The Scientific Case for Intelligent Design

A Synopsis of Stephen Meyer’s Signature in the Cell

Harold R. Booher, Ph.D.

February 2010



I. What is the definition of Intelligent Design and how does it differ from religious or philosophical approaches in explaining origins?

II. How do we distinguish most of science from origins science?

III. What is the difference between information science and material sciences, and where does biological science fit?

IV. How is information used in biology to produce proteins?

V. What are the critical questions that any origin of life scientific theory must answer to explain the origin of life?

VI. What scientific method is required for all scientific theories on origins and what are the major competing scientific theories for the origin of life?

VII. How do all evolutionary theories currently fail (scientifically) in explaining the origin of life?

Chance (probability)
Necessity (e.g., existing law)
Combination (Chance and Necessity) (e.g. neo-Darwinism)

VIII. How does one detect Intelligent Design?

IX. How does Intelligent Design explain the origin of life?

X. How is Intelligent Design a scientific theory?

XI. What are some scientific predictions from Intelligent Design?

XII Why is Intelligent Design the best scientific explanation of the origin of life?

Notes and References


According to the Bible nature itself provides the proof for its creation by an outside power. Making a leap from what is seen in nature to its creation by God is credited to people in Hebrews as “faith.” “Faith is the substance of things hoped for, the evidence of things not seen ... ; we understand that the worlds were framed by the word of God, so that the things that are seen were not made of things which are visible. (Heb, 11:1,3). Through faith we understand nature has been designed out of invisible things. From science we have confirmed that the universe is designed from invisible atomic particles.

Scripture uses design as the primary reason people can assume the existence of God. Paul in Roman (1:20) states, “For since the creation of the world His invisible attributes are clearly seen, being understood by the things that are made (designed).”

In science we have more stringent requirements than the ancient world to assure us whether it be by design or merely the appearance of design. Scripture does not require us to infer a specific design based on appearance. For example, it appears that the sun moves daily around the earth and could (in ancient times) be thought to be the actual design of the earth’s and sun’s relationship. Today we know the true design is the earth rotating around the sun, yet we still say “the sun rises” and “the sun sets.”

It is interesting that the Bible claims the design of nature is from an intelligent source. Language was used to create all that was designed. “In the beginning God created the heavens and the earth; … God said, “Let there be light.” (Gen 1:1, 3)) “In the beginning was the Word, and the Word was with God, the Word was God… All things were made through Him, and without Him nothing was made that was made.” (John 1:1,3).

The reasoning that God created all things and that scientists considered themselves to be discovering what God had designed after Him was in fact the view of most scientists from Newton until the mid 19th Century when Darwin proposed his theory of the Origin of Species. The influence of Darwin on science cannot be understated. When a scientist like Richard Dawkins states that it is because of Darwin that he “can be an intellectually fulfilled atheist,” it easy to appreciate how Darwin has changed the view of the origin of nature from one designed to one evolved.

The primary explanation of many scientists of why things appear designed but yet are not, is because all appearance of design in nature, including cells, proteins, DNA, and RNA is illusory. There has to be a materialistic reason for their origin, but it has yet to be discovered. If we simply say God designed it, we are not explaining anything scientifically.

Until quite recently (if one ignores scientific creationists) there has been no real challenge to those claiming evolutionary views as the only scientific views acceptable to science in the study of origins. Finally, however, there is a scientific challenge to Darwinism and other evolutionary explanations of origins that accepts much of the design that is seen in nature as real design, not apparent design – a challenge disassociated from religion and having the detail needed for a scientific explanation. In fact it is possible, although unlikely, that one could be an atheist and accept the argument for intelligent design.1 The case has now been made that not only is Intelligent design a credible scientific approach to the study of origins, but that Intelligent Design is the best scientific explanation currently available for scientific investigation of origins, in particular the origin of life. This case is made by Stephen Meyer in his book Signature in the Cell. 2

The purpose of this paper is to summarize the major reasons Meyer provides for his claim. My approach is to take a question and answer approach that shows how Intelligent Design is truly scientific and why based on scientific reasoning the evolutionary approaches are failing and likely to continue to fail at explaining the origin of life.

One could, of course (and should) read Meyer’s book, but it is some 600 pages and for the non-biologist can be tough going. I believe I can bring forth the major points and issues in a summary fashion as perhaps a preview of Meyer’s more detailed approach. It also puts the major questions about intelligent design in an easy to access organization. For the non-biologist this paper may also be tough going, but if you can get through this you will have had a primer before tackling Signature in the Cell.

For the reader who would like a very short summary of major features of the Meyer argument may skip to Part XII which in about 2 ½ pages presents four reasons that argue why ID is the best scientific explanation of the origin of life.

I. What is Intelligent Design

Intelligent design is a modern scientific and philosophical view of nature that attempts to explain origins in non-evolutionary terms. There are four major unique events in the history of nature that fit the criterion for a designed origin. These are the origin of the universe, the origin of life, the origin of basic body types, and the origin of human intelligence. Intelligent design claims to be the best scientific explanation of origins (especially the origin of life) since all evolutionary explanations depend on something for evolution to work upon. Evolution does not create from nothing and does not create or communicate information intelligently. Intelligent design is the most conceivable source for such specified information complexity as found in proteins, DNA, and RNA since they appear to be products of a communication, not resulting purely from a materialistic process. Intelligence (i.e., human) is the only thing known in the natural world that can communicate specific messages that can create a product or functional result. Intelligent Design does not depend on any religious view of God’s involvement since the intelligence responsible for origins could be within the universe.

II. How do we distinguish most of science from origins science?

Most of science can be classified under “operations science” which can be explained by general laws of physics and chemistry. Intelligent causes for the phenomena produced by operations sciences are not appropriate because these sciences “only deal with regular and repeating phenomena.” Intelligent agents “cannot be described mathematically by laws of nature.” “Origins science, on the other hand, deals with unique, non-repeatable historical events and causes …such as the origin of the universe, formation of the Grand Canyon, and invention of ancient tools and agriculture”. Origins science allows “for the postulation of singular acts of intelligence to explain certain phenomena.”3

III. What distinguishes information science from material science and where does biological science fit?

In discussions of science and the study of origins, we often forget about information science that is totally unique from science that deals with natural laws of physics and chemistry. Information science is almost totally dependent on human intelligence. Information is produced, coded, translated, and interpreted by human intelligence. There is very little beyond the storage machine that plays an important role that is not dependent on human intelligence. Without human intelligence, we would not expect information systems to form on their own from precursors of material and energy. Material and energy do not produce information on their own. Only people do. Biology seems to lie somewhere between information science and regular science, being an entity unlike any of the other products of nature. Life is composed of material, energy, and information. Where did the information come from? Anything which lives must be part of the natural operational process and its behavior can be studied as a process within operational science. Its origins however depend on the use of information that can best be understood using intelligent design terminology.

IV. How is information used in biology to produce proteins?

DNA genetic material provides the information source for the process of protein synthesis (gene expression). This process is a two-stage process of information transfer involving many smaller discrete steps and many molecular machines.4 The process can be thought of as beginning with copying the genetic message (long chains of nucleotide triplets) during a process known as “transcription”. The message is then transported (by the molecular messenger mRNA) to a complex organelle called a ribosome. At the ribosome site, the genetic message is then “translated” (with the aid of a suite of adapter molecules called transfer tRNAs) to produce growing amino-acid chains. These chains fold into the functional proteins the cell needs to survive. Each of these stages “transcription” and “translation” display highly integrated complexity, but translation exhibits greater complexity than transcription. Transcription makes a single stranded copy of DNA in an RNA format, but translation actually uses this information to build a protein.

