Return of the God Hypothesis: Breakthroughs in Physics, Cosmology, and Biology Seeking Evidence for the Existence of God

by Stephen C. Meyer

The testimony of one of the scientists who held this latter view particularly stood out. Professor Dean Kenyon was an authority on chemical evolutionary theory and the scientific study of the origin of life. He held a PhD in biophysics from Stanford, had done research at NASA, and had published numerous scientific papers on the origin of life. In 1969, he also coauthored a seminal book on the topic titled Biochemical Predestination, a book that by 1985 had established itself as the bestselling advanced-level text on chemical evolutionary theory. In Biochemical Predestination, Kenyon and his coauthor, Gary Steinman, argued that life might have arisen as crucial protein molecules first “self-organized” without assistance from DNA as the result of purely natural forces of chemical attraction between the smaller amino-acid subunits out of which proteins are made.

Many leading origin-of-life biochemists hailed this bold hypothesis as the most plausible chemical evolutionary approach to explaining the origin of life. Yet by the late 1970s, Kenyon himself began to question the plausibility of his own theory. Experiments increasingly contradicted the idea that functional proteins could have assembled themselves from their amino-acid building blocks without preexisting genetic information in DNA directing the process. This forced Kenyon to reconsider the importance of DNA for building proteins and to search for an explanation for the origin of the information it contained. As he studied the structure of the DNA molecule more, Kenyon realized that the information in it could not have “self-organized.” To say otherwise would be like saying a newspaper headline might arise as the result of the chemical attraction between ink and paper.

In Dallas, Kenyon publicly and dramatically repudiated his theory of “biochemical predestination.” He also expressed misgivings about other chemical evolutionary theories and argued that the presence of information in the DNA molecule defied explanation by all ...

Kenyon wasn’t the only scientist on the panel who had come to this conclusion. A year before the conference, in 1984, chemist Charles Thaxton, polymer scientist Walter Bradley, and geochemist Roger Olsen published a book challenging the current chemical evolutionary theories of the origin of life. The book, titled The Mystery of Life’s Origin, was published by Philosophical Library, at the time a prestigious New York scientific publisher that had previously published works by more than twenty Nobel laureates. In Mystery, Thaxton and his colleagues exposed many deficiencies in the various ch...

They argued that, for various reasons, getting from chemistry to code unaided by an intelligence pos...

Few people realize that Darwin’s theory of biological evolution did not explain, or attempt to explain, how the first life—presumably a simple one-celled organism—might have first arisen. Instead, Darwin’s theory sought to explain the origin of new forms of life from simpler preexisting forms. Nevertheless, in the 1860s and 1870s many biologists thought that they could devise a materialistic evolutionary explanation for the origin of first life fairly easily. Why? They assumed that life was composed of a rather simple substance called protoplasm that could be easily constructed by combining and recombining simple chemicals such as carbon dioxide, oxygen, and nitrogen.

German evolutionary biologist Ernst Haeckel called this process cell “autogeny” and likened it to the process of inorganic crystallization. An English counterpart of Haeckel’s, T. H. Huxley, proposed a simple two-step method of chemical recombination to explain the origin of the first cell. Just as salt could be produced spontaneously by adding sodium to chloride, so, Haeckel and Huxley thought, could a living cell be produced by combining several chemical constituents and then allowing spontaneous chemical reactions to produce the simple protoplasmic substance they assumed to be the essence of life.

During the 1920s and 1930s a more sophisticated version of this “chemical evolutionary theory” was proposed by Russian biochemist Aleksandr I. Oparin. He too suggested that life could have first evolved as the result of a series of chemical reactions. But he envisioned many more chemical transformations and reactions over hundreds of millions of years. Oparin postulated these additional steps and additional time, because he understood more about the complexity of cellular metabolism than did Haeckel or Huxley.8 Nevertheless, neither he nor anyone else in the 1930s fully appreciated the complexity—and information-bearing properties—of the DNA, RNA, and proteins that make life possible.

