Models vs. Reality
What's it all about, Charley? ...
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We can't read the world without presuming a model of some kind.. The reason is that we must have criteria for creating patterns and making distinctions among them. We need sensors to make contact, but we also need to direct our observation and pattern the information. Without a model there could be no information -- as there could be no tennis without a tennis court. Modeling creates the space. Whether dealing with objects of ordinary experience or "objects" of the underworld, a model generates a repository of information.
Example: A Newtonian model of motion says "force equals mass times acceleration," a law not expressible in Aristotle's theory of motion. Similarly, the language of quantum mechanics is foreign to Newtonian physics.
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Does it make sense to ask what the world is really like, independent of our observing? It seems okay to ask, but is there an answer?
If there is, doesn't it have to provide Information about that world? And doesn't that presume a mechanism of derivation? Doesn't this also presume a perceiving agent, the model being a human construction? How can information be of the real world, for doesn't the real have to be independent of what we observe, considering that observation delimits what is? And doesn't it have to take our observation into account? Don't we have to know how observation affects the world we observe?
Alternatively, if there is no answer, what good is the question? Can we argue that, somehow, we can get closer and closer to what really is, but that, nevertheless, the real remains "beyond" our points of view? Is it meaningful to say there is something we can "approximate" but never know exactly, or entirely, something that gives rise to virtual realities? Is it like getting to know relatives, friends, and neighbors -- the people that make up our many arenas?
Our attitudes and opinions about them usually change over months and years, and at times we even feel we're getting closer to understanding what really makes them tick. The same thing applies to understanding house plumbing and wiring, or the stock market. Or figuring out how to swing a golf club, or use a pool cue or tennis racket. Even understanding the theory of relativity. Or what the universe of stars is like. What atoms and such are like. Or beginning to see how the brain works, or networks. These and many other examples could well lead us to believe in a real world that's more and more nearly knowable but perhaps never entirely within our grasp. Couldn't they?
Whatever in the world is real, must it not include the fact -- or presumption -- that we observe it? Inasmuch as we must adopt a vantage point to make our observations, can we even know ourselves as the experiencing agent? What then can a "real world" be, other than an element of a model?
Also, doesn't our experience -- whatever its nature, colored or not, bound or not -- have to be included among the things that are real? If we imagine something to be real, isn't the imagining itself real? Otherwise, what are we talking about? Is the object of our inquiry always "once removed" from direct experience by the fact that we must use models to experience? Aren't we then caught in an infinite regress?
Or does the "experience" lie directly on the surface, so to speak, as a raw, naive, unexplained consciousness -- the stream of colors and sounds of the world? My everyday experience?
If so, it is something "we" can't "know," because knowing requires modeling; so discrimination is necessary. Nor is it really a "something," because "things" mean boundaries. A thing can be distinguished only if it's distinguishable from something else. "It" can't be "experienced," either, then, because it would have to be "somebody's experience."
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Does the use of models create a dilemma for us? In other words, is modeling inherently catch-22? If we have no alternative but to use models to find out about the world but models never tell us "the truth, the whole truth, and nothing but the truth," aren't we just spinning our wheels trying to learn anything?
That's the way I feel most of the time about the stock market. But I believe the mood speaks to our vast ignorance of ourselves, our organizations, and our environments. There's so much to know and we know so little! Our skills aren't up to the digging required for anything but the most shallow and elementary knowledge -- putting aside some remarkable theories. Compared to that ignorance, the contradictory nature of models seems almost trivial.
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Contradictions are anathema to logicians and mathematicians. That's been my attitude, too. With Spencer Brown, though, this disposition toward the contrary has softened a bit.
In logic and math circles, the notion of contradiction has a long history. It is acknowledged in the principle of non-contradiction, which has been the underlying tenet of logic and math systems, meaning that statements that contradict each other can't be seen together! You can't have the statements A and not-A in the same system and expect to have a good system. The argument has been that from contradictory premises you can prove anything, and that's not acceptable. Contradiction isn't allowed in the club. That is, it wasn't allowed -- until multi-valued logic and Fuzzy theory came along and changed the picture. At a minimum, the definition had to be modified, but Fuzzy Logic rejects the principle of non-contradiction.
In fact, G. Spencer Brown thinks we're missing a good bet by failing to use contradiction in our proofs! The Brown brothers even used the principle to design and build working circuits. Their hope is to be able to apply the notion in formal systems to prove things we can't otherwise seem to prove.
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Modeling involves making distinctions among elements and environments -- without distinctions there is naught but void. Modeling is patterning -- distinguishing something as a unity apart from what it's not. You model by specifying elements in specific environments, assigning properties to the elements, and defining and formulating the dynamics of the environment. Making distinctions is what Laws of Form is all about. It aims to incorporate in the math of logic the counterpart of the imaginary number of algebra to enhance logic.
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