V. What are the critical questions that any origin of life science must answer to explain the origin of life?

Meyer concludes there are three critical questions that scientists investigating the origin of life must explain. “First they must explain the origin of the system for storing and encoding digital information in the cell.” For example what is the origin of DNA’s ability to store digitally encoded information? “Second they must explain the origin of the large amount of specified complexity or functionally specified information in DNA. Third they must explain the origin of the integrated complexity—the functional interdependence of parts—of the cell’s information system.”5

Question 1. How did the cell’s information processing system originate? The cell’s information processing system has far more parts than DNA, but DNA information is essential for production of proteins that “perform most of the critical functions in the cell.” “Proteins build cellular machines and structures, they carry and deliver cellular materials, and they catalyze chemical reactions that the cell needs to stay alive. Proteins also process genetic information. To accomplish this critical work, a typical cell uses thousands of different kinds of proteins. And each protein has a distinctive shape related to its function, just as the different tools in a carpenter’s toolbox have different shapes related to their function.”6 All proteins are made up from 20 amino acids. DNA has all the information needed to specify the work of a cell, but it is stored in a four-character nucleotide alphabet.7 A genetic code of three letter words links the DNA alphabet to the 20 amino acids alphabet.8 DNA stores the specification that the cell uses to generate physical building blocks (amino acids) which it then uses to chemically construct and physically shape proteins. Although seldom done, the origin of the DNA structure and arrangement of its complex sequence (in such a way to store digitally encoded information) should be the first question that origin-of-life researchers try to answer.

Question 2. What is the origin of the large amount of specified complexity in DNA? DNA has a particular type of information sequence that is followed when performing its functions in a cell. There are three different types of sequences available for the storage of information. The first type is “order”. Order is the simplest type of sequence since it operates in repeating sequences like XYZXYZXYZXYZ Order is highly redundant since once you have seen the first triad of XYZs, the rest are the same. Crystals like ice or salt are made of components having highly redundant order. Ice is H2O over and over. Salt is all NaCl. The more salt you have the more sequences of NaCl you have. No new information is provided beyond the first sequence that is simply repeated. Order is not the kind of sequence found in DNA.

The second type of sequence is basic or mere complexity. A random sequence of complex letters could be something like LNTZBTCZAX. It is complex because nothing in the sequence predicts what the next letter might be. Apparently random polypeptides or polymers can be made up from random sequences of amino acids having basic complexity, but they serve no function. They are unlike complex proteins and DNA that do not have random sequences. They are highly specified to do complex tasks. A set of numbers or letters can be randomly generated to make up mere complexity. For example a series of 10 numbers might be 2965609884. This list of numbers is random, somewhat complex, but meaningless. If a person wanted to call someone with these numbers, who knows who they would reach, if anyone. The same kind of mere complexity can be done with any sequence of letters. MNTDWTROOATIIEAFNEITMA is an arrangement of letters that is complex but the sequence does not communicate anything meaningful. DNA is not made up of mere complexity sequences.

The third type of information sequence is both complex and specified. For example, the same 10 numbers written above might be arranged to correspond to my telephone number 698-840-2956. This is a sequence that is specific and has meaning to anyone wishing to call me. Similarly the above sequence of letters can be arranged in a sequence that is both complex and specified. As an example “Time and Tide wait for no man.” is a sequence of letters which we can understand. DNA, RNA, and proteins have specified complexity just as an arrangement of words and sentences in a human language or the intelligent code of digital computers. Further, the DNA capacity is enormous for its specified sequences. The eukaryotic cell, for example, has a storage capacity many times greater than that of our most advanced silicon chips.9 The origin of this specified complexity and the large capacity inherent in DNA must be explained by origin of life researchers to show any basic understanding of the origin or life. DNA is made up of specified complexity sequences.

Question 3. What is the origin of the integrated complexity—the functional interdependence of parts—of the cell’s information system?

To make matters even more difficult to explain the origin of life is the fact that the complex information stored in DNA is not sufficient on its own to initiate cellular life. Living organisms must also contain systems for processing genetic information. Numerous biochemists and philosophers of science have noted the problem of life being more than identifying the information in DNA
Richard Lewontin states, “No living molecule [i.e. biomolecule] is self reproducing. Only whole cells may contain all the necessary machinery for self-reproduction… Not only is DNA incapable of making copies of itself, aided or unaided, but it is incapable of making anything else… The proteins of the cell are made from other proteins, and without that protein-forming machinery nothing can be made.”
David Goodsell describes the problem: “ The key molecular process that makes modern life possible is protein synthesis, since proteins are used in nearly every aspect of living. The synthesis of proteins requires a tightly integrated sequence of reactions, most of which are themselves performed by proteins.”
Jacques Monod emphasized 40 years ago “The code is meaningless unless translated. The modern cell’s translating machinery consists of at least fifty macromolecular components which are themselves coded in DNA: the code cannot be translated otherwise than by products of translation.”10
The late British philosopher Karl Popper reflected, “What makes the origin of life and the genetic code a disturbing riddle is this: the code cannot be translated except by using certain products of its translation. This constitutes a really baffling circle: a vicious circle it seems, for any attempt to form a model, or a theory, of the genesis of the genetic code.”11

In summary these scientists have observed that the cell needs proteins to process and express the information in DNA in order to build proteins and the construction of DNA molecules themselves also requires proteins. The end result of protein synthesis is required before it can begin. The entire system of protein synthesis must be in place from the beginning. Life in its simplest form needs a complex integrated system of multiple integrated parts to operate. Life cannot exist at the simplest level without the entire system of integrated cellular complexity in place.

VI. What are the major competing scientific theories for the origin of life and what scientific method is required for all scientific theories on origins?

No scientific theory on origins can show results with the confidence of most of our current theories of physics. Newton’s theory of mechanics, Clerk Maxwell’s theory of electromagnetism, Einstein’s theory of relativity, and quantum theory have all been demonstrated by the experimental method of science, which fits within operational science. These features of nature are occurring in the here and now and therefore can be tested to demonstrate the greatest confidence that they are in fact, undeniable facts of nature. Origins cannot be repeated. They must be investigated as questions of history. One might be able to reach high confidence of whether a theory of history is true, but it must compete as the “best explanation” of those postulated.12.

As a theory of history no explanation can reach the scientific confidence that can be shown with the experimental method, but nevertheless, it can be utilized to make a reasonably argued result. The scientific method used in origins science is abduciton.13 This is where the facts of the past event are based on gathered evidence in the present. Both historical and forensic science use abductive reasoning. Determining the cause and convicting someone of a crime is done using abductive reasoning. Depending on how well the evidence is presented and interpreted, the person accused may be convicted or found not guilty. The decision may be correct or in error in so far as the actual truth of the crime, but the jury must decide on the most reasonable interpretation of the event. They cannot actually repeat the criminal event. Scientific theories of origins fall into this category of science, a step below the rigor of the experimental method. So any theory of origins, evolutionary or otherwise, can never be said to have the scientific confident of those scientific theories which rely on current observation and demonstration of the phenomena. Yet if the proper historical criteria are applied to determine one best explanation, then high confidence can be placed on that explanation as best explaining origins.

Currently there are four major theories of origins competing to explain the origin of life.

Three of these are evolutionary theories.

