I guess any article in the bunch that you think is significant you can copy it over here for the archive.
Scientific American's "15 Answers to Creationist Nonsense" is just such an example of "avoiding the truth." Right from the start, a number of those questions reveal that this is what is going on:Huh? Harun Yahya (thought to be a pseudonym for a slew of different authors) has never seen an FR crevo thread."Evolution is only a theory. It is not a fact or a scientific law."
"Evolution is unscientific, because it is not testable or falsifiable. It makes claims about events that were not observed and can never be re-created."
"If humans descended from monkeys, why are there still monkeys?"
None of the above are objections expressed by critics of the theory of evolution.
I can tell. I've really been sleepy lately.
Although when I was in college, I had a professor who wasn't impressed with the speed limit for light. In both optics and QM we had to deal with mathematical descriptions that had no physical meaning until they were multplied with their complex conjugates. Why not dynamics? The negative mass thing is still a puzzle to me though.
the board could return to a 5-5 moderate-conservative split
Dembski's chief argument is that Dawkins's algorithm—and Darwinism generally—does not do what it seems. Indeed despite our unerring arrival at METHINKS…, the "Darwinian mechanism does not generate actual specified complexity but only its appearance." How can Dembski possibly claim such a thing? Enter the No Free Lunch theorems.
The NFL theorems compare the efficiency of evolutionary algorithms; roughly speaking, they ask how often different search algorithms reach a target within some number of steps.7Because the NFL theorems are deeply counterintuitive, it'll help to start with an informal rendition. It runs like this: If algorithm A beats algorithm B at some class of problems there will always be another class of problems at which B beats A. Further, one can show that A and B are equally efficient when averaging over all possible problems. The NFL theorems thus show that there's no such thing as a universally efficient algorithm: when faced with all problems, any algorithm is as good as any other. To appreciate Dembski's "generic" form of the NFL theorems, you need to appreciate that reaching a prespecified target with a particular fitness function is an example of a problem. Reaching the target with a different fitness function is a different problem. The NFL theorems thus say that if we average over all possible fitness functions—where some lead directly uphill to the target and others don't, and some are smooth and others rugged—no evolutionary algorithm outperforms any other. But one allowable algorithm is blind search, where we randomly move to a neighboring sequence regardless of its fitness (remember our monkey with a word-processor). The NFL theorems thus prove that no evolutionary algorithm beats blind search when averaging over all fitness functions. A surprising result.
The apparent success of Dawkins's algorithm at getting to METHINKS… must therefore be just that, an appearance. If Dawkins tried reaching his target when averaging over all fitness functions, he'd find he does no better than blind search. So why does Dawkins's algorithm seem to work? The answer is that it subtly cheats: it starts not only with a target but also with a fitness function that leads straight to it. Everything's been cooked into the fitness function. Algorithms like Dawkins's thus "fail to generate specified complexity because they smuggle it in during construction of the fitness function."8
Hence Dembski's big claim: "Darwinian mechanisms of any kind, whether in nature or in silico, are in principle incapable of generating specified complexity." At best, Darwinism just shuffles around preexisting specified complexity, using up that available in the fitness function to give the appearance of producing it de novo.
We can now complete the Dembskian Syllogism: Organisms show specified complexity; Darwinism can't make it; therefore, something else does. You won't be surprised to learn that that something else is intelligence. Indeed the "great myth of contemporary evolutionary biology is that the information needed to explain complex biological structures can be purchased without intelligence."
Nice answer, wrong question
The problem with all this is so simple that I hate to bring it up. But here goes: Darwinism isn't trying to reach a prespecified target. Darwinism, I regret to report, is sheer cold demographics. Darwinism says that my sequence has more kids than your sequence and so my sequence gets common and yours gets rare. If there's another sequence out there that has more kids than mine, it'll displace me. But there's no pre-set target in this game. (Why would evolution care about a pre-set place? Are we to believe that evolution is just inordinately fond of ATGGCAGGCAGT…?) Dembski can pick a prespecified target, average over all fitness functions, and show that no algorithm beats blind search until he's blue in the face. The calculation is irrelevant. Evolution isn't searching for anything and Darwinism is not therefore a search algorithm. The bottom line is not that the NFL theorems are wrong. They're not. The bottom line is that they ask the wrong question for what Dembski wants to do. More precisely, the proper conclusion isn't that the NFL theorems derail Darwinism. The proper conclusion is that evolutionary algorithms are flawed analogies for Darwinism.9
The astonishing thing is that Dembski knows all this. In a remarkable revelation—and one that follows two hundred pages of technical mumbo-jumbo—Dembski suddenly announces that Darwinists won't find his NFL objection terribly relevant. And why not? For the very reason I just gave. Dembski even quotes Richard Dawkins at length, who, it turns out, warned all along that his METHINKS… example is
…misleading in important ways. One of these is that, in each generation of selective "breeding," the mutant "progeny" phrases were judged according to the criterion of resemblance to a distant ideal target, the phrase METHINKS IT IS LIKE A WEASEL. Life isn't like that. Evolution has no long-term goal. There is no long-distance target, no final perfection to serve as a criterion for selection….In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success.10
At this point the reader of Dembski's book is a tad confused. Why, given the above revelation, is the book entitled No Free Lunch? Why is its dust jacket lined with blurbs from physicists attesting that Dembski has done something big? And, most important, why did I spend two nights reading about a theorem that reports an irrelevant result? The reader at this point has some right to know what Dembski's real problem with Darwinism is. And he comes through. After two hundred pages, Dembski finally unveils his Über-Objection: Darwinism does "not guarantee that anything interesting will happen." (I'm not making this up.) Darwinism, he admits, will work on a small scale—it will make bacteria resistant to antibiotics and insects resistant to insecticide—but it might not work on a big scale, yielding complex critters and the breathtaking biological diversity that envelops the earth. Dembski's problem isn't then with Darwinism per se. Like the scientific creationists before him, it's with Darwinism writ large. He's worried about the proper limits of extrapolation. And the non-extrapolationist evolution he ends up allowing—one that tinkers but doesn't innovate—is "certainly not a form of Darwinism that is worth spilling any ink over."
