Erwin and Davidson have made a bold start with their clue list ruling out neo-Darwinism. But the evidence explored in these pages suggests additional attributes that need to be added to their profile of the actual cause of the Cambrian explosion. Our previous investigations have suggested that building an animal requires specified or functional information and that any explanation for the origin of the Cambrian animals must identify a cause capable of generating:
digital information
structural (epigenetic) information
functionally integrated and hierarchically organized layers of information
Still, do any or even all of these clues add up to a reason for considering that an alternative kind of cause—a designing intelligence—might have played a role in the origin of animal life?
They do. As it turns out, each of the features of the Cambrian animals and the Cambrian fossil record that constitute negative clues—clues that render neo-Darwinism and other materialistic theories inadequate as causal explanations—also happen to be features of systems known from experience to have arisen as the result of intelligent activity. In other words, standard materialistic evolutionary theories have failed to identify an adequate mechanism or cause for precisely those attributes of living forms that we know from experience only intelligence—conscious rational activity—is capable of producing. That suggests, in accord with the method of historical scientific reasoning elucidated in the previous chapter, the possibility of making a strong historical inference to intelligent design as the best explanation for the origin of those attributes.
Let’s have a look at each of these features of the Cambrian event, starting with key features of the Cambrian animals themselves, to see how they might point to the past activity of a designing intelligence, thereby making intelligent design scientifically detectable.
The Cambrian Information Explosion
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.11 And as we have seen, Microsoft’s Bill Gates notes: “DNA is like a computer program but far, far more advanced than any software ever created.”12
Yet we’ve also seen that neither neo-Darwinism nor any other materialistic evolutionary model or mechanism explains the origin of the genetic information (the digital code) necessary to produce the Cambrian animals or even the simplest structural innovations that they exhibit. Could this—from a materialistic point of view—unexplained appearance of design point instead to actual intelligent design?
I think it does. But to explain why, I need to tell a bit more about the “evolution” of my own thinking on the matter.
After learning about how historical scientists make inferences about the causes of events in the remote past, I first applied these methods of reasoning to the question of the origin of the information necessary to produce the first living cell. My book Signature in the Cell used the method of multiple competing hypotheses (or inference to the best explanation) to evaluate the “causal adequacy” of proposed explanations for the ultimate origin of biological information. I showed that chemical evolutionary models (whether based upon chance, physical-chemical necessity, or the combination of the two) failed to identify a cause capable of producing the digital information in DNA and RNA. Yet we do know of a cause that has demonstrated the causal power to produce digital code. That cause is intelligent agency. Since intelligent agency is the only cause known to be capable of generating information (at least starting from nonliving chemicals), intelligent design offers the best explanation for the origin of the information necessary to produce the first organism.
The case for intelligent design in Signature was carefully limited as a challenge to chemical evolution. Many evolutionary biologists acknowledge that chemical evolutionary theory has failed to account for the origin of the first life. Many cite its inability to account for the origin of biological information as one of the main reasons for that failure. Moreover, because they do not think that natural selection could have played a significant role in evolution until after the first self-replicating organisms had arisen, most evolutionary biologists also think that explaining the origin of information in a prebiotic context is much more difficult than explaining the origin of new information in already living organisms.
For this reason, in Signature I did not try to argue that intelligent design might help explain the origin of the information necessary to account for the origin of new animals from simpler preexisting forms of life. That would have required a separate demonstration showing the inadequacy of natural selection and mutation as a mechanism for generating new genetic information in already living organisms. This book—in Chapters 9–14—has provided that demonstration. These chapters show how neo-Darwinism fails to explain the origin of genetic information—at least, in amounts necessary to build a new protein fold. Chapters 15 and 16 showed, in addition, that the other main materialistic evolutionary theories also fail to account for the information necessary to build new forms of animal life. These theories presuppose, rather than explain, the origin of the information necessary for structural innovation in the history of life. And since the Cambrian explosion of animal life is an explosion of information and structural innovation, that raises a question. Is it possible that this increase of biological information not only represents evidence against materialistic theories of biological evolution, but also positive evidence for intelligent design?
A Cause Now in Operation
It does. Intelligent agents, due to their rationality and consciousness, have demonstrated the power to produce specified or functional information in the form of linear sequence-specific arrangements of characters. Digital and alphabetic forms of information routinely arise from intelligent agents. A computer user who traces the information on a screen back to its source invariably comes to a mind—a software engineer or programmer. The information in a book or inscription ultimately derives from a writer or scribe. Our experience-based knowledge of information flow confirms that systems with large amounts of specified or functional information invariably originate from an intelligent source. The generation of functional information is “habitually associated with conscious activity.”13 Our uniform experience confirms this obvious truth.
