jamzen@world.std.com wrote:
(stuff deleted)
>Yes. I believe that the shift of perspective afforded to us by the new
>understanding of chaos and nonlinear systems is more encompassing than
>either quantum theory or relativity. The present revolution dwarfs
>anything since Newton.
>And frankly I'm welcoming it. There were a lot of things I never liked
>about "science", back when "science" meant "finding Newton-type laws for
>whatever you happen to be looking at" and "Newton-type laws" meant "slap
>numbers on everything and then find at least a couple of plausible
>closed-form algebraic expressions with time as an independent variable
>that look like they might have some predictive power". Newton did that
>for the planets, and from then until now everybody's been trying to do
>that for economics and sociology and psychology and biology and a lot of
>other *logy's. And then the "philosophers of science" get PhD's for
>wondering about the reversibility of time! The closed solution is the
>real conceptual villain in here, and it's the closed solution -- the
>analytical algebraic expression -- that is the _FIRST_ casualty of
>nonlinear systems study. Chaotic systems _DON'T_ have closed-form
>solutions with time as an independent variable; LaPlace goes down with a
>stake in his heart.
>And the glorious paradox in all of this is that it's accomplished without
>giving up ordinary causality. Even chaotic systems don't have "free
>choice"; each momentary state is continously connected to the one before
>and the one after. (For centuries after Newton, it was commonly argued
>that unpredictability was inconsistent with causality. Tee-hee.)
(more stuff deleted)
in response to John Conover discussing Rudy Rucker's book:
(stuff deleted)
> (which is a very good book, BTW,) and presents some very formidable
> arguments in support of your premiss. Such systems that exhibit this
> phenomena are usually called fractal or non-linear dynamic systems. It
> does indeed appear that social institutions are such a system. As an
(ditto)
IMHO, chaos/fractal/nonlinear dynamics are *not* the real revolution.
They are only qualitative changes in an unstated theory that the world can
be accurately described in formal/mathematical terms of any level of
complexity. For example, the heart of chaos theory is the "discovery"
that even simple systems (let alone complex ones) can be extremely
sensitive to initial conditions. Left unstated is the assumption that the
even chaotic systems can be described in formal/ logical/mathematical
terms. Chaos only says that our job of prediction is only much (near
impossibly) harder. This assumption is fine for mathematicians (as long
as they don't actually claim the math applies to a real system) and
computer scientists (whose "ground truth" is the logical computation going
on inside their box). But to say that chaos/fractals/etc. are the key to
understanding the dynamics of *real*, particularly, "living" systems such
as organizations and other social systems is to continue the long
tradition of assuming that such systems follow the same system of logic
that mathematics addresses. On other words, I think the
chaos/fractal/etc. *revolutionaries* are confusing difficulty in
predicatablity with *inherent unpredictability*. Living systems such as
people and their social systems are inherently unpredicatable because the
*create* things in the real physical world. Any formal description of a
physical system can only describe the "important" aspects of reality *that
have already been discovered*, which are very small compared to all the
possible descriptions of that same reality. But living systems are able
to use the implications of *physical*, not just logical, features and
relationships to produce inherently unpredictable (via any formal means)
future realities. It is the impications of this absolute unpredictability
and role of creativity in science that will be the *real* revolution.
George Kampis, in his book "Self-modifying Systems in Biology and
Cognitive Science" (Pergammon 1991), presents this argument in
excruciating detail. It has been some years since I have read it, but I
seem to remember an example of physical implication that goes like this:
If someone were to ask the information capacity of a particular
computer tape, they might look at its length, its magnetic properties, the
bit per inch capability based on these magnetic properties, and any other
number of "formal" properties thought to have anything to do with its
information capacity. Such analysis would allow me to "predict" its
capacity *in the frame of the formal system I have chosen to represent
it*.
Now lets say this tape is lying around the computer room, not being
used. I might agree with my fellow programmers that if I tie a knot in
the end of the tape when I leave the room, it means I intend to return and
not to shut down the system. I am now conveying information with the tape
that was not predicted in my formal analysis because my formal
representation (based on already discovered ways of using the tape for
carrying information) did not account for all possible physical
implications, in this case, the fact that this particular tape is flexible
enough to tie into knots. This inability to predict is a different *kind*
of unpredictability than the sensitivity of initial conditions (or brute
complexity of a formal system) addressed by chaos/fractals/non-linearity.
The "-ologies" that jamzen@world.std.com referred to (e.g., sociology,
psychology, biology) will undergo the *real* revolution when the own up to
the inherent limitations of formalization *of any kind* (including these
"new sciences of complexity"), the loss of predictability, and ultimately
(especially so for organizations and management) the loss of the ability
to *control* based on this predictability when dealing with people and
living things.
Fred Reed
freed@cc.atinc.com