Necessity (or natural law)
Combination of chance and necessity

1. Chance

Chance is measured by probability. Chance refers “to events or processes that produce a range of possible outcomes, each with some probability of occurring.“14 Most people are familiar with chance in betting games. How likely is someone is to get the jackpot when betting at a slot machine or getting a certain set of cards in a poker game? When applied to the origin of life, the thinking is that the start of life appeared in an environment of a “prebiotic soup” say something like Alecksandr Oparin’s early theory that chemical building blocks collected in the earth’s early ocean.15 Scientists who thought (and may still think) this way imagined subunits of DNA, RNA, and protein molecules floated freely in this soup and eventually through chance, these building blocks would combine and recombine to form larger biologically relevant molecules. Meyer states, “chance theories for the origin of biological information typically envision a process of chemical shuffling. This process eventually would produce large specifically sequenced biopolymers (DNA, RNA, and proteins) by chance starting from an assortment of smaller molecules (such as amino acids in the case of proteins, or bases, sugars, and phosphates in the case of DNA and RNA).”16

2. Necessity (or natural law).

Scientists have developed several theories for the origin of life that do not rely on chance but rather speculate the origin comes about out of necessity to follow some type of natural law. One of the first speculations to compete with chance was “self-organization” a type of “biological predestination” originated by Dean Kenyon.17 The term self-organization is used in physics to refer to spontaneous increase in the order of a system due to some natural process, force, or law. “Self-organizational theories of the origin of life try to attribute the organization in living things to physical or chemical forces or processes—ones that can be described mathematically as laws of nature.”18 Kenyon’s model postulated that “simple monomers (e.g., amino acids, bases, and sugars) arose from simpler atmospheric gases and energy; polymers, (proteins and DNA) arose from monomers; primitive membranes formed around these polymers; and a primitive metabolism arose inside these membranes as various polymers interacted chemically with one another.”19

Unlike Oparin’s early model which relied on chance variations to get things started, Kenyon relied on deterministic chemical reactions. Kenyon suggested that each of the Oparin stages (from a prebiotic soup of monomers to complex molecules) came about through some force of chemical necessity. For example perhaps amino acids might have special affinities for each other and out of necessity arranged themselves to form proteins.20

Another prominent self-organization theory for the origin of life is that of Stuart Kauffman. Meyer summarizes Kauffman’s self-organization model as one that tries to bypass the need to generate genetic information to start the process. Kauffman proposes that “a self-reproducing metabolic system might emerge directly from a set of “low specificity” catalytic peptides and RNA molecules in a prebiotic soup, or what he called a “chemical minestrone.”21 Unlike Kenyon who envisioned special affinities among each of the stages but with proteins coming first, Kauffman suggests “Once a sufficient diverse set of catalytic molecules had assembled, .. the ensemble of individual molecules spontaneously underwent a kind of phase transition (akin to crystallization) resulting in a self-reproducing metabolic system.”22 In other words, ”the first metabolic system might have arisen directly from a group of low-specificity polypeptides.”23 In short although Kauffman has some aspects of a protein first theory like Kenyon, he differs by proposing a total metabolic system where no single molecule reproduces itself but rather the system as a whole reproduces itself. In this way he avoids explaining the internal complexity of molecules like DNA and RNA altogether.

3. Combination of chance and necessity

The last evolutionary category for the origin of life considered by Meyer is one which combines chance and necessity. This category is more like neo-Darwinian theory in which chance is provided by mutations and the law like process (necessity) of natural selection. Oparin did model his later approaches on Darwin. Oparin sought to explain the origin of the first life by combining chance and various types of necessity, including both deterministic chemical reactions and a kind of prebiotic natural selection. The first amino acids and other building blocks would come about by necessity after which a series of chance interactions between these first building blocks would eventually result in the first proteins that are needed for establishing metabolic processes. After these larger molecules arose, there would by necessity be competition for nutrients between some of the smaller bodies (called coacervate protocells). In the “struggle for existence” the “more numerous, highly organized protocells would have overwhelmed simpler structures.” The “more metabolically complex and efficienct coacervates would generally outcompete the less complex ones.” This process would eventually produce “a living cell with the features we see today.”24 Oparin’s earlier work was before the discovery of DNA complexity, but his later attempts to explain DNA through prebiotic natural selection was not convincing. He proposed natural selection would act on “unspecified strings of nucleotides and amino acids,” but no one could visualize how this could work. Research showed that “unspecified polypeptides will not replicate genetic information accurately” so there is no useful genetic material for natural selection to act on.25 Oparin was never successful in explaining the origin of genetic information in DNA.

Henry Quasler was one of the first to use chance and necessity in a way that assumed no constraints on how DNA was sequenced. In that way he could avoid the complexity of DNA to get things started. He reasoned, if any sequence would do, then chance alone might produce a set of proteins sufficient to get things started. Chemical necessity could then operate on the unspecified polynucleotides so they could self-replicate via complementary base pairing and produce specific proteins. In his scenario, any polynucleotide sequence would suffice at first, then “at some point, the previously unspecified polynucleotide sequences would acquire specificity and functional significance by their association with a system of other molecules for producing proteins.”26.Quasler’s theory is a DNA first theory.

Perhaps the most popular current theory for origin of life is RNA-first. It has certain advantages over the protein first and DNA first concepts. Carl Woese at the University of Illinois was the first scientist to propose the RNA first idea. Later Walter Gilbert, a Harvard microbiologist expanded the RNA concept into what is now known as the “RNA World.”27 RNA-first advocates believe they can sidestep “the need for an interdependent system of DNA and proteins in the earliest living system.”28 RNA-first combines chance events with the necessity process of natural selection. “As Gilbert and others envision it, a molecule of RNA capable of copying itself … first arose by chance association of nucleotide bases, sugars, and phosphates in a prebiotic soup…. Then because that RNA enzyme could self-replicate, natural selection ensued, making possible a gradual increase in the complexity of the primitive self-replicating RNA system, eventually resulting in a cell with the features we observe today… these RNA enzymes eventually were replaced by the more efficient proteins … in modern cells…. Finally, DNA emerged for the first time by a process called reverse transcription. In this process DNA received the information stored in the original RNA molecule, and eventually these more stable DNA molecules took over the information-storage role that RNA had performed in the RNA world.”29

Finally there have been a number of simulation models (e.g., Ev and and Avida) that claim to demonstrate how evolutionary algorithms (using mutation and selection) can generate new information. Their claim is that “undirected material processes of replication, mutation and selection are necessary and sufficient for information gain to occur.”30

4. Intelligent Design. Except for it being an abductive historical scientific method as are the evolutionary theories, intelligent design is completely different from the evolutionary theories. The evolutionary theories, even though human intelligence is used throughout in their modeling assumptions, give no credibility to intelligence as a source of origins. Intelligent design proposes to explain that something as complex as DNA, RNA, and proteins in a cellular process is explainable only by an intelligent source. There is nothing in the material and energy world that suggests the formation of complex specified sequences of information. The only thing we know in nature that can design products and processes through specifications is human intelligence. Life is so complex that not even human intelligence has been able to produce it. One must conclude that such complexity of information found in the origin of biological systems had to have an intelligent source greater than that of humans.

VII. How do all evolutionary theories currently fail (scientifically) in explaining the origin of life?
VII.A. Why does chance fail in explaining the origin of life?

Most chance hypotheses assume that life cannot originate without biological information first arising in some form. Since DNA stores the information for producing the proteins that perform most critical functions in a cell, scientists must explain either (a) where the information in DNA (or similarly RNA) came from or (b) how proteins might have arisen directly without DNA.31 In nearly all chance based scenarios one of three possibilities (DNA first, protein first, or RNA first) are assumed. If for example DNA is proposed as first arising by chance, it is presumed that later the DNA “came into a functional association with the protein molecules needed to transcribe and translate genetic information into proteins.”32 In these scenarios origin of life theorists first envision some favorable prebiotic environment rich in the building blocks out of which DNA, RNA, and proteins are made.33

There are generally two reasons given for why it might be presumed that chance-based theories are reasonable for bringing about the origin of life’s building blocks even though the odds are against it.. First is the argument that even if odds are very small of a particular event happening, such as getting a specific hand (say a royal flush) dealt in cards or winning the lottery, these events do happen to someone and if we consider all the games played, such outcomes are quite frequent. Predicting the specific outcome is very improbable, yet if all outcomes are equally probable, the one we want could happen. Origin-of-life chance-hypothesis theorists and popularizers of science think in such analogies. Second is the belief vast expanses of time can make the improbable probable. George Wald argued in 1954 the “Time is in fact the hero of the plot… Given so much time, the impossible becomes possible, the possible probable, and probable virtually certain.”34

Meyer and Demski (Chapters 8-10) provide several convincing arguments as to why the chance hypothesis has virtually no chance of producing one DNA or RNA information molecule or even a single functioning protein.

