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> Simple answer to complex problems, outside science and engineering, are almost always wrong. True, but it seems that the universe is simple at its foundation
by sometime 8y ago
> Simple answer to complex problems, outside science and engineering, are almost always wrong.
True, but it seems that the universe is simple at its foundation and complex in some of the things that emerge from it.
The standard model fits on a sheet of paper and it commonly makes predictions that are accurate to the ~20th decimal place. Neural networks can be expressed in fraction of that complexity and evolution is even simpler. Computations that emerge from these things are often complex beyond our comprehension, and hence it is a good heuristic to distrust simple explanations in the sciences about emergent phenomena such as psychology, sociology, economy and biology.
- chobeat 8y agoYes but consciousness is not in any way a foundation of the universe. It's a foundation of our own experience, but if you take a mechanicistic, reductionist approach, consciousness is pretty high in the ranking of things. I'm not saying its explanation must be necessarily complex, but so far the simple explanations didn't work. > Neural networks can be expressed in fraction of that complexity That's not an explanation. That's a rule to construct them. Same for evolution: one thing is to define a basic rule that underlies a phenomena, another thing is to explain why we like peanut butter and jelly using evolutionary psychology. The basic rule doesn't capture much. And sometimes, maybe, there's not even a basic rule to begin with, because we conflate a lot of stuff in concepts that have no root or relationships in the physical world.
- sometime 8y ago> Yes but consciousness is not in any way a foundation of the universe. The universe is fractally structured regarding simplicity: It is simple at its foundation upon which we find layers of evidently chaotic processes (e.g. brownian motion, thermodynamics, fluid dynamics), which in turn converge to metastable rule sets that are seemingly simple again (e.g. evolution, neural networks). Unpredictable fluctuation from the chaotic layers below are either exploited as a computational mechanism (e.g. for probabilistic modeling or adaptations of unpredictability in behavior) or averaged out by regulation (homeostasis), so simple rules remain plausible despite the underlying chaos. Those simple rule sets in turn produce complex processes (e.g. psychology, science), which in turn produce simple processes (e.g. game theory, economics). Of course the higher up in this hierarchy, the more unstable rule sets become, e.g. most economic theories make poor predictions, but evolution is an extremely reliable theory.