Darwin's Doubt: The Explosive Origin of Animal Life and the Case for Intelligent Design

by Stephen C. Meyer

Eden pointed out in his Wistar presentation that the combinatorial space corresponding to an average-length protein (which he assumed to be about 250 amino acids long) is 20250—or about 10325—possible amino-acid arrangements. Did the mutation and selection mechanism have enough time—since the beginning of the universe itself—to generate even a small fraction of the total number of possible amino-acid sequences corresponding to a single functional protein of that length? For Eden, the answer was clearly no.

Eden and others questioned whether mutations provided an adequate explanation for the origin of the genetic information necessary to build new proteins, let alone whole new forms of life. As physicist Stanislaw Ulam explained at the conference, the evolutionary process “seems to require many thousands, perhaps millions, of successive mutations to produce even the easiest complexities we see in life now. It appears, naïvely at least, that no matter how large the probability of a single mutation is, should it be even as great as one-half, you would get this probability raised to a millionth power, which is so very close to zero that the chances of such a chain seem to be practically non-existent.”9

In the same way, Sauer established that though many different combinations of amino acids will produce roughly the same protein structure and function, the sequences capable of producing these functional outcomes are still extremely rare. He showed that for every functional 92-amino-acid sequence there are roughly another 1063 nonfunctional sequences of the same length. To put that ratio in perspective, the probability of attaining a correct sequence by random search would roughly equal the probability of a blind spaceman finding a single marked atom by chance among all the atoms in the Milky Way galaxy—on its face clearly not a likely outcome.17

As a Ph.D. student in chemical engineering at the California Institute of Technology in the late 1980s, Douglas Axe (see Fig. 10.1) became interested in evolutionary theory after several fellow graduate students read the then-bestselling book by Richard Dawkins, The Blind Watchmaker. Axe’s compatriots were quickly converted to zealous advocates of Dawkins’s arguments and urged him to read the book for himself. Axe was impressed by the clarity of Dawkins’s writing and illustrations, but he found his case for the creative power of natural selection and random mutations unpersuasive. Whether in the analogies he drew to animal breeding or the computer simulations he used to demonstrate the supposed ability of mutation and selection to generate new genetic information, Dawkins repeatedly smuggled in the very thing he insisted the concept of natural selection expressly precluded: the guiding hand of an intelligent agent.

He found Dawkins’s computer simulation particularly interesting. In The Blind Watchmaker, Dawkins described how he had programmed a computer to generate the Shakespearean phrase: “Me thinks it is like a weasel.”1 Dawkins did this in order to simulate how random mutations and natural selection could generate new functional information. Dawkins programmed the computer first to generate many separate strings (sequences) of English letters. He then programmed it to compare each string to the Shakespearean target phrase and select only the string that most closely resembled that target.2 The program then generated variant versions of that newly selected string and compared those sequences to the target, selecting, again, only the one that most closely resembled the desired target. This eventually generated—after many iterations—a string that matched the target perfectly.

Axe recognized immediately the role that Dawkins’s own intelligence had played. Not only did Dawkins provide the program with the information that he wanted it to generate (“Me thinks it is like a weasel”), he imbued the computer with a kind of foresight by directing it to compare the variant sequences of letters with the desired target. Axe realized that Dawkins’s program did not simulate natural selection, which by...

If the conditional probability of the chance hypothesis, given the number of opportunities it has to occur, is less than ½, then it is more likely than not that the event will not happen by chance. It will be viewed as implausible—more likely to be false than true. Conversely, if the conditional probability of the chance hypothesis, given the number of opportunities it has to occur, is more than ½, then it is more likely than not that the event in question will occur by chance. It will be deemed plausible—more likely to be true than false. And, of course, the smaller the conditional probability associated with a hypothesis, the more implausible the hypothesis—the more likely the chance hypothesis is to be false than true.