1. Statements like those above on chances in cards or vast time allowing origins of complex molecules or strings of specific meaningful words in biology are vacuous. There are no data or observations to back them up. Further making definite claims does not necessarily mean that the claims are true. Appeals to chance must be justified. In the case of origin of life theories on chance, even the definition of chance by theorists is extremely vague. They are so thin on detail that it is difficult to assess them.35

2. Statisticians and scientists routinely test substantive (as opposed to vacuous) chance hypotheses which allow them to decide when to accept and when to reject chance as an explanation. If a ball on a roulette wheel falls into a given pocket 100 times consecutively no one will believe it is luck. The odds are too low. The odds of the ball falling in the pocket once is 1 chance in 38. For 100 times, it is 1 chance in 38100 or 1 chance in 10158. The gambling managers would suspect either the wheel has a mechanical defect or someone is cheating. They would obviously eliminate the chance hypothesis as a reasonable explanation of the event.36 In the 1920s, Ronald Fisher provided a mathematical method whereby statisticians could “catch” or “identify” events that resulted from factors other than chance by pre-specifying a rejection region. “According to Fisher, chance hypothesis can be eliminated precisely when a series of events that deviates too greatly from an expected statistical distribution of events based on what we know about processes that generate those events or what we know from sampling about how frequently those events typically occur.”37 Origin of life by chance theories do not specify models or criteria for accepting or rejecting chance. Chance is just assumed no matter how unlikely.

3. The probability of useful DNA, RNA, or proteins occurring by chance is extremely small. Calculations vary somewhat but all are extremely small (highly improbable). If one is to assume a hypothetical prebiotic soup to start there are at least three combinational hurdles (requirements) to overcome. Each of these requirements decreases the chance of forming a workable protein. First, all amino acids must form a chemical bond (peptide bond) when joining with other amino acids in the protein chain. Assuming, for example a short protein molecule of 150 amino acids, the probability of building a 150 amino acids chain in which all linkages are peptide linkages would be roughly 1 chance in 1045. The second requirement is that functioning proteins tolerate only left-handed amino acids, yet in abiotic amino acid production the right-handed and left-handed isomers are produced in nearly the same frequency.38 The probability of building a 150-amino-acid chain at random in which all bonds are peptide bonds and all amino acids are L-form is roughly 1 chance in 1090. The third requirement for functioning proteins is that the amino acids must link up like letters in a meaningful sentence, i.e. in a functionally specified sequential arrangement. The chance for this happening at random for a 150 amino acid chain is approximately 1 chance in 10195. It would appear impossible for chance to build even one functional protein considering how small the likelihood is. By way of comparison to get a feeling of just how low this probability is consider that there are only 1065 atoms in our galaxy..

However, scientists in the late 1980s (Robert Sauer and Douglas Axe) asked the question of “how much variance among amino acids might be tolerated at any given site in several proteins.”40 Statistical probabilities for functional sequences like that computed above reflect very rare functional sequences, since amino acids must be arranged precisely in a particular sequence to be considered functional. However, molecular biologists know that “most sites along the chain can tolerate several of the different twenty amino acids commonly found in proteins without destroying the function of the protein.”41 If functional sequences are more common than the mathematicians are supposing, ‘then that would increase the probability that a random search through the space of possibilities would find a functional sequence.”42 Sauer’s experiments found that when the possibility of variance is taken into account in several known proteins (about 100 amino acid sequences long) the probability did indeed increase for achieving a functional sequence. He found that under these conditions, a functional sequence could appear with 1 chance in 1063, a probability much greater than the one calculated above, but still “exceedingly small” (again very comparable with the number of atoms in our galaxy).43

In a more rigorous but similar method to Sauer’s, Douglas Axe calculated that a functionally significant 150 amino acid sequence of a protein called betalactamase would have only about 1 chance in 1074 of being produced by chance.44 Although these odds are highly unlikely in themselves to produce anything significant by chance, they do not begin to address the chance problem of origin of life. For example these latter estimates did not take into account the first two requirements, i.e., using peptide bonds and left-handed amino acids.45 When these requirements are calculated into the overall probability with Axe’s sequence odds, the total probability of getting one functional protein decreases to one chance in 10164.46 And these incredibly low odds for chance to succeed in making just one functional protein do not come close to the far smaller odds of creating something like a minimally complex cell. First Axe’s short protein is not typical. Typical proteins have hundreds of amino acids and often their function requires close association with other protein chains. As an example the typical RNA polymerase has over 3,000 functionally specified amino acids. Finally if we consider a minimally complex cell which needs at least 250 proteins averaging 150 amino acids each, the odds soar to something like one chance in 1041,000.47 It is inconceivable that chance alone could produce either a minimally complex cell or the genetic information necessary to produce those proteins from a prebiotic soup, even if the soup were as large as the universe (there are 1080 protons, neutrons, and electrons in the observable universe).48

4. Nevertheless Meyer is very careful about eliminating chance for the origin of life based solely on the improbability of the event. He also relies on William Demski’s argument that pattern recognition needs to be considered as well. Historical scientists can often successfully explain events after the fact that they could not have predicted before the fact. Patterns are important after the fact for events of low probability. For example a spy cannot tell whether the sounds of an encoded message are random noise or something intelligible. After decoding the signals as meaningful text, through pattern recognition (i.e., a cryptographic key), he can reject chance as providing the improbable event.49 So both pattern recognition and improbability of the event are necessary in explaining the event. In the case of origin of life, the improbability of the information in DNA and RNA to create protein and minimal cell occurring by chance urges us in the direction of eliminating chance. Additionally the pattern recognition of the way DNA codes its information to produce amino acids and produces proteins suggests an intelligent source. The fact that an intelligent source is reasonable from the pattern recognized as intelligent gives another reason to reject chance. If the odds for chance of making DNA functional had been high and an intelligent pattern was not recognized, then chance would have been the better explanation.

5. Even though the odds of creating DNA, RNA, or a protein are extremely low and pattern recognition suggests something other than chance is responsible for the origin of these complex molecules, one still cannot prove by statistics that an unlikely event did not happen or that the existence of an intelligible message in DNA proves that intelligent design created DNA. Because of the vast time belief, origin of life by chance theorists could still maintain that given enough time, perhaps chance could provide the miracle accident of life that appears designed. They seem to think time gives infinite opportunities for life to appear. Meyer brings up a final factor that should convince even the most avid chance theorist that chance as an explanation for the origin of life should be eliminated. This factor is probabilistic resources.50