It also suggests, therefore, that intelligent design meets the key “causal adequacy” requirement of a good historical scientific explanation. Certainly, intelligence is a “cause now in operation” capable of generating functional or specified information in a digital form. As I write this, my mind is generating specified information. Intelligent agents generate information in the form of software code, ancient inscriptions, books, encrypted military codes, and much else. And since we know of no “presently acting” materialistic cause that also generates large amounts14 of specified information (especially in a digital or alphabetic form), only intelligent design meets the causal adequacy requirement of a historical scientific explanation. In other words, our uniform experience of cause and effect shows that intelligent design is the only known cause of the origin of large amounts of functionally specified digital information. It follows that the great infusion of such information in the Cambrian explosion points decisively to an intelligent cause.
Intelligent design stands alone as an explanation for the origin of genetic information for another reason: purposive agents have just those necessary powers that natural selection lacks as a condition of its causal adequacy. We have seen that natural selection lacks the ability to generate novel information precisely because it can only act after new functional information has arisen. Natural selection can favor new proteins
and genes, but only after they perform some function (influencing reproductive output). The job of generating new functional genes, proteins, and systems of proteins therefore falls entirely to random mutations. Yet without functional criteria to guide a search through the space of possible sequences, random variation is probabilistically doomed. What is needed is not just a source of variation (i.e., the freedom to search a space of possibilities) or a mode of selection that can operate after the fact of a successful search, but instead a means of selection that (a) operates during a search—before success—and that (b) is guided by information about or knowledge of a functional target.
Demonstration of this requirement has come from an unlikely quarter: genetic algorithms. Genetic algorithms are programs that allegedly simulate the creative power of mutation and selection. Richard Dawkins, Bernd-Olaf Küppers, and others have developed computer programs that putatively simulate the production of genetic information by mutation and natural selection.15 Yet these programs succeed only by the illicit expedient of providing the computer with a “target sequence” and then treating proximity to future function (i.e., the target sequence), not actual present function, as a selection criterion. As mathematician David Berlinski shows, genetic algorithms need something akin to a “forward-looking memory” in order to succeed.16 Yet such foresighted selection has no analogue in nature. In biology, where differential survival depends upon maintaining function, natural selection cannot occur before new functional sequences arise. Natural selection lacks foresight; the process, as evolutionary theorists Rodin and Szathmáry note, works strictly “ ‘in the present moment,’ right here and right now … lacking the foresight of potential future advantages.”17
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. Rational agents have repeatedly demonstrated the capacity to constrain possible outcomes to actualize improbable but initially unrealized future functions. Repeated experience affirms that intelligent agents (minds) uniquely possess such causal powers.
Analysis of the problem of the origin of biological information, therefore, exposes a deficiency in the causal powers of natural selection and other undirected evolutionary mechanisms that corresponds precisely to powers that agents are uniquely known to possess. Intelligent agents have foresight. Such agents can determine or select functional goals before they are physically instantiated. They can devise or select material means to accomplish those ends from among an array of possibilities. They can then actualize those goals in accord with a preconceived design plan or set of functional requirements. Rational agents can constrain combinatorial space with distant information-rich outcomes in mind. The causal powers that natural selection lacks—by definition—are associated with the attributes of consciousness and rationality—with purposive intelligence. Thus, by invoking intelligent design to overcome a vast combinatorial search problem and to explain the origin of new specified information, contemporary advocates of intelligent design are not positing an arbitrary explanatory element unmotivated by a consideration of the evidence. Instead, we posit an entity possessing precisely the causal powers that a key feature of the Cambrian explosion—the explosive increase in specified information—requires as a condition of its production and explanation.
Integrated Circuitry: Developmental Gene Regulatory Networks
Keep in mind, too, that animal forms have more than just genetic information. They also need tightly integrated networks of genes, proteins, and other molecules to regulate their development—in other words, they require developmental gene regulatory networks, the dGRNs that Eric Davidson has so meticulously mapped over the course of his career. Developing animals face two main challenges. First, they must produce different types of proteins and cells and, second, they must get those proteins and cells to the right place at the right time.20 Davidson has shown that embryos accomplish this task by relying on networks of regulatory DNA-binding proteins (called transcription factors) and their physical targets. These physical targets are typically sections of DNA (genes) that produce other proteins or RNA molecules, which in turn regulate the expression of still other genes.
