|
Hi Howard,
An interesting post. I have some comments and a few questions and
corrections, as well...
I must emphasize that any critical comments are only my academic
opinion and do not in any way detract from my close personal friendship and high
regard for them both.
Thanks for that-- it does make a difference.
Rosen began studying wet biology in high school,
What is "wet biology"?
He had been doing experimental biology for almost a decade by the
time he was in high school! It was really that he realized he would never get
the answers to his questions about life that made him begin to look more at
theoretical science. Math was a tool he thought might be very useful, so he
pursued it almost exclusively right until he got to Chicago. He hadn't expected
to find a venue for doing the kind of biology he intended to do until he got out
of school. So Rashevsky's fairly recent epiphany, just before my father got
there, was providential.
but his instincts and abilities were for mathematics rather than
experimental biology. After studying math and physics, it was largely because of
the influence of Rashevsky's relational models that he finally found that his
deepest interest was in how our epistemology and our assumptions about
scientific models influence our concept of life. As members of this list know,
his basic conclusion, developed as an analogy with the creative open-ended
"corpus of mathematics," was that (as in mathematics) formal (computable,
purely syntactic) models are too "impoverished" to capture the creative
open-ended novelties of life.
Rashevsky had only begun to feel his way towards a new way to do
biology when my father met him. He was on the right track, though and he offered
my father the freedom to do things his own way. Which of them influenced
the other more, is a matter of debate. I tend to think that this brilliant kid
with a brainful of new ideas was exactly what Rashevsky needed to help him
crystallize his own sense that reductionism was missing something essential. My
mother tells a story of the night before Dad's defense of thesis, when Rashevsky
called up in a panic and Dad had to spend a couple hours "talking him down"...
When he got off the phone, he turned to her and said, "I can't believe it! He
still doesn't get it, even after all this time!" In Robert Rosen's published
work, however, Rashevsky always was treated with extreme deference because he
was, in essence, the only father figure my father really had. He was protective
of Rashevsky and respected Rashevsky's intelligence, courage, and stubbornness.
I think Dad genuinely loved Rashevsky, the way a son loves a father. That comes
through in everything he wrote about Rashevsky's character and
career.
Kauffman criticizes Rosen (as have I and others) for his imposing claims
written in a language that few biologists understand, and that have as yet
suggested no biological observables that could allow a verifiable model.
This is a legitimate criticism, at least about the language part.
He said he wrote as if he were speaking to himself. I've said before that I
don't think that's entirely true; it's more accurate to say that he was speaking
at a level that he was comfortable with but he knew full well that the vast
majority of the rest of humanity would not be able to "keep up". I tend to think
it was his form of "code" such that, in order for any readers to use the
knowledge he had accumulated over a lifetime, they had to do some work, too. But
as I've mentioned, a significant part of "cracking the code" is simply to
realize that all of the mathematics are there in the form of
illustrations of the main ideas. Proofs. You can read only the prose and still
get the full concepts. He was the first to say that mathematics is not
everything and where biology is concerned, it's a useful tool-- as long
as we don't forget it's a tool.
Regarding the second part of that... how do you conclude that he
suggested no biological observables that could allow a verifiable model? In my
experience, his books are peppered with examples-- all of which are verifiable.
A great many are self-evident, it seems to me.
Kauffman, on the other hand, has a simple computer simulation that behaves
by various interpretations like developing organisms and like an evolving
population. If I had to say it in < 20 words, Kauffman has empirical models
without a specific epistemology; Rosen has an epistemology without (as yet)
specific empirical models.
How would Stephen Wolfram's computer simulations compare with
Kauffman's?
Judith
----- Original Message -----
Sent: Tuesday, January 25, 2005 1:23
AM
Subject: [ROSEN] Rosen cf. Kauffman
At 11:23 AM 1/24/05 +0200, Ayten wrote:
[snip]
>After
having written these passages, I asked myself the question of how
>close
Kauffmann and Rosen in their views on this question of What is Life?
I
>also further asked myself if the main actors of this list as Tim,
John K,
>and Judith consider making a comparison of these two minds and
show for us
>similarities and dissimilarities . .
.