Probabilistic resources are the number of opportunities that the event in question might have had to occur. One of the sub-factors is time. For the origin of life, time is not all that vast considering the probability numbers we have been working with. Time is limited to all the time since the big bang which although being billions of years is only 1016 seconds. So if we consider the total number of opportunities as consisting of total time (1016 seconds), multiplied by how often elementary particles can interact with each other per second (at most 1043 times) multiplied by the limited number of elementary particles (1080), we have a measure of probabilistic resources of the entire observable universe since the beginning of time which is 10139. The number of events for a functional sequence to happen would be limited to no more than 10139. Other mathematicians and scientists have made similar calculations that range from 1050 to 10120 events but all are smaller than Demski’s number of probabilistic resources. Dembski’s calculation gives chance its “best chance.”51 Since the odds of producing one functional protein by chance is one chance is 10164 Meyer concludes that to have a good (better than 50-50) chance of generating a functional protein by chance, more than half of the 10164 nonfunctional sequences would have to be produced to get 1 functional sequence. The maximum number of opportunities is much less than that needed by more than a trillion, trillion times (.5.x 10164 compared to 10139). When the probability of producing an entire minimal cell is considered (one chance in 1041,000 ) it completely dwarfs all the probabilistic resources of the universe. Taking all those resources (10139) into account only increases the chances of producing a minimal complex cell by chance alone to one chance in 1040,861. The universe itself does not possess the probabilistic resources necessary to make probable the origin of biological information by chance alone.52

VII. B. Why do necessity theories fail to explain the origin of life?

Meyer spends two chapters (11 and 12) describing example necessity theories and their fundamental limitations in explaining the origin of life. Two theorists in particular, Dean Kenyon, a biophysicist at San Francisco State University in his youth and Stuart Kauffman, head of the Sante Fe Institute have long been disillusioned with the possibility of chance being the reason for the formation of life from a prebiotic soup. Both agree that the odds discussed above are too improbable for DNA, RNA, and working proteins to have appeared as a completely random event. Both have proposed self organization theories which act in accordance with Jacques Monod’s description of necessity, i.e. “the lawlike forces of physics and chemistry” being the cause of life’s beginnings.53 Self organization theorists realize they need “to identify a specific lawlike process … that could generate life or critical components of living cells starting from some specific set of conditions.” They need to find “deterministic processes that could help overcome the otherwise long odds against the origin of life occurring by chance alone.”54

Meyer provides several reasons that the self-organization models do not explain the origin of life.

1. Central to the whole issue of biological predestination (or self-organization) is overcoming the DNA enigma. Both Kenyon and Kauffman have focused on proteins forming by self-organization first, since “they knew that proteins perform most of the important enzymatic and structural functions in the cell”55 and believed that perhaps proteins could arise without the help of nucleic acids, so they would not initially need to “explain the origin of DNA and RNA and the information they contained.”56 However, Kenyon realized early on that he could not avoid explaining the origin of genetic information.

(a.) “DNA provides the template of information for building proteins and not the reverse.” There are good reasons for the one-way flow of information. (1.) Each triplet of DNA bases specifies exactly one amino acid during transcription and translation. Yet most amino acids correspond to more than one nucleotide triplet. This feature of the genetic code ensures that information can flow in only one direction without loss of specificity. (2.) Proteins do not possess two anti-parallel stands of identical information and thus cannot be unwound and copied as the DNA helix. (3.) If proteins are unwound from their specific shape they tend to cross-link and aggregate or be quickly destroyed in the cell. (4.) Proteins do not regain their original three-dimensional shape once they lose it whereas DNA is a stable, chemically inert molecule that maintains its chemical structure and composition while other molecules copy its information.57

(b.) Although it might be argued that certain amino acids had differential bonding affinities that caused the first proteins to arise directly from amino acids, there is no evidence of any differential affinities that can be produced by experiment that correlate with known sequencing patterns of large classes of actual proteins.58

Neither Kenyon nor Kauffman has tried to develop a model of self-organization that includes DNA or RNA.

2. Meyer accepts Michael Polanyi’s argument that life transcends physics and chemistry. The existence of DNA and its method of information storage and transmission cannot be explained by laws of physics and chemistry.59 Meyer paraphrases Polanyi’s reasoning “In the case of communication systems, the laws of physics and chemistry do not determine the arrangements of the characters that convey information. The laws of acoustics and the properties of air do not determine which sounds are conveyed by speakers of natural languages…. the chemical properties of ink [do not] determine the arrangements of letters on a page. Instead the laws of physics and chemistry allow a vast array of possible sequences of sounds, characters, or symbols in any code or language. Which sequence of characters is used to convey a message is not determined by physical law, but by the choice of the users of the communications system…[similarly] living things defy reduction to the laws of physics and chemistry because they contain a system of communications—in particular, the DNA molecule and the whole gene-expression system.. .. DNA base sequencing cannot be explained by lower-level laws or properties any more than the information in a newspaper headline can be explained by reference to the chemical properties of ink.”60

3. If the sequences in DNA were biochemically determined, the molecule could not store and transmit information. Because any nucleotide can follow any other, a vast array of sequences is possible, which allow DNA to encode a vast number of protein functions. Polyani explains, “It is this physical indeterminacy of the sequence that produces the improbability of occurrence of any particular sequence and thereby enables it to have a meaning—a meaning that has a mathematically determinate information content equal to the numerical improbability of the arrangement.”61

Up to this point Meyer’s arguments against necessity (self-organization) theories of origins clearly show that there is nothing internal to DNA or proteins that would encourage some lawlike bonding affinities that could self-organize simpler nucleotide bases into DNA or amino acids into functioning proteins.

4. Kenyon and Polyani showed that the differences in internal bonding affinity (both between nucleotide bases and amino acids could not solve the DNA enigma internally for self-organization theories.62 In 1977 Belgian physicist Ilya Prigogine thought he could solve the problem by looking external to DNA and the proteins. In his book with Gregoire Nicolis, Self-Organization in Nonequilibriam Systems Prigogine suggested that energy flowing into the open biological system could cause order to arise spontaneously. In the past, Prigogine had demonstrated that open systems (systems that maintain their organization by utilizing matter and energy from the environment.) driven far from equilibrium (driven far from the normal state they would occupy in the absence of environmental input) frequently displayed self-ordering tendencies as they receive inputs of energy. For example, thermal energy flowing through a heat sink can generate distinctive convection currents or “spiral wave activitiy.” Prigogine recognized that the probability of living systems arising by chance alone were “vanishingly small.”63 However he and Nicolis speculated that if an external source of energy were supplied to simple biochemical parts under nonequilibrium conditions, the biochemical systems might arrange themselves into highly ordered patterns and primitive biological structures.

Up to the present no experiments have been done to test Prigogine’s theory on biochemical bases or amino acids, but even if they did and similar results were found as in his thermodynamics systems, (simple order effects like convection currents and chemical crystals) we could only expect some kind of simple ordering of bases or amino acids, not specified information. Hubert Yockey pointed out to Meyer in an interview, “What needs explaining in biological systems is not order (in the sense of a symmetrical or repeating pattern), but information, the kind of specified digital information found in software, written languages, and DNA.”64

5. Kauffman also looks at external sources to DNA and functional proteins to create his theory. Unlike Prigogine, he has also done a lot of experimentation to demonstrate his self-organization theory. Unfortunately he has not produced either in the lab or by simulation anything that resembles the specified information in DNA, RNA, or proteins. As mentioned before Kauffman does not try to deal with DNA issues, but rather focuses on metabolism-first models. As described in paragraph VI.2 Kauffman believes that an ensemble of relatively short and “low specificity” catalytic peptides and RNA molecules could be enough to establish a metabolic system. To support this idea, he cites the fact that some proteins, like proteases, can perform enzymatic functions with low specificity and complexity.65

Meyer has found four significant information-related problems with Kauffman’s theory.66

(a.) Kauffman does not avoid the problems mentioned for Kenyon’s protein-first model and similar metabolism-first models like (1.) “how the proteins in various metabolic pathways came into association with DNA and RNA;” (2) “how the information in the metabolic system of proteins was transferred from the proteins to DNA,” or (3) “how the sequence specificity of functional polypertides arose (given that the bonding affinities that exist among amino acids don’t correlate to actual amino acid sequences in known proteins.)”67

(b.) Just “because some enzymes might function with low specificity,” it does not follow “that all the catalytic peptides (or enzymes) needed to establish a self-reproducing metabolic cycle could function with similarly low levels of specificity and complexity.”68 Kauffman does not address this problem.

