Human Devolution

[Pulse]

Hmm, blindly accepting all of science except evolution, and trying to use it to disprove evolution. Again.

Why does that particular theory always cause such a stir?

Oh that's right. It makes magical creation accounts look ridiculous. Well, they already look ridiculous.

You're clearly not here to learn anything. You're here to make yourself feel better about your beliefs by slinging shit around at anything that you think opposes your viewpoint. You're incredibly aggressive and rude, and not worth dealing with. If evolution is "wrong", I wouldn't care. Makes no difference to me. I don't have to have all the answers. I don't need to gap fill with superstitious nonsense.

Also the problem of copying and pasting long pseudo scientific answers from other people is that when people counter them, you don't have the knowledge or understanding to continue the conversation. So when I get round to answering Pulse's long copypasta about GAs he'll probably just end up repeating himself. Looking at that list of points, it's clear that the original author looked at the GAs mentioned in books written by atheist authors, and without actually understanding them, wrote down all the differences with natural evolution without care or knowledge about whether those differences were relevant or not.

I am learning fast about GAs and can see that you are incorrect to suppose they accurately reflect reality with its millions of variables. And from your mistaken notion that pesticide resistance increases information in the genome, I am not sure if you have expertise in biology itself, although I grant you are fluent in computational methods.

The appeal of GAs is that they are modeled after biological evolution. The latter is the main motivation for tolerating such an inefficient awkward process, very telling, wouldn't you think? The GA search technique begins with a large random pool of representations of “potential solutions.” Genetic algorithms are seen as a subset of evolutionary algorithms and as “evolutionary computation.” The methodology is inspired by modeling a random beginning phase space, various kinds of mutations, inheritance and selection. The experimenter chooses the fittest solutions from each generation out of the “evolving” phase space of potential solutions. The goal of the process is optimization of a certain function.

All too many evolutionary computationists fail to realize the purely formal nature of GA procedures. GAs are not dealing with physicodynamic cause-and-effect chains. First, what is being optimized is a formal representation of meaning and function. A representation of any kind cannot be reduced to inanimate physicality. Second, “potential solutions” are formal, not merely physical entities. Third, at each iteration (generation) a certain portion of the population of potential solutions is deliberately selected by the agent experimenter (artificial selection) to “breed” a new generation. The optimized solution was purposefully pursued at each iteration. The overall process was entirely goaldirected (formal). Real evolution has no goal. Fourth, a formal fitness function is used to define and measure the fittest solutions thus far to a certain formal problem. The act of defining and measuring, along with just about everything else in the GA procedure, is altogether formal, not physical.

Despite the appealing similarities of terms like “chromosomes”, GAs have no relevance whatsoever to molecular evolution or gene emergence. Inanimate nature cannot define a fitness function over measures of the quality of representations of solutions. GAs are no model at all of natural process. GAs are nothing more than multiple layers of abstract conceptual engineering. Like language, we may start with a random phase space of alphabetical symbols. But no meaning or function results without deliberate and purposeful selection of letters out of that random phase space.

No abiotic primordial physicodynamic environment could have exercised such programming prowess. Neither physics nor chemistry can dictate formal optimization, any more than physicality itself generates the formal study of physicality. Human epistemological pursuits are formal enterprises of agent minds. Natural process GAs have not been observed to exist. The GAs of living organisms are just metaphysically presupposed to have originated through natural process. We can liberally employ GAs and so-called evolutionary algorithms for all sorts of productive tasks. But GAs cannot be used to model spontaneous life origin through natural process because GAs are formal.

From my research its simply far fetched that GAs reflect reality accurately.

In addition ‘Genetic algorithms’ use completely unrealistic ‘genome’ sizes (very small), mutation rates (extremely high) and selection coefficients (very high) (  Schneider, T.D., Evolution of biological information, Nucleic Acids Research 28(14):2794–2799, 2000.) . They also do not take into account non-viability—that is, an organism would not be viable at all (and therefore evolution could not proceed!) until the system that is supposedly evolving in the computer actually worked. Real-world organisms need to be viable and maintain viability. ReMine addresses the problems of mutation rates and selection coefficients for the evolutionary story, showing that the neo-Darwinian mechanism just cannot explain the amount of information in genomes.

Again to think GAs reflect reality with its multi variable complexity is simply wrong.

See ReMine, W., The Biotic Message, Saint Paul Science, Saint Paul, Minnesota, USA, 1993.