There are so many problems with this view that it's hard to know where to start. For one thing, it's wholly subjective. Though Dembski enjoys dressing up his claims in mathematical garb, his key objection to Darwinism ends up being a tad less rigorous than set theory: whether he finds the likely products of natural selection "interesting." For two of the 3.5 billion years of life, nothing fancier than bacteria lived on earth. Is this interesting? A virus might only have four genes. Is this interesting? Just where does one draw the line between beasts or changes that are sufficiently uninteresting that they can be subsumed under a Darwinian mechanism and those that are sufficiently interesting that they can't? Dembski's equations are silent here. For another thing, Dembski's anti-extrapolationist view leads him into some formal muddy waters. If, as he oddly continues to claim, the NFL theorems pose a problem for Darwinism, why don't they pose a problem for a little Darwinism? The NFL theorems don't say anything about scale. To say then, as Dembski does, that a little bit of Darwinism is okay (despite NFL) but a lot is bad (because of NFL) is to say something odd. Dembski comes precariously close here to saying that while there's no such thing as a free lunch, you can help yourself to brunch. Last, surely it's the refusal to extrapolate Darwinism from the small to the large scale that needs justifying. If Darwinism can explain small changes in organisms over the last fifty years (antibiotic resistance, say), surely it can explain progressively bigger changes over the last 500, 5000, or 50,000 years. The cumulative effects of mutation and selection aren't going to get smaller. Dembski's anti-extrapolationism seems a lot like saying that, while Kepler's laws might hold on any given day, they don't hold over whole years. Such a position is, I suppose, formally possible but it—and not extrapolation—requires special justification.
Alas, Dembski's attempts to explain why Darwinism won't extrapolate don't wash. He offers two reasons. The first is that things get simpler not fancier under Darwinism. "Simplicity by definition always entails a lower cost in raw materials…than increases in complexity, and so there is an inherent tendency in evolving systems for selection pressures to force such systems toward simplicity." Darwinism thus chokes when confronting a biological world that's so baroque. This is an ancient argument and the replies to it are equally old. Even if selection favors simplicity, note that the history of life must show a trend of increasing complexity. The reason is this history starts at zero complexity. On average it can only go up (where we cannot see the descendants of lineages that crashed and burned back into zero complexity). There are also good reasons for thinking that organisms get stuck at higher levels of complexity. John Maynard Smith and Eörs Szathmáry argue at book length that the formation of complex assemblies is often irreversible.11 When free living mitochrondria and early cells came together, for instance, to make the first eukaryotic (true) cells, they swapped genes, so that mitochondrial proteins are now encoded by nuclear genes and vice-versa. At this point, things are essentially irreversible and the two partners can't go their separate, simpler ways. Dembski seems unaware of this well known point. Dembski's it-just-gets-simpler argument also relies on an erroneous assumption that natural selection cares primarily about the cost of raw materials. But selection cares only about how many kids you have. If I use more raw materials but have more kids than you, my type gets more common, period. Last, Dembski's argument is betrayed by his own examples of admitted Darwinism. When Salmonella evolved penicillin resistance and the mosquito Anopheles evolved DDT resistance just how did they get simpler? The answer is they didn't.12
Dembski's second anti-extrapolationist argument is that Darwinism could explain the fantastic range of biological diversity only if fitness functions are well-behaved. As he puts it, "the fitness function induced by differential survival and reproduction [may not be] sufficiently smooth for the Darwinian mechanism to drive large-scale biological evolution." If not, natural selection can't gradually ascend lofty fitness peaks and "there is no reason to think you will get anything interesting." Dembski tries here to reconnect his argument with the NFL world—you have to sneak in a fitness function that's just right. But the argument doesn't fly. To see this, consider fitness functions that are as unsmooth as you like, i.e., rugged ones, having lots of peaks and few long paths up high hills. (These are the best studied of all fitness landscapes.13) Now drop many geographically separate populations on these landscapes and let them evolve independently. Each will quickly get stuck atop a nearby peak. You might think then that Dembski's right; we don't get much that's interesting. But now change the environment. This shifts the landscape's topography: a sequence's fitness isn't cast in stone but depends on the environment it finds itself in. Each population may now find it's no longer at the best sequence and so can evolve somewhat even if the new landscape is still rugged. Different populations will go to different sequences as they live in different environments. Now repeat this for 3.5 billion years. Will this process yield interesting products? Will we get different looking beasts, living different kinds of lives? My guess is yes. Dembski's is no. And that is, I suppose, fine. He's entitled to his guess. But don't let him tell you that it follows ineluctably from some mathematical theorem because it doesn't. The troubling thing is that the above scenario isn't some contrived attempt to sidestep Dembski. It's the standard explanation of why organisms don't get permanently stuck on local peaks. For one brief moment Dembski seems to realize that changing environments might matter, pulling the rug out from under his it-won't-go-anywhere argument. But the worry is quickly dispatched with a footnote: "More precisely, f needs to be an evolving fitness function indexed by time. My argument, however, remains intact." Unfortunately it doesn't.