(c.) “The allegedly low specificity molecules (or proteases) that Kauffman cites … are actually very complex and highly specific in their sequencing.” Trypsin for example is a “nonrepeating 247-amino-acid protein that possesses significant sequence specificity as a condition of its function.”69

(d.). Kauffman’s system must start with a large amount of specified information or specified complexity. Kauffman masks this requirement by stating a need for complex information that has an unspecified source. “For autocatalysis to occur, the molecules must be held in a very specific spatial-temporal relationship to one another.”70 Where does the specified information to hold the molecules in this relationship come from?

Kauffman has done some interesting simulations with buttons and strings (and interconnecting lights) to show how the prebiotic environment could be represented. From these simulations (if for example, buttons are considered novel genes and strings lawlike forces of interaction between the genes –e.g. proteins), he maintains that “as a result of these rules [where rules determine how past states will influence future states], the system will, if properly tuned, eventually produce a kind of order in which a few basic patterns [of buttons or] light activity recur with greater than random frequency.” These patterns would of course represent only “a small portion of the total possible states for the system,” but extended they could represent a large set of highly improbable biological outcomes.71

Meyer lists three critical problems with Kauffman’s simulations.

(a.). The patterns produced are not constrained by any functional considerations. They are not analogous to biological systems. While a system of interconnected lights governed by preprogrammed rules might settle into a small number of patterns within a larger space of possibilities (more than random), the failure to have any functional requirements does not model biological organisms. It again is a combination of human intelligence (preprogrammed) producing at most some kind of order, not a specified functional sequence.72

(b.) At times Kauffman produces aperiodic patterns of mere complexity interrupting the general routine of simple order. These patterns are meaningless. DNA, like software programs or sentences on a page are aperiodic but specified. (they do not repeat in a rigid or monotonous way). Kauffman produces large amounts of symmetrical order interspersed with some aperiodic sequences (of mere complexity) lacking function.73

(c.). Even when Kauffman does produce some interesting nonrandom patterns, it seems to come from an unexplained source of information (human intelligence) when the system is “properly tuned.”74

VII.C Why do combination (chance and necessity) theories fail in explaining the origin of life?

Meyer devotes two chapters (13 and 14) describing combination (chance and necessity) theories and their limitations in explaining the origin of life. The first chapter covers Darwinian approaches (mutations and natural selection – chance and necessity) while the second chapter is devoted entirely to the RNA-first approach to the origin of life. Both of these major combinational theories are attempts to avoid the problems discussed with chance alone or law-like nature (self-organization) alone theories eliminated above.

Under the Darwinian approaches the primary problem seen by theorists is solving or avoiding the DNA enigma problem and they attempt to do in various ways. Three of the most familiar approaches are 1. Oprain’s later theory of prebiotic natural selection. 2 Quasler’s DNA-first, and 3. computer evolutionary simulations using mutation and natural selection to produce new information.

Meyer presents cogent arguments to dispel all of the Darwinian combinational theories.

1. Oparin’s theory of prebiotic natural selection was basically the idea that chance would originally produce unspecified strings of nucleotides and amino acids, which natural selection would act upon until the most efficient strings of nucleotides and amino acids that made up functional proteins were produced. The major problem with Oparin’s theory, pointed out by many scientists in the late 1960s, was that prebiotic natural selection was indistinguishable from pure chance hypotheses. “Random molecular interactions were still needed to generate the initial complement of biological information that would make natural selection possible.”75 Vast amounts of functionally specified information would have to arise first as in chance theories, before natural selection could start to improve the process of information generation. Oparin’s Darwinian approach can be rejected for the same reasons as chance alone. It is too improbable for the amount of probabilistic resources available.

2. Henry Quastler’s DNA-first model is really a DNA avoidance model. His major assumption that differed from Oparin was that any sequence of nucleotide bases would be enough at the beginning to appear by chance. Also rather than using the term natural selection, his “unspecified polynucleotides could self-replicate by complementary base pairing by chemical necessity.”76 Quasler expected an initially unspecified sequence that arose by chance could later acquire functional specificity with something he terms an “accidental choice remembered.”77 Basically Meyer argues that Quasler has not solved the problem of complex specificity but only transferred the problem to another system of proteins, RNA molecules, and ribosomes. Quasler really added nothing to the overall problem of a working DNA or protein molecule. However he did seen to anticipate that RNA molecules would somehow need to arise before a total system with DNA and functional proteins could occur.

3. Developers of computer simulations like Ev and Avida claim they can generate new information through sophisticated evolutionary algorithms. The problem with all these algorithms is no matter how sophisticated they need some kind of “forward looking memory”78 Natural selection in nature lacks foresight. It does not know where it is going. Selection cannot occur before new functional sequences arise. In simulation algorithms, they all use strategies to ensure the program will generate an information-rich sequence. For example Ev is provided with a target sequence (sequence of nucleotide bases) that functions as a binding site. A program is devised that allows Ev to eventually converge on the target sequence. It makes use of information that gives the process a goal-directed foresight, that is not like natural selection, but rather is like human selection. “Ev exhibits the genius of its designer.”79

Avida is much more complicated than Ev, but rather than trying to solve the origin of life problem, it tries to demonstrate how biological evolution might generate new biological information starting from a preexisting organism. It begins with virtual organisms programmed to self-replicate. Meyer comments “Avida lacks realism as a simulation of biological evolution because the program selects functionally significant logic functions possessing too little complexity to represent the actual information content of functional proteins or genes.”80 It is a program designed by an intelligent designer which does some interesting functions that might replicate some aspects of evolution, but it only presupposes, not explains the origin of information needed for life.

4. RNA-first is perhaps the most thoroughly thought out evolutionary concept among origin of life theorists. Nevertheless Meyer is quick to point out that although simplistic descriptions might seem reasonable, a detailed analysis of this approach is riddled with problems. Meyer discusses in considerable detail five of the most critical problems.

(a) RNA building blocks are hard to synthesize and easy to destroy. Before the first RNA molecule could have come together, smaller constituent molecules like ribose, phosphate molecules, and the four RNA nucleotide bases (adenine, cytosine, guanine, and uracil) would have had to arisen first. These building blocks have been shown nearly if not totally impossible to create under realistic prebiotic conditions.81

(b) Ribozymes are poor substitutes for proteins. The RNA-first model has RNA replacing proteins in the earliest stages of chemical evolution. Yet RNA molecules have very few of the specific enzymatic properties of proteins. Currently it is known that ribozymes can only perform a few of the thousands of functions performed by proteins. And many of those few functions ribozymes can perform are simply due to scientists intentionally directing the RNA catalyst under consideration.82

(c) An RNA-based Translation and Coding System is implausible. Modern cells rely on a variety of proteins to process genetic information and regulate metabolism. If RNA is to have arisen first and proteins are needed to make genetic encoding, then the RNA-based replication system would eventually have to begin to produce proteins capable of template-directed protein manufacture.” “In short, the evolving RNA world would need to develop a coding and translation system based entirely on RNA and also generate the information necessary to build the proteins that later would be needed to replace it.”83 The question Meyer asks “Is it possible that a … translation and coding system capable of producing genetically encoded proteins might first have arisen using only RNA catalysts (ribozymes)?84 Meyer thinks an RNA-based translation and coding system is simply implausible for three major reasons.

