is a
"by-pass' that makes the notion of "integrative database" collapse to just
"database".
4* Creating tools to encourage humans to
collaboratively and individually insert new knowledge into the
database
--> People already
collaborate in many different ways, it is not the computer that is needed to
enhance this natural activity but rather it is the computer, under the current
use patterns, that inhibits this
collaboration.
5* Creating computational tools to create new data out
of old, and put it in the database
--> Why store useless
things. One needs to create educational processes that provides humans the
ability to understand better and deeper the nature of
life....
The bottom line is that
the planet has billions of individual human minds and each of these has far
greater capacity to renew information in creative ways, than does the Internet
(as something divorced from people.) One can act as if this is not so, but
that acting does not change the reality a single bit. (no pun
intended...smile)
-----Original Message-----
From: Ben Goertzel [mailto:[EMAIL PROTECTED]]
Sent: Wednesday, November 06, 2002 6:13 PM
To: beadmaster
Cc: NaturesPattern
Subject: RE: localized and global ontologiesHi all,paul wrote:***Dr. Ben Goertzel's deep work on implicit ontology is important not in the development of something that can not be (by nature) but in the development of something unexpected and new and thus in great need for definition. But let us not call this "intelligence" as the work already has a meaning that is violated by this notion of a computer intelligence. Let us work on our language so that there is no unnecessary confusion. (I say to my friend, Ben.) I think that Don is leading the way here***My friend Shane Legg has coined the word "cybernance" to mean "the ability to achieve complex goals in complex environments." This is basically what I mean by "general intelligence" ...I do not agree that the word "intelligence" is violated by the notion of a computer intelligence.I think that "intelligence" is a *behavioral* quantity, which may be realized by systems built of organic molecules, by digital computers, and probably by many other types of media that we 21'st century humans haven't yet conceived....I see the Manhattan Project for KM has having four main aspects:1* Actually building a huge integrative database out of existing structured databases2* Creating tools for creating structured data out of unstructured data (e.g. text)3* Creating tools for browsing the integrative database4* Creating tools to encourage humans to collaboratively and individually insert new knowledge into the database5* Creating computational tools to create new data out of old, and put it in the databaseAI plays a role in 3 and 5.But for starters, it may be that 1, 3 and 4 are our greatest concerns. They're "easy" technically yet difficult to execute politically & socially...In this picture, Paul's and my disagreement on the relation of intelligence & computation is really a small matter. It has to do with the amount of power that can be achieved in 5, via computational intelligence alone without significant human participation.-- Ben G
