Hm. I can't shake the feeling you're relying on some ambiguity in "meaningful distinction". If you admit distinctions in things like domain knowledge, correctness, verified code, tolerances, sensitivities, etc., then why not admit there are meaningful distinctions in _types_ of computation?
Sure, it all may boil down to distinctions of degree rather than kind. But (going back to definiteness) any 2 points in a continuum are still distinct points, even if they are arbitrarily close. And discretization of continuous data has proven a valuable technique. So, we're not going to stop doing it. Hence, we'll end up with at least 2 types of computation, anyway, the one called "living systems" versus the purely mechanical ... even if, in full reduction, they are fundamentally the same kind. So, we may as well allow the distinction now and see where it takes us. On 07/06/2016 06:30 PM, Marcus Daniels wrote: > I don't buy there is a meaningful distinction -- I mean one that should be > preserved -- between those who do analysis and those who do calculations. > (There's history and prejudice about this of course.) There's just > differences in domain knowledge, and a formalism gap where misunderstandings > occur. Ideally there would be automated proofs (and context) all the way > down. If a code can be shown to be correct and as intended, and tolerances > of the machine are known as are numerical sensitivities in the algorithms, > then there is no reason to trust analytical results more or less than > calculations. The latter just takes longer. As for neural correlates of > consciousness, same thing: If it turns out there are neat, modular ways to > model cognitive function, great, but decoupling different kinds of evidence > into stove-piped areas of expertise is just throwing away information. -- ☢ glen ============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
