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Archive for October 30th, 2008

This post is my interpretation.  Other thinkers, philosophers and researchers have other (more technical) approaches regarding this subject.

Statement: There are no models that completely explain the “how or why” sufficiently complex phenomenon.

Clarifications:

Explain – Accurately represents the causes, context, behavior and consequences of a phenomenon and presents such representation in a usable form (we can apply this knowledge outside of just explaining)

Completely – 100% (or very nearly 100%) represent all cases of the phenomenon.  In particular, there are no “exceptions” nor is there simply a “rule of thumb.”

“How and Why” –  The actual behavior, make up, and structure of the phenomenon.

In other words:

All our scientific efforts produce models, not explanations.  Models help us improve our methods and provide insight into phenomenon, but they are not the “thing” and they do not explain the “thing”.  Our explanations based on models and/or the incomplete information they are always based on (computational irreducibility, uncertainty) are forever not complete and always capable of revision (inaccurate).

Math is the ultimate model language.  It is a way to describe relationships when you strip away the gnarly details of the real world.  It sometimes has beautiful results but never produces an explanation of the real world.

Computer science is inbetween the real world and math.  A great way to simulate things and build new computational models, but because it’s not made of the stuff we’re often simulate it can’t possibly be completely accurate.

Biology and other specialized disciplines tend to rely more observations than abstract models.  The result is a nearly infinite record of exception cases making conceptual models that span multiple phenomenon very difficult (well, that’s because you mostly can’t do it.)

Though I’m giving a very truncated account of everything hopefully the point is clear.  Explanations are always our judgment, our subjective synthesis of the inaccurate data we have.  This does not imply we don’t know anything.  Nor does it imply we don’t have explanations.  For simple, or relatively simple, phenomenon we have accurate explanations and good working knowledge.

Specifically, as related to this blog, economics, behaviorism, and social models are all useful models.  None of the “laws” presented in these disciplines are fullproof.  Rational Choice theory, supply and demand, matching laws….  these are good tools, but not full explanations of the how and way of behavior, media and social activity.

Proof: Is left as an exercise to the reader.

Proof Part Duex:  This is an intractable problem.  There’s no way to formally prove these statements.  They are hunches.  I do believe the proof is somehow along these lines: to determine if an explanation is complete and accurate I’d have to be able to reduce a phenomenon down somehow, which is impossible for sufficiently complex phenomenon. (think along the lines of the halting problem.  i can’t determine if a program is going to halt any more quickly than running the program and seeing if it halts….)

For a more formal treatment of scientific explanation head here.

There are many more resources and I’ll post them as I surface them.

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