To understand why it has been so difficult to explain the origin of the information in DNA and other biomacromolecules in living cells, it’s important to take a closer look at exactly what kind of information DNA, RNA, and proteins contain. In so doing, we’ll see that DNA does not contain information in just the mathematical sense described by modern information theory as developed during the late 1940s by the MIT scientist Claude Shannon (Fig. 9.6).9 Shannon’s theory equated the amount of information with the amount of uncertainty that was reduced by a series of symbols or characters.10 In Shannon’s theory, the more improbable an event or sequence, the more uncertainty it eliminates and thus the more information it conveys.

inwehnsdysk]ifhsnmcpew,m.sa Time and tide wait for no man. Clearly, there is a qualitative difference between these two strings of characters. Whereas the bottom string performs a communication function, the top string does not. Thus, although the top string contains “Shannon information” and has a measurable improbability (or “complexity”), the bottom string contains both Shannon information and “functional” or “specified” information (sometimes called “specified complexity”).12

It turns out that the specific arrangements of bases in DNA, like the arrangement of letters in an English sentence or digital characters in computer software, do not just exhibit a high degree of mathematical improbability. Instead, the specific arrangements of the nucleotide bases (especially in the coding regions of DNA) enable the DNA bases to perform a function in the cell. The bases in DNA convey instructions for building proteins—and do so in virtue of their specificity of arrangement. As Francis Crick explained in 1958, “Information means here the precise determination of sequence, either of bases in the nucleic acid [i.e., in the DNA] or of amino-acid residues in the protein.”13

Thus, DNA not only has Shannon information; it also contains “specified” or “functional” information. Consequently, it also contains information in the ordinary sense of “alternative sequences or arrangements of characters that produce a spe...

Thus Richard Dawkins notes that “the machine code of the genes is uncannily computer-like.”14 And software developer Bill Gates observes that “DNA is like a computer program.”15 Similarly, biotechnology specialist Leroy Hood describes the information stored in DNA simply as “digital code.”16 After the early 1960s, further discoveries made clear that the digital information in DNA and RNA represents only part of a complex information-transmission and -processing system—an advanced ...

I show that the probability of producing even a single functional protein of modest length (150 amino acids) by chance alone in a prebiotic environment stands at no better than a “vanishingly small” 1 chance in 10164, an inconceivably small probability. To put this number in perspective, recall that physicists estimate that there are only 1080 elementary particles in the entire universe.

In short, it is extremely implausible to think that even a single protein would have arisen by chance on the early earth even taking into account the “probabilistic resources” of the entire universe over its 13.8-billion-year history. And a single protein, keep in mind, does not a living cell, with its many hundreds of specialized proteins, make.

For these and other reasons, serious origin-of-life researchers now consider “chance” an inadequate explanation for the origin of biological information.21 Nobel laureate Christian de Duve, a leading origin-of-life biochemist until his death in 2013, categorically rejected the chance hypothesis precisely because he judged the necessary fortuitous convergence of events implausible in the extreme.22 In a memorable passage in his 1995 article “The Beginnings of Life on Earth,” de Duve made explicit the logic by which he rejected the chance hypothesis.

As he put it, “A single, freak, highly improbable event can conceivably happen. Many highly improbable events—drawing a winning lottery number or the distribution of playing cards in a hand of bridge—happen all the time. But a string of improbable events—drawing the same lottery numbe...

First, the process of natural selection presupposes the differential reproduction of already living organisms and thus a preexisting mechanism of self-replication. Yet self-replication in all extant cells depends upon functional (and therefore sequence-specific, information-rich) proteins and nucleic acids.

And the origin of such information-rich molecules is precisely what Oparin needed to explain. Thus, many rejected his postulation of prebiotic natural selection as question-begging. As the evolutionary biologist Theodosius Dobzhansky insisted, “Pre-biological natural selection is a contradiction in terms.”27 Or as Christian de Duve explained, theories of prebiotic natural selection “need information which implies they have to presuppose what is to be explained in the first place.”28

Since the 1980s, the crisis in origin-of-life research has only deepened. As Francis Crick lamented in 1981, “An honest man, armed with all the knowledge available to us now, could only state that in some sense, the origin of life appears at the moment to be almost a miracle, so many are the conditions which would have had to have been satisfied to get it going.”