First an RNA-based translation system would be extremely complex. An RNA translation system would include “the ribosome (consisting of fifty distinct protein parts), the twenty distinct tRNA synthetases, twenty distinct tRNA molecules with their specific anticodons, …various other proteins, free floating amino acids, ATP molecules (for energy), and … information rich mRNA transcripts for directing protein synthesis.”85 Such a translation system is not close to being produced in a simulated prebiotic environment.

Second is the need to establish a genetic code having molecules that can catalyze highly specific aminoacylation for each of the twenty protein-forming amino acids. To date ribozyme engineers have successfully designed an RNA molecule that will catalyze the formation of an aminoacyl bond between itself and two amino acids. Yet no one has demonstrated that RNA can catalyze aminoacyl bonds with the other 18 amino acids. One may see some progress here, but until all 20 amino acids can be catalyzed successfully with aminoacyl bonds and with the specificity required to make the molecules useful for translation, there is far more hype than success in claims for a realistic RNA-based translation and coding system.86

Third “the protein-based enzymes involved in translation perform multiple functions.” Ribozymes, however typically can perform only “one subfunction of the several coordinated functions that a corresponded enzyme can perform.” “They cannot perform the entire range of necessary functions, nor can they do so with the specificity needed to execute the many sequentially coordinated reactions that occur during translation.” RNA cannot catalyze the suite of enzyme functions nor the coordinated functions that need to be preformed by an operable translation and coding system.87

(d) The RNA world doesn’t explain the origin of genetic information. In general the RNA world does not attempt to explain the origin of genetic information, since “the RNA world was proposed not as an explanation for the origin of biological information, but as an explanation for the origin of the interdependence of nucleic acids and protein in the cell’s information-processing system.” But the problem for the origin of sequence specific information “looms just as large in a hypothetical RNA world as it does in a DNA world.”88 As with DNA, not just any sequence of RNA bases will be capable of self-replication. Appeal to chance, chance and selection, or self-organization meet with similar limitations as attempts to explain DNA. The specificity of the sequencing problem with RNA information makes it unlikely that RNA bases capable of self replication would arise in a prebiotic environment. To date some researchers have engineered a molecule that can copy part of itself. However this limited success to develop a self replicating RNA molecule was done by human selection out of an engineered pool of 1015 other RNA molecules, most of which do not have this capability. Moreover the investigator had to provide a complementary primer strand to the ribozyme to get this partial (10 percent) self replication.89
(e) Ribozyme engineering does not simulate undirected chemical evolution. “Ribozyme-engineering experiments typically… try to generate either more efficient versions of existing ribozymes or altogether new ribozymes capable of performing some of the … functions of proteins.”90 The engineers of this field “tend to overlook the role that their own intelligence has played in enhancing the functional capabilities of their RNA catalysts.”91 Any success ribozyme engineering might have in enhancing the capabilities of RNA catalysts, only shows “an overt role for intelligence”, not “the plausibility for an undirected process of chemical evolution.92

At this point, we can see that all of the evolutionary proposed theories for the origin of life have what appear to be insurmountable problems. Meyer’s argument when read in all its detail is sufficient to reject all the evolutionary theories as plausible causes of the origin of life. It should be noted that what I have summarized in 10 pages here, Meyer provides 7 chapters and notes covering 180 pages of detailed arguments to support the rejection of the three evolutionary approaches as convincing explanations of the origin of life. It is now time to see if Intelligent Deign can do any better at explaining the origin of life.

VIII. How does one detect Intelligent Design?

In chapter 16 Meyer relies heavily on William Demski in describing several methods and examples of how to detect intelligent design..

In Demski’s book The Design Inference he identifies two indicators of intelligent activity that produce effects different from the effects of purely undirected material causes. Whenever we see events, systems, or sequences that have both “complexity” (small probability) and “specification” operating jointly) we infer intelligent causes to the design of these events, systems, or sequences. We do not attribute chance or physical-chemical necessity to the event, if it has a small probability of occurring and we know independently that the event or system is specified. “Complex events or sequences of events are extremely improbable and exhibit an irregular arrangement that defies description by a simple rule, law, or algorithm.”93. “Events or objects are ‘specified’ if they exhibit a pattern that matches another pattern that we know independently”94

As an example the twin requirements for low probability and specification can be shown with a simple lock. Say a lock dial has 40 settings and the correct combination is R9, L26, and R18. Chance could open this lock in three spins of the dial with a probability of one in 64,000. If someone claims not to know the combination but opens it with just three spins the first time, you would disbelieve him, because 1. The probability is too low for a chance opening on only one try and 2. The fact that it opens shows us a combination was “specified” in advance by an independent source. Only a specific pattern would open the lock. The person who opened the lock matched an independent pattern and met a set of independent functional requirements. We are sure the lock was intelligently designed and the person opening it knew the intelligent code (combination) in advance. Chance or physical-chemical necessity does not explain, only intelligent design explains the lock and its opening on the first trial.95

Another reason for the two requirements of low probability and pattern (specification) can be shown in the objections people have risen with things like low probability card distribution or low probability of a specific person winning the lottery. Low probability alone does not eliminate chance. Coins may be tossed a hundred times and any specific sequence that came up would be very improbable, but still would have happened by chance. If however a pattern could be discerned like the coin showing heads every time, or the winning lottery ticket going to the same person 50 times in a row then we believe something other than chance is responsible.

Dembski developed an “explanatory filter” which provides a general guide to choose between chance, necessity or natural law, and intelligent design. If the event is high probability we can assume natural laws (necessity) is the likely cause. If the event is an unspecified low or intermediate probability, then chance can be inferred as causal. But if the event is a specified event of small probability, then we can infer intelligent design. Note that intelligent design must be both low probability and specified (i.e., a known pattern is detected).96

What is it that distinguishes patterns that come from law-like necessity from patterns that indicate intelligent design? Demski concludes we need an “independent realm of experience” to help detect design, otherwise “the patterns tell us nothing about whether the events in question reflect the activity of another mind.”97 If the events match independently known patterns, the independent patterns are specifications. If they are only perceived as patterns but do not match known patterns, they are “fabrications.”

It is also important to recognize that functional specifications can be treated as independent patterns. There are two cases of pattern recognition that can be subsumed under “specifications”. The first case is one in which the observer recognizes a pattern in an event directly (like the all heads for 100 coin tosses). The second is when the observer recognizes a functionally significant outcome in an event. Regarding the second, Meyer comments: “In Dembski’s way of thinking, a functional requirement represents a kind of target and a target is a kind of pattern.”98 For example if we developed a long string of letters from the English alphabet generated at random we could come up with a large set of possible combinations of letters for a fixed length in which almost all combinations would have no meaning. A much smaller set of meaningful sequences of the same length (sentences) could be generated by an intelligent source. The intelligent design of the meaningful English sequence that meets its probability and specification requirements is described by Meyer as follows: “Clearly all of the English sentences that define the smaller domain or target … actualize or utilize existing conventions of vocabulary and requirements of grammar. Since the smaller domain .. distinguishes its functional sequences (English sentences), and the functionality of alphabetic sequences depends on independently existing conventions of English vocabulary and grammar, the smaller domain defines an ‘independently given’ target or pattern.”99

IX. How does Intelligent Design explain the origin of life?

We can see from Dembski’s and Meyer’s discussion general methods of detecting or inferring intelligent design. The big question in most people’s minds, however, is how does intelligent design apply to biology.100 There are people who truely understand that base sequences in DNA are vastly improbable and highly complex; who understand the base sequences in DNA perform a critical function by directing protein synthesis in the living cell; but cannot see how DNA was specified in the origin of life. “Do the base sequences in DNA match a pattern from some other realm of experience? If so, where does that pattern reside?101