Douglas Axe had succeeded in making a rigorous estimate of the rarity of proteins in sequence space, I wondered what neo-Darwinists would say in response. Given the experimental rigor and mathematical precision of the work he reported in the Journal of Molecular Biology in 2004, and the long odds against mutation and selection ever finding a novel gene or functional protein, what could they say? That the probability of a successful search for new genes and proteins was higher than Axe’s experiments suggested? That his methods or calculations were flawed? That no one else had gotten similar results? Since Axe’s work confirmed other analyses and experiments, and since his paper had passed through the careful scrutiny of peer review, none of those responses seemed plausible. Yet defenders of the adequacy of the neo-Darwinian mechanism were far from admitting defeat, as I would soon find out.

The same year, I published a peer-reviewed scientific article about the Cambrian explosion and the problem of the origin of the biological information needed to explain it.1 In the paper, I cited Axe’s results and explained why the rarity of functional proteins in sequence space posed such a severe challenge to the adequacy of the neo-Darwinian mechanism. The article appeared in a biology journal, Proceedings of the Biological Society of Washington, published out of the Smithsonian Institution by scientists working for the Smithsonian’s National Museum of Natural History (NMNH). Because the article also argued that the theory of intelligent design could help explain the origin of biological information (see Chapter 18), its publication created a firestorm of controversy.

Museum scientists and evolutionary biologists from around the country were furious with the journal and its editor, Richard Sternberg, for allowing the article to be peer-reviewed and then published. Recriminations followed. Museum officials took away Sternberg’s keys, his office, and his access to scientific samples. He was transferred from a friendly to a hostile supervisor. A congressional subcommittee staff later investigated and found that museum officials initiated an intentional disinformation campaign against Sternberg in an attempt to get him to resign. His detractors circulated false rumors: “Sternberg has no degrees in biology” (actually he has two Ph.D.’s, one in evolutionary biology and one in systems biology); “He is a priest, not a scientist” (Sternberg is not a priest, but a research scientist); “He is a Republican operative working for the Bush campaign” (he was far too busy doi...

Recall that Douglas Axe estimated the ratio of needles (functional sequences) to strands of straw in the haystack (nonfunctional sequences) to be 1 to 1077 for sequences of modest-length (150 amino acids).

The neo-Darwinian synthesis was formulated during the 1930s before the elucidation of the structure of DNA. Biologists at that time did not yet understand the nature, structure, or precise location of genetic information.11 They did not associate genes with long strings of nucleotide bases along the spine of the DNA molecule. They did not think of genes as long sections of digital code stored in complex biomacromolecules. Instead, after Mendel, but before Watson and Crick, genes were defined operationally as those entities, associated with chromosomes, that produced specific visible or selectable anatomical traits, such as eye color or beak shape.

After 1953, biologists no longer conceived of the gene as an abstract entity. Watson and Crick showed that the gene had a definite locus and structure and that individual genes contain hundreds or thousands of precisely sequenced nucleotide bases, each functioning as digital characters in a larger instruction set. Consequently, biologists changed their understanding of mutations as well. Biologists came to understand mutations as something like typographic errors in long strings of digital code. As a result, many scientists began to realize that individual mutations were unlikely by themselves to produce new beneficial traits. Some scientists realized that mutations were instead overwhelmingly more likely to degrade the information contained in a gene than to produce a new function or trait, and that the accumulation of mutations would eventually and typically result in the loss of function.

Although they calculated a shorter waiting time then Behe did, their result nevertheless underscored the implausibility of relying on the neo-Darwinian mechanism to generate coordinated mutations during the relevant evolutionary timescale. Their calculation suggested that it would take not several hundred million years, but “only” 216 million years to generate and fix two coordinated mutations in the hominid line—more than thirty times the amount of time available to produce humans and chimps and all their distinctive complex adaptations and differences from their inferred common ancestor.