In 2008 in the film Expelled, Richard Dawkins publicly acknowledged that “we don’t know” how life originated in the first place and even speculated that the information in DNA might represent a “signature of some kind of designer.”34 Not a divine designer, though. He proposed as an “intriguing possibility” that an alien civilization evolved elsewhere in the cosmos and then “designed” and “seeded” the first life on earth.35

The Mystery of Life’s Origin and the “Intelligent Cause” Hypothesis It was this growing crisis that led Charles Thaxton (Fig. 9.9), Walter Bradley, and Roger Olsen to write The Mystery of Life’s Origin. In it, they not only critiqued then current evolutionary theories, but also proposed a radically new approach. In a philosophical epilogue, they proposed an “intelligent cause” as an explanation for the origin of genetic information necessary to produce life in the first place.37 They also argued that positing such a cause might constitute a completely legitimate and appropriate scientific hypothesis within the historical sciences, a mode of inquiry they called “origins science.”

By the mid-1980s, Dean Kenyon had come to consider this same possibility. For him, the digital information in DNA provided “evidence for intelligent purpose in the cosmos, or design” and he suggested as a result that “the natural theological question should now be reopened by the philosophers.”39

One of the first scientists to develop this principle was the geologist Charles Lyell, who influenced Charles Darwin. Darwin read Lyell’s magnum opus, The Principles of Geology, on the voyage of the Beagle and employed its principles of reasoning in the Origin of Species. The subtitle of Lyell’s Principles summarized the geologist’s methodology: Being an Attempt to Explain the Former Changes of the Earth’s Surface, by Reference to Causes Now in Operation. Lyell argued that when scientists seek to explain events in the past, they should not invoke unknown types of causes. Instead, they should cite causes known from our uniform experience to have the power to produce the effect in question.44 Historical scientists should cite “causes now in operation.” This was the idea behind his famous “uniformitarian” dictum: “The present is the key to the past.”

Darwin himself adopted this methodological principle as he sought to demonstrate that natural selection qualified as a vera causa, that is, a true, known, or actual cause of significant biological change.45 He sought to show that natural selection was causally adequate to produce the effects he was trying to explain.

What did all this have to do with the origin of biological information, what I have called “the DNA enigma”? I wondered if a case for an intelligent cause of the information in DNA could be formulated and justified in the same way that historical scientists would justify any other causal claim about an event in the past.

“The creation of new information is habitually associated with conscious activity.”48 Quastler’s remark hit me like a thunderbolt. It suggested a radical possibility, a way to formulate a rigorous scientific case for intelligent design as an inference to the best explanation—specifically, the best explanation for the origin of biological information.

The creative action of a conscious and intelligent agent clearly represents a known and adequate cause (one “now in operation”) for the origin of specified information. Uniform and repeated experience affirms that intelligent agents can produce large amounts of functional or specified information, whether in software programs, ancient inscriptions, or Shakespearean sonnets. The specified information in the cell also points to intelligent design not just as an adequate explanation, but as the best explanation (Fig. 9.12). Why? Experience shows that large amounts of specified information invariably originate from an intelligent source. This is particularly apparent when the information is expressed in a digital or alphabetic form. A computer user who traces the information on a screen back to its source invariably comes to a mind, that of a software engineer.

Scientists in many fields recognize the connection between intelligence and information and make inferences accordingly. Archaeologists assume that a scribe produced the inscriptions on the Rosetta Stone. The search for extraterrestrial intelligence (SETI) presupposes that specified information imbedded in electromagnetic signals coming from space would indicate an intelligent source.52 As yet radio astronomers have not found any such information-bearing signals. But closer to home, molecular biologists have identified specified information-rich sequences and systems in the cell, suggesting, by the same logic, the past existence of an intelligent cause for those effects.

