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Even if math and
logic were fundamentally without fuzziness, their applicability to the rest of the world is inherently fuzzy. Their invention has inescapable, inevitable repercussions which have ethical consequences - so yeah, those need to be considered by someone. But I wouldn't even be that generous. The amount of inherently human decisions that go into the design, representation, learning, educating, and yes - categorization of math is far from a perfect un-fuzzy logical utopia. We inherently add our own human ideals of what we consider a beautiful (elegant, easily understandable) formula/proof/concept/whatever, and every time we do we affect the perception of subsequent discoveries. Any computer scientist who has developed a sufficiently complex system knows that it is is impossible to make something "purely rational" without making arbitrary categorizations, which another programmer might do completely differently to produce a similar result with far-reaching effects down the line. Likewise, Math as we know it is taught the way it is because of the specific way it formed historically and the way it's best understood by its human students. The fuzziness runs deep. Maybe you want to escape to fundamental concepts with rigorous self-consistent definitions only, with no applicability to the real world. Just cold hard formulas - the "real math". 1+1=2. Well then I hate to break it to you, but unless you have mathematical definitions of elegance and complexity to replace the human ones, you have no choice but to treat every tautology the same. Even selecting which proofs and axioms we care about is inherently human. So 1=1 and 46332688=3+211+7774+... Oh, and forget base 10... Or for that matter, why we even choose to define particular operators... Or explaining the proofs of any of this in english without some self-bootstrapping rigorous definition of the proof language... My point is just that to completely remove the human fuzziness you have to cut out a LOT. You have to sacrifice understandability, brevity, and conceptual usefulness, amongst many others. And even if you could make a perfect self-bootstrapping logic box (something famously proven to be impossible by Godel Esher Bach - no system can perfectly define itself, it can only be defined by its parent) then there's still the problem that whatever the discoveries of your self-contained system are, they'll still have an impact on the rest of the world - which we then judge the effects of through Ethics. Sorry, but truly escaping the fuzzy swamp of human culture is pretty damn tough. Maybe it can be done, but I doubt it. All language is fuzzy, all understanding is fuzzy, representation is fuzzy, the choice to define one thing and not another is fuzzy, Mathematics and Computer Science as educational subjects are very fuzzy still (even as much as they believe they aren't). Fuzziness is the baseline, and the study of that fuzziness is Philosophy. Maybe there exists some pure kernel that is strictly without human fuzziness, but that remains to be seen, and even if it was - it would be very different from the subjects of Math and Computer Science as we understand them today. |
First off categorization and naming is a human endeavor. The logic that lies underneath is solid and independent of the nomenclature or any formal rigor needed to define the names. We understand math through using words and naming as tools, but the words themselves do not define the underlying structure itself which is as far as we know: Not Fuzzy.
Second our choice of what axioms and theorems to study don't make anything fuzzy. We are simply choosing a subset out of a set of all possible choices in which the subset remains not fuzzy. OUr arbitrary choices are human, but the logic within the framework of our choices still apply.
Godel Escher Bach is just a book. The incompleteness theorem you are seeking comes from Godel. Not only can a system not define itself, it cannot be fully provable and internally consistent at the same time. This does have a lot of interesting things to say about logic BUT it does not make mathematics or logic fuzzy and opinionated.
Fuzziness is not baseline. The baseline is unknown, but what we do know has been consistently observed to be not fuzzy.
Let's be clear, by fuzzy we mean things like ethics and religion. Things that are based on opinion and exclusive to the human experience. None of this type of fuzziness applies to science or math or computer science.