In seeking to refute Behe, Durrett and Schmidt inadvertently confirmed his main contention. As they acknowledged, their calculation implies that generating two or more coordinated mutations is “very unlikely to occur on a reasonable timescale.”32 In sum, calculations performed by both critics and defenders of neo-Darwinian evolution now reinforce the same conclusion: if coordinated mutations are necessary to generate new genes and proteins, then the neo-Darwinian math itself, as expressed in the principles of population genetics, establishes the implausibility of the neo-Darwinian mechanism.

Darwin’s doubt about the Cambrian explosion centered on the problem of missing fossil intermediates. Not only have those forms not been found, but the Cambrian explosion itself illustrates a profound engineering problem that fossil evidence does not address—the problem of building a new form of animal life by gradually transforming one tightly integrated system of genetic components and their products into another.

These different sources of epigenetic information in embryonic cells pose an enormous challenge to the sufficiency of the neo-Darwinian mechanism. According to neo-Darwinism, new information, form, and structure arise from natural selection acting on random mutations arising at a very low level within the biological hierarchy—within the genetic text.

Yet both body-plan formation during embryological development and major morphological innovation during the history of life depend upon a specificity of arrangement at a much higher level of the organizational hierarchy, a level that DNA alone does not determine. If DNA isn’t wholly responsible for the way an embryo develops—for body-plan morphogenesis—then DNA sequences can mutate indefinitely and still not produce a new body plan, regardless of the amount of time and the number of mutational trials available to the evolutionary process. Genetic mutations are simply the wrong tool for the job at hand.

Even in a best-case scenario—one that ignores the immense improbability of generating new genes by mutation and selection—mutations in DNA sequence would merely produce new genetic information. But building a new body plan requires more than just genetic information. It requires both genetic and epigenetic information—information by definition that is not stored in DNA and thus cannot be generated by mutations to the DNA. It follows that the mechanism of natural selection acting on...

With the publication of On the Origin of Species in 1859, Darwin advanced, first and foremost, an explanation for the origin of biological form. At the time, he acknowledged that the pattern of appearance of the Cambrian animals did not conform to his gradualist picture of the history of life. Thus, he regarded the Cambrian explosion as primarily a problem of incompleteness in the fossil record.

In Chapters 2, 3, and 4, I explained why the problem of fossil discontinuity exemplified by the Cambrian forms has, since Darwin’s time, only intensified. Yet clearly a more fundamental problem now afflicts the whole edifice of modern neo-Darwinian theory. The neo-Darwinian mechanism does not account for either the origin of the genetic or the epigenetic information necessary to produce new forms of life. Consequently, the problems posed to the theory by the Cambrian explosion remain unsolved. But further, the central problem that Darwin set out to answer in 1859, namely the origin of animal form in general, remains unanswered—as Müller and Newman in particular have noted.

For example, evolutionary biologist Keith Stewart Thomson, formerly of Yale University, has expressed doubt that large-scale morphological changes could accumulate by minor changes at the genetic level.38 Geneticist George Miklos, of the Australian National University, has argued that neo-Darwinism fails to provide a mechanism that can produce large-scale innovations in form and structure.39 Biologists Scott Gilbert, John Opitz, and Rudolf Raff have attempted to develop a new theory of evolution to supplement classical neo-Darwinism, which, they argue, cannot adequately explain large-scale macroevolutionary change. As they note:

Starting in the 1970s, many biologists began questioning its [neo-Darwinism’s] adequacy in explaining evolution. Genetics might be adequate for explaining microevolution, but microevolutionary changes in gene frequency were not seen as able to turn a reptile into a mammal or to convert a fish into an amphibian. Microevolution looks at adaptations that concern the survival of the fittest, not the arrival of the fittest. As Goodwin (1995) points out, “the origin of species—Darwin’s problem—remains unsolved.”