Our uniform experience affirms that specified or functional information—whether inscribed in hieroglyphics, written in a book, encoded in a radio signal, or produced in an RNA-world “ribozyme-engineering” experiment—always arises from an intelligent source, from a mind, not a strictly material process. So the discovery of functional digital information in the DNA and RNA molecules in even the simplest living cells provides strong grounds for inferring that intelligence played a role in the origin of the information necessary to produce the first living organism.

Indeed, when I first noticed the subtitle of Lyell’s book referring to “causes now in operation,” a light came on for me. I asked myself a question: “What cause now in operation produces digital code or specified information?” Is there a known cause—a vera causa—of the origin of such information? What does our uniform experience tell us? It occurred to me that by Lyell’s and Darwin’s own criterion of a sound scientific explanation, intelligent design qualifies as the best explanation for the origin of biological information. Why? Because we have independent evidence—“uniform experience”—that intelligent agents can and do produce specified or functional information and we know of no other cause that does (at least starting from a purely physical or chemical state). Late nineteenth-century scientists knew nothing, of course, about the importance of information to living systems.

They assumed that the universe consisted of two fundamental entities: matter and energy. But during the 1950s and 1960s molecular biologists discovered a third fundamental entity at the foundation of life—information.

the Cambrian explosion. During this event, beginning about 530 million years ago, most major groups of animals first appear in the fossil record in a geologically abrupt fashion. Although the Cambrian explosion of animals is especially striking, it is far from the only “explosion” of new living forms. The first winged insects, birds, flowering plants, mammals, and many other groups also appear abruptly in the fossil record, with no apparent connection to putative ancestors in the lower, older layers of fossil-bearing sedimentary rock. Evolutionary theorist Eugene Koonin describes this as a “biological big bang” pattern. As he notes, “Major transitions in biological evolution show the same pattern of sudden emergence of diverse forms at a new level of complexity.

Any larger-scale changes would have to be built slowly from a long series of smaller-scale, heritable variations. Significant changes to organismal form and function would thus require many hundreds of millions of years. That is precisely what appears unavailable in the case of many salient episodes of evolutionary innovation, such as the Cambrian explosion (Fig. 10.1), the angiosperm (flowering-plant) “big bloom” during the Cretaceous (130 million years ago), and the mammalian radiation in the Eocene period (about 55 million years ago). Darwin hoped the mystery of the missing ancestral fossils would be solved by future geological discoveries documenting the gradual transitions his theory predicted. But the opposite has occurred.

the 160 years since the publication of the Origin, paleontologists have combed geological strata worldwide, looking for the expected precursors to many major groups of organisms4 and have not found the pattern of gradual change (Fig. 10.2) that Darwin anticipated. Instead, new findings have often shown explosions of novel biological form to have been even more dramatic than Darwin realized.

For the mathematically minded scientists at Wistar, doubts about the creative power of the mechanism of random mutation and natural selection stemmed from the elucidation of the nature of genetic information and the confirmation of Francis Crick’s sequence hypothesis during the early 1960s. The discovery that DNA stores information as a four-character digital code raised questions about the efficacy of random mutational changes in producing such information—or at least enough of it to produce a novel protein structure and therefore any major innovation during the history of life.

Murray Eden (Fig. 10.3), one of the MIT professors who convened the event, emphasized that in all computer codes and written texts specificity of sequence determines function. Thus, random changes in sequence consistently degrade function or meaning.

Indeed, no computer programmer wants random changes introduced into a program that he or she has written. Such changes will inevitably degrade and ultimately destroy the function of the existing program long before a new program would emerge through such a process. As Eden explained, “No currently existing formal language can tolerate random changes in the symbol sequences which express its sentences. Meaning is almost invariably destroyed.”9 He suspected that the need for specificity in the arrangement ...

Former MIT computer engineering professor Murray Eden. Eden helped convene the now famed Wistar Institute conference “Mathematical Challenges to Neo-Darwinism” in 1966.

