[Avery Andrews 950807]
A sequence of thoughts on evolution, reorganization, and Ed Ford's
stuff.
Suppose we start with replicators. It seems a reasonable guess that
all replicators require rather specific (local, micro-) environmental
conditions in order to replicate: no replicator will work equally
well on top of a rock in Datj Va;;eu and at the bottom of an oceanic
trench. So replicators that can maintain local conditions suitable for
their replication will have an edge over those that can't, or are less
good at it. This, we assume, means the replicators will tend to develop
control systems.
Sidebar: the perceptual variables and corresponding CEV's controlled by
the replicators are not necessarily the same as the Ecological Variables
on which replication actually depends. A wasp might need a nest that
will remain in a fixed position (so it can fly back to it after flying
away to get building materials, food supplies for the eggs/larvae,
etc.). The wasp can't *control* the position of the nest because (a)
it has to go other places (b) isn't strong enough to hold it in place
against wind, etc. But what the wasp can do is control for a perception
to the effect that the nest is attached to such-and-such-a-kind-of-surface
in such-and-such-a-way. Then, thanks to the principles studied in materials
science, the theory of adhesion, etc., the nest will indeed tend to stay
put. End Sidebar.
Genetic Evolution (Darwinian selection in populations of replicators) is
a very powerful method for developing effective control systems (that
(a) manage to control their perceptual variables, and (b) thereby stabilize
the environmental variables favorable for replication), basically
because large numbers of variants can be tried out simultaneously, and only a
fraction need to survive.
One of the strategies that GE comes up with is `societies' of control
systems (in one organism, or across organisms) that can tune and
adapt their structure, e.g. learn. (Even bees can learn to recognize
new shapes, I'm told). But learning/reorganization, at least within
single organisms, is a much more problematic affair then Genetic
Evolution: the organism can only try a few possibilities, one after
the other, must survive all the experiments, and find an adequate
solution in a timely manner. So what you'd expect to find is not
some general, nonspecific reorganizing capacity, analogous to random
mutation, crossing-over, etc. om GE, but a variety of special-purpose
mechanisms, optimized to work well under specific conditions (the native
environment of the organism). (This is Chomsky's basic point about
learning.)
So what Ed Ford's recent postings suggest to me is that the human
learning/reorganizing system is not very well adapted to finding good
solutions in the rather beaurocratized environment created by modern
societies. A signficant fraction of kids seem to fail to find any
viable solution to the environment found in schools (and, having mucked
up there, get tossed into environments for which they are even less
well endowed to find a solution). What the program does is subtly
change the environment so that their intrinsic reference levels (such as
to be with their friends) tend to lead them towards good solutions
rather than bad ones, and perhaps the emphasis on thinking and planning
helps them to succeed in developing these capacities in certain
directions which are not perhaps required in the native human environment
(obviously, humans living the original lifestyle had to think and plan,
or we wouldn't be able too, but they might have utilized this capacity
in different ways than those that are advantageous in modern societies;
therefore we are not well-adapted to find good ways to think about
how we actually live).
And, evidently, even the teachers and administrators, who have found somewhat
viable solutions to their environment, seem not to have found optimal
ones! One more thing I gotta find out more about! b.t.w., prioritized
reference levels sound exactly like constraint ranking in Optimality
Theory, an emerging (perhaps explosively developing would be more
accurate) approach to linguistic theory.
Avery.Andrews@anu.edu.au