Gilbert and his colleagues have tried to solve the problem of the origin of form by invoking mutations in genes called Hox genes, which regulate the expression of other genes involved in animal development—an approach that I will examine in Chapter 16.41 Notwithstanding, many leading biologists and paleontologists—Gerry Webster and Brian Goodwin, Günter Theissen, Marc Kirschner, and John Gerhart, Jeffrey Schwartz, Douglas Erwin, Eric Davidson, Eugene Koonin, Simon Conway Morris, Robert Carroll, Gunter Wagner, Heinz-Albert Becker and Wolf-Eckhart Lönnig, Stuart Newman and Gerd Müller, Stuart Kauffman, Peter Stadler, Heinz Saedler, James Valentine, Giuseppe Sermonti, James Shapiro and Michael Lynch, to name several—have raised questions about the adequacy of the standard neo-Darwinian mechanism, and/or the problem of evolutionary novelty in particular.42 For this reason, the Cambrian explosion now looks less like the minor anomaly that Darwin perceived it to be, and more like a profound enigma, one that exemplifies a fundamental and as yet unsolved problem—the origination of animal form.

Moreover, any doubts that at least some biologists have begun to embrace a post-Darwinian perspective should have been laid to rest in the summer of 2008, when sixteen influential evolutionary biologists met for a private conference at the Konrad Lorenz Institute in Altenberg, Austria. The scientists, whom the science media later dubbed the “Altenberg 16,”3 met to explore the future of evolutionary theory. These biologists had many different, and sometimes conflicting, ideas about how new forms of life might have evolved. But all were united by the conviction that the neo-Darwinian synthesis had run its course and that new evolutionary mechanisms were needed to explain the origin of biological form.

As paleontologist Graham Budd, who was in attendance, explained, “When the public thinks about evolution, they think about [things like] the origin of wings. . . . But these are things that evolutionary theory has told us little about.”

Of course, explaining the origin of form is precisely what has made the Cambrian explosion so mysterious. In Chapter 7, in discussing the idea of punctuated equilibrium, I quoted Cambrian paleontologists James Valentine and Douglas Erwin, who concluded exactly that. They argued that neither punctuated equilibrium nor neo-Darwinism has accounted for the origin of new body plans and that, consequently, biology needs a new theory to explain “the evolution of novelty.”5

The Altenberg 16 sought to address this challenge. Since the conference, and for nearly two decades preceding it, many evolutionary biologists have been working to formulate new theories of evolution, or at least new ideas about evolutionary mechanisms with more creative power than mutation and natural selection alone.

Kauffman encounters this same problem in attempting to explain the origin of the first life as the result of autocatalytic reactions starting from a prebiotic soup. In The Origins of Order, he acknowledges that generating an autocatalytic, or self-reproducing, set of molecules—a crucial step in his origin-of-life scenario—would require “high molecular specificity”17 in the initial set of peptides or RNA molecules. In other words, it would require specificity of arrangement and structure, that is to say, functional information.

In 2007, I participated in a private meeting of evolutionary biologists and other scientists who shared the conviction that a new theory of biological origins is now needed. In attendance were several prominent advocates of the self-organization approach. During the meeting, these scientists presented intriguing analogies from physics and chemistry to show how order might have arisen “for free”—that is, without intelligent guidance—in the biological realm. Yet the order they described in these analogies seemed to have no direct relevance to the complexity—indeed the specified complexity—of genes or cell membranes or animal body plans. Other scientists at the conference challenged the advocates of self-organization to cite known processes that could produce biologically relevant form and information.

Near the end of the meeting one advocate of self-organization privately acknowledged to me the validity of these critiques, admitting that, for now, “self-organization is really more of a slogan than a theory.” Stuart Kauffman, perhaps attempting to make a virtue of the necessity of accepting this explanatory deficit, has recently celebrated the self-organizational perspective for embracing what he calls “natural magic.” In a lecture at MIT, he concluded: “Life bubbles forth in a natural magic beyond the confines of entailing law, beyond mathematization.”45 He went on to explain that one benefit of the self-organizational perspective is that it allows us to be “reenchanted” with nature and to “find a way beyond modernity.”

