natural vs. artificial – more than semantics.

Stan later replied “Nice.” and Nick “A nice perspective”.  to my reply to both their insightful comments on how vagueness in science is replaced by precise definitions, that leave out important questions from the earlier discussions.   It’s something I’ve been trying to say in a way that avoided the usual pitfalls for many years actually.

a very special new sort of ‘fuzz’ we really must reattach to our equations

Anselmo had said yesterday:

I think the dispute on “natural” vs. “artificial” is not just mere semantics, as you [Nick] appear to perceive it. Why? let me explain this with an historical example: think of physics at the time of Galieo Galilei. If you possibly have read the “dialogo sui massimi sistemi…”, you may have noticed that the word “impetus” was used in several ways, meaning velocity, force, impulse, acceleration, work, energy….

There are pages and pages in this seminal half literary, half scientific work where three disputants do not come into agreement on anything just because each one of them uses the same word meaning something different (often even switching between meanings within a same exposure or statement). Newton and Leibnitz got us out of void disputes by developing and formulating the proper mathematical frame, that made evident “impetus” was too a fuzzy concept, that needed to be split up in several well distinct, mathematically defined concepts. We all know what a revolution in physical science this kicked off.

And Stan on 6/15:

This making explicit and crisp is exactly one of the problems OUR culture has created. The world and everything in it is to some degree vague, but our technological models are all as fully explicit as possible. Fuzzy logic is just beginning to be used in computation, but I think not much in science and technology.

Note that one could argue that it is the crispness of meanings in or culture that has led us badly astray from the natural world, and is an important part of the ‘artificial’. Re the meaning of words, I have argued that the meaning of words like ‘impetus’ is in fact vague, and can be intuited from what one might call the ‘intersection’ of all the explicit definitions.

to which I replied :

I’d agree with Stan in part, that there is error in making science overly explicit. Anselmo’s example, though, is also excellent in bringing out how science prospers from finding something that can be stated clearly within a larger confusing debate. So, my compromise is that “scientists should also check the bath water for babies”.

In the discussion of “impetus” Anselmo mentions, perhaps how Newton and Leibnitz reduced it to “force” represented by equations found a very useful part, but reduced the subject too far. We did in fact end up reducing science to a concern about externally imposed force as the only possible impetus for change.

What is lost as a “driving force of change” is local systemic development, the aspect of rapid emergence of new organization, that many kinds of systems display

What is lost as a driving force of change is local systemic development and learning that many kinds of systems display. Those are what allows self-organization and self-animation.

So, I think that seems like a rather big omission, at least for the forces of change people are actually most affected by and interested in. One of the things you can say clearly about learning systems is that their learning is accumulative, and *not* ‘logical’, and so does *not* follow equations.

The equations and their narrow uses seem to keep us from recognizing rapid self-organizational processes.  It seems to identify a very special new sort of ‘fuzz’ we really must reattach to our equations to make them passably useful for navigating a complexly learning world .

a very special new sort of ‘fuzz’ we really must reattach to our equations


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