Later, worries about neo-Darwinism spread to evolutionary biologists themselves.10 Over the past three decades, many evolutionary biologists have challenged a key tenet of the neo-Darwinian synthesis, namely, the idea that small-scale microevolutionary changes can be extrapolated to explain large-scale macroevolutionary innovations. For the most part, microevolutionary changes (such as variation in color) merely use or express existing genetic information, while the macroevolutionary change necessary to assemble new organs or whole body plans requires the production of new genetic information. Recognizing this and other problems, in 2008 a group of sixteen evolutionary biologists met in Altenberg, Austria, to discuss their doubts about the creative power of the mechanism of random mutation and natural selection.

Known as the “Altenberg 16,” they and others have called for a new theory of evolution—one based on some mechanism other than—or in addition t...

In November 2016, the Royal Society, the world’s oldest and arguably most august scientific body, over which Isaac Newton once presided, hosted a similar conference in London to address perceived inadequacies in the standard neo-Darwinian theory of evolution. Austrian evolutionary biologist Gerd Müller (Fig. 10.4) opened the proceedings by outlining “the explanatory deficits” of neo-Darwinism, including its inability to explain the origin of “phenotypic complexity” and “anatomical novelty” in the history of life.11

I attended this 2016 meeting and it was clear to me that Müller’s Royal Society audience understood the grave significance of his indictment, though the colorless technical terms “phenotypic complexity” and “anatomical novelty” might have obscured that significance for nonspecialists. What exactly does neo-Darwinism fail to explain? A phenotype refers to the visible form of an animal’s or plant’s anatomy. Müller was therefore saying that standard neo-Darwinian theory has failed to explain the origin of the new and complex anatomical features and structures that have arisen throughout the history of life.

That would include novel animal architectures such as the arthropod, chordate, and molluscan body plans; new anatomical structures such as wings, limbs, eyes, nervous systems, and brains; and new specialized organs such as the vertebrate liver, digestive system, and kidneys. In short, neo-Darwinism fails to explain the origin of the most important defining features of living o...

The Australian molecular biologist Michael Denton, whose 1985 book Evolution: A Theory in Crisis emboldened a number of younger scientists to express their growing doubts about neo-Darwinism.

Drawing on the insights of the Wistar conferees, Denton explained the mathematical reason for this. In English there are vastly more ways “to go wrong than to go right”—that is, for any sequence of any given length, there are more combinations of English letters that will not produce a meaningful phrase or sentence than combinations of those same 26 letters that will generate a meaningful sentence. Indeed, the number of nonfunctional gibberish sequences dwarfs the number of functional combinations. Consequently, random changes in letters are overwhelmingly more likely to “find the gibberish,” or degrade meaning, than to generate a new meaningful sentence, especially as the number of changes to the original meaningful sequence increases.

Moreover, as the length of the required phrase or sentence grows, the number of possible letter sequences of that length grows exponentially, and grows much faster than the number of possible meaningful sequences, so that the probability of finding a functional sequence via a random search diminishes precipitously with necessary sequence length. Denton noted that whereas for every meaningful sequence of English letters 12 letters long there are one hundred trillion (or 1014) corresponding gibberish sequences, for every meaningful sequence of English letters 100 letters long there are 10100 corresponding gibberish sequences, an unimaginably large number. Mathematician David Berlinski (Fig. 10.6) has dubbed this the problem of “combinatorial inflation” in his seminal 1996 essay titled “The Deniable Darwin.”16

Consequently, random mutational changes were overwhelmingly more likely to degrade biological function than to generate a new functional gene or protein.

Thus, to assess the difficulty of a random search, it’s necessary to know how many of the combinations will open the lock. The key isn’t just the number of total combinations that have to be searched, but the ratio of the number of combinations that will open the lock to the total number of combinations. In the same way, it isn’t just the total number of possible combinations in the amino-acid sequence space that determines the difficulty of a random search for a new protein structure. Ultimately, it’s the ratio of functional to nonfunctional sequences that determines the difficulty.

In 1966 at the Wistar conference—and in 1988 when I met Denton—molecular biologists knew that the combinatorial sequence space associated with even a protein of modest length was enormously and exponentially large. Yet they didn’t know how many of those arrangements were functional. In effect, they didn’t know how many of the possible combinations would “open the lock.”