Recent paper with an ID spin? Abel and Trevors (2005).

First a word of caution. I have a side interest in artificial intelligence (AI) and cognitive science. However, I have not spent much time studying genetic algorithms (GA). Thus you should assume that my knowledge of GA is amateurish at best. The main reason I have not spent much effort in studying GA, is that I see it as based on a misunderstanding of biological processes. My skepticism of GA might be apparent in my comments below.Abel and Trevors appear to be basing their report on what has been learned through experimentation with GA (genetic algorithms) in AI.On the use information theory, there is less there than meets the eye. The authors mention three kinds of sequence complexity, RSC, OSC and FSC. Most of their time is spent on FSC, which is the only one that they consider important. They clearly state that Shannon's measures of information content are mainly applicable to RSC and OSC, not to FSC. That greatly diminishes the relevance of information theory. They are left with making comments about information with respect to FSC, but admitting that this information is not easily quantified.Percy (Message 3) seems to think that this is an ID article. That's possible, but it is hard to be sure of the intentions of the authors. I don't see anything that attacks ToE (theory of evolution). If it is an ID article, then it is abiogenesis that is in their targets. Their section headed "Testable hypotheses about FSC" presents 4 "null hypotheses", which they presumably believe can be established by a failure to falsify them. Those null hypotheses appear to be aimed at the idea that RNA might have arisen spontaneously, and thus have started off bioligical life. However, it doesn't necessarily follow that they are proposing ID. Their intention might be to have research on abiogenesis redirected elsewhere, rather than on spontaneous creation of RNA.Speaking for myself, I think the spontaneous creation of RNA is an unlikely explanation of life on earth. Assuming life originated here (as opposed panspermia), I think it far more likely that some far simpler sort of pre-life developed first, and the use of a genetic code evolved later out of early pre-life processes.

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nwr writes:

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The main reason I have not spent much effort in studying GA, is that I see it as based on a misunderstanding of biological processes.

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GA's received a lot of discussion a couple years ago (Information and Genetics is one of the threads), and I've written a couple simple GAs. What do you think is the misunderstanding?

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Hmm. I misstated that. I should have said that the way GA is used in AI is based on a misunderstanding. The kind of problems that AI attempts to solve are very different from those solved by evolutionary processes.Thanks for that reference to Information and Genetics. I'll take a look.

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This quote from the article is pure ID:

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We can hypothesize that metabolism "just happened," independent of directions, in a prebiotic environment billions of years ago. But we can hypothesize anything. The question is whether such hypotheses are plausible. Plausibility is often eliminated when probabilities exceed the "universal probability bound".

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You have probably read more ID articles than I. Any discussion of what happened in a prebiotic world is necessarily speculative. The problem I see is that there are only hand waving assertions, and no actual attempt to calculate probabilities. There is no way of telling whether the authors were making realistic assumptions in coming to their conclusions.

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The paper is very similar to the Meyer paper that appeared in the BSOW last year both in its lack of scientific rigor and in its lack of evidence to support any of its arguments.

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I grant that it is a weak paper that provides very little support for its assertions.

That is a puzzle. My guess would be that a referee was confused by the references to information theory. I have never expected peer review to be perfect. However, I doubt that there will be a torrent of such papers, at least not in reputable journals.

I found the abstract easy enough to read. That probably is a question of background.It does assert assumptions as fact. But then, it's only an abstract. Maybe the full article provides better support. I disagree with the stated conclusions. But they might not be too far from current thinking in some parts of the AI community.

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