When Stephen Jay Gould was first wrestling with the question of how new forms of animal life could have arisen so quickly in the fossil record, he considered many possible mechanisms of change. In the famed 1980 paper in which he declared neo-Darwinism “effectively dead,”1 he didn’t just propose allopatric speciation and species selections as new evolutionary mechanisms. He also granted a rehearing to a long discredited idea. Specifically, he argued that large-scale “macromutations” might generate significant innovations in form relatively quickly.2

“The continued insistence on the random nature of genetic change by evolutionists should be surprising for one simple reason: empirical studies of the mutational process have inevitably discovered patterns, environmental influences, and specific biological activities at the roots of novel genetic structures and altered DNA sequences.”55 The depth of Shapiro’s challenge to orthodox neo-Darwinism is profound. He rejects the randomness of novel variation that Darwin himself emphasized and that neo-Darwinian theorists throughout the twentieth century have reaffirmed.56 Instead, he favors a view of the evolutionary process that emphasizes preprogrammed adaptive capacity or “engineered” change, where organisms respond in a “cognitive” way to environmental influences, rearranging or mutating their genetic information in regulated ways to maintain viability.

As an example, Shapiro notes that—contrary to the neo-Darwinian assumption that “DNA alterations are accidental”57—all organisms possess sophisticated cellular systems for proofreading and repairing their DNA during its replication. He notes that these systems are “equivalent to a quality-control system in human manufacturing,” where the “surveillance and correction” functions represent “cognitive processes, rather than mechanical precision.”58

As an example of regulated mutation, Shapiro observes that in response to environmental assault—UV damage from sunlight or the presence of an antibiotic, for instance—bacteria activate what is known as the “SOS response” system. This system makes use of specialized error-prone DNA polymerases, normally left unexpressed, that are synthesized and set into action, allowing the population to generate a much wider range of genetic variation than usual. Bacterial cells regulate this process using a DNA-binding protein known as LexA, which normally represses the error-prone polymerases. When the SOS system is activated by environmental damage, the production of LexA first drops dramatically, allowing expression of the error-prone polymerases, but then rises, which “ensures that as soon as DNA repair occurs . . . LexA [will] reaccumulate and rep...

Dawkins has noted, for example, that the digital information in DNA bears an uncanny resemblance to computer software or machine code.5 He explains that many aspects of livings systems “give the appearance of having been designed for a purpose.”

We have seen that building a Cambrian (or any other) animal would require vast new, functionally specified digital information. Moreover, the presence of such digitally encoded information in DNA presents, at least, a striking appearance of design in all living organisms. As Richard Dawkins observes, for example, “The machine code of the genes is uncannily computer-like.”10 Similarly, biotechnology pioneer Leroy Hood refers to the information stored in DNA as “digital code” and describes it in terms reminiscent of computer software.

Bill Gates notes: “DNA is like a computer program but far, far more advanced than any software ever created.”12

What natural selection lacks, intelligent design—purposive, goal-directed selection—provides. Rational agents can arrange both matter and symbols with distant goals in mind. They also routinely solve problems of combinatorial inflation. In using language, the human mind routinely “finds” or generates highly improbable linguistic sequences to convey an intended or preconceived idea. In the process of thought, functional objectives precede and constrain the selection of words, sounds, and symbols to generate functional (and meaningful) sequences from a vast ensemble of meaningless alternative possible combinations of sound or symbol.18 Similarly, the construction of complex technological objects and products, such as bridges, circuit boards, engines, and software, results from the application of goal-directed constraints.19 Indeed, in all functionally integrated complex systems where the cause is known by experience or observation, designing engineers or other intelligent agents applied constraints on the possible arrangements of matter to limit possibilities in order to produce improbable forms, sequences, or structures.