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Only it is not set to detect why a man is dead; but the darker secret of why he is alive. Nothing evolves as surely as anti-evolutionism. The anti-Darwin movement, at least in its popular form, began in the primitive whoops and hollers of young-earthers and seven-day literalists. Their claims, as you might guess, were short on science and long on Genesis.

But somewhat higher in the strata we find a thoroughly transformed, though recognizably related, beast: the scientific creationist. While still relying on some scriptural sources many believed the fossil record reflected a certain forty-day deluge , these creatures did talk science, disputing radioactive dating and making lots of interesting claims about hydrology, pH, and sedimentation.

Following their extinction, the strata reveal yet another and far more advanced form, the Intelligent Design champion.

Compared to this modern species, its predecessors look downright primordial. Indeed the Intelligent Design advocate is characterized by at least three novel traits: i advanced academic degrees; ii sophisticated arguments accompanied by expert knowledge; and iii strict avoidance of religious language, including any speculation on just who the designer might be. While usually admitting that life on earth is billions of years old and that people, pigs, and petunias are related by common descent, the Intelligent Design ID movement maintains that some bits of biology show the unmistakable handiwork of an intelligent agent.

And while this agent may not wholly displace Darwin, the two at least stand shoulder to shoulder. The ID movement further maintains that intelligent design, as a legitimate scientific hypothesis, deserves a place alongside blind evolution in public schools and that students should, at the least, be exposed to both sides of the debate.

Indeed Ohio, which is revising its curricular standards, is currently embroiled in a dispute over the possible introduction of intelligent design into its biology classes. Texas, which dominates the U. Dembski—whose new book, No Free Lunch , is sure to ignite new firestorms over design vs.

Darwin—is perhaps the most impressively credentialed of the lot. He wields a Ph. He is also author of seven books, including The Design Inference , a fairly technical work that laid out a statistical method allegedly allowing reliable detection of design. And, yes, he believes—contrary to everything biologists told us for the last years—that an intelligent agent helped shaped you and me.

To appreciate the magnitude of Dembski's claims in No Free Lunch you need to appreciate the relative modesty of Darwin's claims in the Origin of Species. Darwin did not rule out the formal possibility of a designer. Instead, he showed that the apparent design residing in organisms could be explained naturally, without recourse to a designer.

And while he marshaled great masses of evidence for the role of his natural mechanism natural selection and against the role of a designer, Darwin made no claims about the impossibility of the latter hypothesis.

Dembski's claims are more ambitious. Darwinism, he says, is formally incapable of explaining certain features of organisms. This is not to say that Darwinian mechanisms might not act now and then—Dembski agrees they might—but it is to say that Darwinism is mathematically barred from explaining certain things we always thought it could explain. And unfortunately for evolutionary biology, these things are not trivial arcana but the characteristic features of organisms: their staggeringly complex designs.

We'll sharpen the sense of "complex" below. Dembski does not mince words: "[I]ntelligent design utterly rejects natural selection as a creative force capable of bringing about the specified complexity we see in organisms. This is a big claim. And it explains why Dembski gets so much attention. You might whip up a bit of applause if you say that a designer can explain biology. But you'll bring down the house if you say that Darwinism can't and only a designer can.

Especially if this claim gets dressed up in fancy mathematics of the sort that presumably intimidates biologists but snows the general reader. And this is precisely how Dembski dresses his claims. Borrowing results from computing theory—the so-called No Free Lunch theorems—Dembski claims to prove that Darwinism is utterly impotent before organismic complexity.

Hence a designer. Unfortunately, Dembski's proof has nothing whatsoever to do with Darwinism and his claim to the contrary is hopelessly silly. To show this, I need to back up and do two things. First, explain what kind of biological complexity Dembski is so worked up about and, second, explain why he thinks the No Free Lunch theorems stand in the way of Darwinism accounting for it.

Doing this will require getting slightly technical for a moment. But don't worry—things will get simple again quick. Not all complexity is a thumb in the eye of Darwinism.

The problem, Dembski tells us, comes from a particular variety he calls "specified complexity":. An object, event, or structure exhibits specified complexity if it is both complex i. A long sequence of randomly strewn Scrabble pieces is complex without being specified.

A short sequence spelling the word "the" is specified without being complex. A sequence corresponding to a Shakespearean sonnet is both complex and specified. Dembski argues that biology is replete with specified complexity. It is certainly true that organisms are fantastically complex. It is also true that in some ways but not others—this will become an issue they are specified.

It is clear for instance that the various parts of an organism are fitted to each other: the curvature of the lens is fitted to the distance to the retina so as to produce a sharp image.

Dembski spends a great deal of time formalizing specified complexity in the language of information theory. Roughly speaking, we know we have a case of complex specified information if out of all possible ways of putting together a set of elements—say, all possible sequences of a set of letters and blank spaces—only a small subset represents a prespecified target and the actual outcome belongs to this target. Meaningful English phrases, for instance, represent a small target: the overwhelming majority of random combinations of English letters and blank spaces yield gibberish.

So if you see a meaningful phrase as you hopefully are now , you're seeing complex specified information. Now it's obvious how we go about making meaningful phrases: we use intelligence and crank them out at will. But how do biologists explain the complexity that resides in organisms? By Darwinism. To get a feel for what this means, consider the following caricature of Darwinism offered by Richard Dawkins and discussed at length by Dembski.

Real evolution occurs in a sequence space that uses the four DNA "letters" A, G, C, and T but this is a distinction that doesn't make a difference. First consider the odds of forming this target sequence by blind chance, i. Draw a random letter from the alphabet for the first position in the phrase; now another for the second position, and so on. But now consider the following "evolutionary algorithm.

This example also illustrates the idea of a fitness function. Fitness is a measure of quality; high fitness is good and low is bad. In biology the only kind of quality that matters is how good you are at having kids.

High fitness means you have a lot of kids and low means you have few. A fitness function is just a mathematical function that assigns a fitness value to each possible sequence. A random sequence typically suffers a quite low fitness. If we now pretend that all possible sequences sit in a plane, we could plot their corresponding fitness values above this plane, forming a 3-D plot.

Dembski's chief argument is that Dawkins's algorithm—and Darwinism generally—does not do what it seems. 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. 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. 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.

Hence Dembski's big claim: "Darwinian mechanisms of any kind, whether in nature or in silico, are in principle incapable of generating specified complexity.

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. 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?


No Free Lunch

Only it is not set to detect why a man is dead; but the darker secret of why he is alive. Nothing evolves as surely as anti-evolutionism. The anti-Darwin movement, at least in its popular form, began in the primitive whoops and hollers of young-earthers and seven-day literalists. Their claims, as you might guess, were short on science and long on Genesis.


No Free Lunch: Why Specified Complexity Cannot Be Purchased Without Intelligence

William A. Darwin's greatest accomplishment was to show how life might be explained as the result of natural selection. But does Darwin's theory mean that life was unintended? Dembski argues that it does not. In this book Dembski extends his theory of intelligent design.


A Sublime Detective Story

A Senior Discovery Institute Fellow, Dembski explains that the Darwinian search mechanism of random mutation coupled with natural selection is incapable of generating novel complex, specified information CSI. Natural Darwinian mechanisms can shuffle this information around, but only intelligence can generate novel CSI. In other words, when it comes to generating truly novel biological complexity, Darwin can have no free lunch. Some critics have asserted that he has never applied his model for detecting design to any real biological systems.

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