HP: Here are some of my own comparisons between the minds of Rosen
and
Stuart Kauffman. I have known them both personally and professionally
for
many years. But first, since in the past Tim and Judith have
misinterpreted
some of my critical opinions as a personal attack, I must
emphasize that
any critical comments are only my academic opinion and do
not in any way
detract from my close personal friendship and high regard
for them both.
John M's intuition is correct. Here are two different
types of scientific
minds that start from different backgrounds and work
from divergent points
of view, ending up with completely different types
of models. Kauffman
began as an MD but was attracted to experimental
developmental biology.
Then, largely because of a single computer program,
and with no significant
mathematical background, he morphed into a
theoretical biologist focusing
on self-organization, origin of life,
non-Darwinian evolution, and
development.
Rosen began studying wet
biology in high school, but his instincts and
abilities were for
mathematics rather than experimental biology. After
studying math and
physics, it was largely because of the influence of
Rashevsky's relational
models that he finally found that his deepest
interest was in how our
epistemology and our assumptions about scientific
models influence our
concept of life. As members of this list know, his
basic conclusion,
developed as an analogy with the creative open-ended
"corpus of
mathematics," was that (as in mathematics) formal (computable,
purely
syntactic) models are too "impoverished" to capture the creative
open-ended novelties of life.
Kauffman's basic computer program (an
elaboration of previous work by Ashby
and Walker in England) is remarkable
for three things, its simplicity, its
initial randomness, and the richness
of the interpretations he gives its
results. Kauffman originally
discovered these computed results entirely
empirically and largely
unexpectedly. The basic model is a randomly
connected network of random
(boolean function) nodes started with random
initial conditions -- i.e.,
maximum disorder. The discrete states of the
network are just the current
values of the nodes, and the next state is
completely deterministic
(unless externally mutated). The well-known (and
now mathematically
understood) result for low connectivity is that the
paths in the
exponentially enormous state-space follow transient paths
collapsing into
relatively few, short, stable limit cycles. Higher
connectivities lead to
a finite analog of chaotic dynamics.
This behavior with various
elaborations has been interpreted by Kauffman in
many ways: 1) as
self-organization from complete disorder, 2) as a first
step in the origin
of life, 3) as epigenetic canalization in development,
4) as the
self-organizing structures on which Darwinian natural selection
can
operate, but cannot override, and 5) by allowing variation in
connectivities and by coupling nets, a model of meta-evolution where
natural selection (coevolution) chooses the "edge of chaos" as the most
adaptive condition.
It is fair to say that Rosen and Kauffman never
formed more than a civil
relationship that is usual at professional
meetings. Kauffman has much more
personal ambition than did Rosen and
achieved a notoriety that in my
opinion (and Rosen's and many others) is
not justified by hard evidence
supporting his imposing claims for his
models. Rosen saw the behavior of
random nets as an obvious example of the
generic behavior of discrete
dynamical systems. He saw Kauffman's many
interpretations as simply
illustrating that the same formalism can be
encoded any way you like.
On the other hand, Kauffman has suggested
biological observables that would
allow empirical tests of his models. His
books include biological evidence,
and are written with conventional
language that biologists understand well
enough to critically discuss.
Kauffman criticizes Rosen (as have I and
others) for his imposing claims
written in a language that few biologists
understand, and that have as yet
suggested no biological observables that
could allow a verifiable
model.
I don't think any of these criticisms, while probably true, are
scientifically relevant. My current view is that Rosen and Kauffman are
thinking on different levels. Rosen's thinking is primarily on an
epistemic
model. One might call it a general principle that any biological
model must
satisfy to answer a "Why?" type of question. After all, the
modeling
relation itself is a model. It is based on the Hertz condition
that is not
itself empirically verified except that a model must satisfy
it to give us
the answers we want. An analogy is the symmetry
principles of physical
models. These principles are not empirically
testable. They are epistemic
conditions we discover we must place on
empirical models to give us the
types of explanation or answer to the
questions we ask.
Kauffman, on the other hand, has a simple computer
simulation that behaves
by various interpretations like developing
organisms and like an evolving
population. If I had to say it in < 20
words, Kauffman has empirical models
without a specific epistemology;
Rosen has an epistemology without (as yet)
specific empirical
models.
Howard
|