[...]
>
>We need a different paradigm that can do justice to the complexity
>in living things. We need a paradigm which can handle information at
>more than the signalling level, and which can view the cell as an
>integrated whole.
>
>Could it be that this is what ID is able to offer?
>
I believe that if one looks at the history of science one will
find that the idea of design was abandoned not because of metaphysical
prejudices but rather because it was not found to be useful. If
the approach you are suggesting turns out to be useful, for example
it yields some advances in the knowledge and understanding of
developmental biology say, then I think many people will start
to change their minds. I would, at any rate. How do you see ID
being useful to a better understanding of complex systems?
Now, let me offer another paradigm which might overcome some
problems encountered by the reductionist approach. This paradigm
would be based on nonlinear dynamics. One reason that a reductionist
approach might fail methodologically is that it is tied to linearity
and most complex biological systems are most likely highly nonlinear.
Before I get into that, let me say that there are likely many
forms that reductionism might take. Generically, we might say that it
is the idea that things happening at one level can always be
understood in terms of principles at a lower level. One keeps
working ones way down the ladder until everything is explained,
at least in principle, upon the simplest elements. Instead of
trying to deal with this general idea let me introduce instead
what I'll call methodological reductionism which one can think of
as the actual process of trying to work down the ladder. It is
possible, after all, that the ladder is there and we just can't
find it :). Of course, if this turns out to be the case, then I
suppose that one might argue that the generic form of reductionism
is not useful.
OK, the basic approach to finding a path down the ladder
(methodological reductionism) is to take a complex system and
break it up into simpler parts. One then bangs these simpler
parts to death trying to understand everything there is to
know about how they behave. When you're all done, you put
the parts back together to try to understand the whole. But
herein lies the problem. In putting the parts back together
to describe the whole one is implicitly assuming, whether one
realizes it or not, that the system is linear. Getting the
behavior of a system as a sum of the behaviors of the
parts is a superposition process. Superposition is a property
of linear systems, it doesn't hold for nonlinear systems.
Is it possible then that a failure of methodological reductionism
reflects only the fact that complex biological systems are
highly nonlinear? How would an ID approach be better than just
trying to gain a better understanding of nonlinear dynamical
systems?
>Feedback welcome.
>
Well, you asked for it ;-). Seriously, thanks for your comments.
Brian Harper
Associate Professor
Applied Mechanics
The Ohio State University
"All kinds of private metaphysics and theology have
grown like weeds in the garden of thermodynamics"
-- E. H. Hiebert