These interdependent networks of genes and gene products present a striking appearance of design. Davidson’s graphical depictions of these dGRNs look for all the world like wiring diagrams in an electrical engineering blueprint or a schematic of an integrated circuit, an uncanny resemblance Davidson himself has often noted. “What emerges, from the analysis of animal dGRNs,” he muses, “is almost astounding: a network of logic interactions programmed into the DNA sequence that amounts essentially to a hardwired biological computational device.”21 These molecules collectively form a tightly integrated network of signaling molecules that function as an integrated circuit. Integrated circuits in electronics are systems of individually functional components such as transistors, resistors, and capacitors that are connected together to perform an overarching function. Likewise, the functional components of dGRNs—the DNA-binding proteins, their DNA target sequences, and the other molecules that the binding proteins and target molecules produce and regulate—also form an integrated circuit, one that contributes to accomplishing the overall function of producing an adult animal form.
Yet, as explained in Chapter 13, Davidson himself has made clear that the tight functional constraints under which these systems of molecules (the dGRNs) operate preclude their gradual alteration by the mutation and selection mechanism. For this reason, neo-Darwinism has failed to explain the origin of these systems of molecules and their functional integration. Like advocates of evolutionary developmental biology, Davidson himself favors a model of evolutionary change that envisions mutations generating large-scale developmental effects, thus perhaps bypassing nonfunctional intermediate circuits or systems. Nevertheless, neither proponents of “evo-devo,” nor proponents of other recently proposed materialistic theories of evolution, have identified a mutational mechanism capable of generating a dGRN or anything even remotely resembling a complex integrated circuit. Yet, in our experience, complex integrated circuits—and the functional integration of parts in complex systems generally—are known to be produced by intelligent agents—specifically, by engineers. Moreover, intelligence is the only known cause of such effects. Since developing animals employ a form of integrated circuitry, and certainly one manifesting a tightly and functionally integrated system of parts and subsystems, and since intelligence is the only known cause of these features, the necessary presence of these features in developing Cambrian animals would seem to indicate that intelligent agency played a role in their origin (see Fig. 13.4).
The Hierarchical Organization of Genetic and Epigenetic Information
In addition to the information stored in individual genes and the information present in the integrated networks of genes and proteins in dGRNs, animal forms exemplify hierarchical arrangements or layers of information-rich molecules, systems, and structures. For example, developing embryos require epigenetic information in the form of specifically arranged (a) membrane targets and patterns,
(b) cytoskeletal arrays, (c) ion channels, and (d) sugar molecules on the exterior of cells (the sugar code). As noted in Chapter 13, much of this epigenetic information resides in the structure of the maternal egg and is inherited directly from membrane to membrane independently of DNA.
This three-dimensional structural information interacts with other information-rich molecules and systems of molecules to ensure the proper development of an animal. In particular, epigenetic information influences the proper positioning and thus the function of regulatory proteins (including DNA-binding proteins), messenger RNAs, and various membrane components. Epigenetic information also influences the function of developmental gene regulatory networks. Thus, information at a higher structural level in the maternal egg helps to determine the function of both whole networks of genes and proteins (dGRNs) and individual molecules (gene products) at a lower level within a developing animal. Genetic information is necessary to specify the arrangement of amino acids in a protein or bases in an RNA molecule. Similarly, dGRNs are necessary to specify the location and/or function of many gene products. And, in a similar way, epigenetic information is necessary to specify the location and determine the function of lower-level molecules and systems of molecules, including the dGRNs themselves.
Furthermore, the role of epigenetic information provides just one of many examples of the hierarchical arrangement (or layering) of information-rich structures, systems, and molecules within animals. Indeed, at every level of the biological hierarchy, organisms require specified and highly improbable (information-rich) arrangements of lower-level constituents in order to maintain their form and function. Genes require specified arrangements of nucleotide bases; proteins require specified arrangements of amino acids; cell structures and cell types require specified arrangements of proteins or systems of proteins; tissues and organs require specific arrangements of specific cell types; and body plans require specialized arrangements of tissues and organs. Animal forms contain information-rich lower-level components (such as proteins and genes). But they also contain information-rich arrangements of those components (such as the arrangement of genes and gene products in dGRNs or proteins in cytoskeletal arrays or membrane targets). Finally, animals also exhibit information-rich arrangements of higher-level systems and structures (such as the arrangements of specific cell types, tissues, and organs that form specific body plans).
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