Meyer cogently explains how Demski’s criteria for intelligent design can apply to the origin of DNA molecules and to the cell’s information-processing system as well. Meyer explains that while “we do not see any pattern in the DNA molecule that we recognize from having seen such a pattern elsewhere,… molecular biologists do [however] recognize a functional significance in the sequences of bases in DNA based upon something else we know.”102 Molecular biologists have recognized since 1957 that “the sequence of bases of DNA produce a functionally significant outcome—the synthesis of proteins.” “The base sequences in the coding region of DNA do exemplify… independent functional requirements and produce outcomes that hit independent functional targets in combinational space.”103 Specifically, “the nucleotide base sequences in the coding regions of DNA are highly specific relative to the independent requirements of protein function, protein synthesis, and cellular life.”104. Building “proteins with their specific three-dimensional shapes depends upon the existence of specific arrangements of nucleotide bases in the DNA molecule.” So “any nucleotide base sequence that directs the production of proteins hits a functional target within an abstract space of possibilities” or in other words any protein produced is “specified” by a DNA sequence.105 “Accordingly, the nucleotide sequences in the coding regions of DNA are not only complex, but also specified.”106 This of course means the specific arrangements of bases that would be necessary for DNA to function in its origin would meet the requirements for intelligent design

The argument about not seeing a pattern in DNA that matches a pattern elsewhere can be answered in another way. There is the pattern we see when we understand how DNA and a cell’s information system operate in the present. Recall that we are using abductive reasoning for all explanations of origins of life. We are trying to explain the origin of life by intelligent design in the past by evidence of the present. That evidence is in the operation of biology in the here and now. Intelligent design infers a similar pattern as shown today would have existed at its origin. From the evolutionary views it is important that the operation of DNA in its origins be as simple as possible. From the view of intelligent design, the operation of DNA in the present could be very close to how it operated in its origins. Either way we would expect a DNA pattern in the past that we could infer from the present. We would expect a pattern that could produce specified function.

The concept of intelligent design as an explanation for origin of life can be extended beyond DNA bases to an entire cell. Meyer discovered that “small probability specification” was also information, at least the functional kind of information that is an indicator of design.107 Since function constitutes a special case of specification, it is not a far stretch to consider “small-probability specifications” and “complex specified information” as the same thing.108 Meyer concludes that Dembski’s theory of design applies to any system that has large amounts of … functional information. Since DNA, RNA, and proteins each have large amounts of functionally specified information, and since even the first simple self-replicating organism would have required large amounts of it,” then “the origin of the specified information necessary to build the first living cell could also be explained by intelligent design.”109

Intelligent design meets the requirements for the source of the first form of life and explains better than any evolutionary example how it is that life is here. We know of no way that specified information can appear except from human minds. Matter does not produce specified information. DNA for example is not similar to a computer program or human language in being the product of specified information, but is for that feature, “identical with intelligently designed codes, languages, and artifacts.”110 Intelligent design explains the origin of life because life depends on an intelligence source of information to make it operate. We have first hand knowledge of our minds and what they can do. Our experience shows that only the human mind is capable of producing specified information. Our experience also shows that material processes do not have the capacity to produce specified information. Historical science reasoning finds only a superior form of intelligence could account for and therefore explain the design shown in DNA, RNA, proteins and functional cells.

Although it is logical that a superior mind would explain the specified information we find in life and there are really no better explanations, several objections to intelligent design have been brought on philosophical grounds. These include 1. Our ignorance of any known natural causes of biological origins. 2. Science never says never. 3. We cannot infer a designing intelligence prior to the existence of humans. 4. David Hume’s argument that biological organisms differ significantly from human artifacts and therefore cannot be shown to originate from a mind by analogy. 5. Information as used in biology is nothing more than a metaphor.

Meyer, a philosopher of science himself easily counters these objections.

1. Argument from ignorance.

This objection is essentially stating that intelligent design is just a mysterious notion that covers for ignorance—a sort of God of the gaps argument. But the design inference does not constitute an argument from ignorance, rather it constitutes an “inference to the best explanation” based on our best available knowledge. “We are not ignorant of how information arises. We know from experience that conscious intelligent agents can create informational sequences and systems…. When we encounter the information based in large biological molecules needed for life, we can infer—based on our knowledge of established cause and effect relationship—that an intelligent cause operated in the past to produce the specified information necessary to the origin of life.” Intelligent design is applying a standard historical sciences principle of uniformitarianism, that “the present is the key to the past.”111

2. Science never says never.

This is similar to the objection above. Just because we are ignorant of what future inquiry may find about causal powers of natural or material processes, future discoveries might prove the intelligent design argument false. Currently intelligent design has a negative generalization which states “purely physical and chemical causes do not generate large amounts of specified information.”112 This objection is of course wrong since science often says never. The laws of thermodynamics are good examples. Also in science one does not discard the best explanation at the time purely on the hope or possibility of some future discovery. Further things that do not explain should be discarded. On the other hand, if someday matter can be shown to produce complex specified information, then other explanations may be developed. In the meantime the fact that there is no explanation of how matter can produce information rules against it and certainly does not mean that someday matter will produce information.

3. Assumptions prior to humans.

This is the objection that “since we do not have independent knowledge of the existence of intelligent agents prior to the advent of human beings, the case for intelligent design fails the causal-existence requirement of best explanation… One way to meet both adequacy and past-existence is to show that there is only one known cause of a given effect.”113 This was discussed above and is true in the case of intelligent design. It is the only known cause of large amounts of specified information as exists in the cell.

4. David Hume’s argument.

David Hume’s argument is that human artifacts and biology are significantly different so that we cannot assume by analogy that the criteria for discovering an artifact (which is determined to have human design) can use the same criteria for assuming that biology (which appears designed) is a result of intelligent design. For example, although there may be similarities one cannot argue from analogy because unlike watches “experience teaches that organisms always come from other organisms.”114 This could lead to an infinite regress of earlier organisms, not a transcendent mind. Meyer counters with several flaws in Hume’s argument.

First, uniform experience shows “organisms possess information-rich macromolecules and a complex information-rich system for processing and replicating the information stored in those molecules.” This raises two possibilities, none of which are Hume’s; (a) Either information-rich systems arise from preexisting systems of information via a mechanism of replication, or (b) information-rich systems arise from minds. But our experience also shows that all cases in which we know the cause of such systems “ultimately arise from intelligent design.”115

Second, “advances in our understanding of planetary and cosmic evolution have ruled out the possibility that biological life has always existed, either on earth or in the cosmos.” There seem only two options, either “life originated from a purely undirected material process or a mind played a role.”116
Third, analogy plays no role in the current defense of intelligent design. As already discussed intelligent design in biology is not argued by analogy, it argues from the existence of specified information in cells which is needed for the production of proteins in cells as produced by minds. Matter does not produce specified information. As stated above, DNA is not similar to a computer program or human language in being the product of specified information, but is for that feature, identical with “intelligently designed codes, languages, and artifacts.”117

5. Information as Metaphor.

It has been raised that using the term “information” in biology is nothing more than metaphor. Some historians and philosophers of biology say the term has only semantic meaning and does not designate anything real. Therefore, the origin of biological information does not require explanation. Others say the concept of information has little theoretical significance in biology because it lacks predictive or explanatory power.118 Meyer counters that, “insofar as the term ‘information’ connotes semantic meaning, it does function as a metaphor within biology… However that does not mean ‘information’ functions only metaphorically or that origin-of-life biologists have nothing to explain.”119 In particular, “where information refers to functional specificity, it defines a feature of living systems that calls for explanation every bit as much, as, say, a mysterious set of inscriptions on the inside of a cave.”120

X. How is Intelligent Design a scientific theory?

Intelligent design is a science the same as the evolutionary theories of origins. All scientific methods for origins fall under “historical science”. To support the claim that Intelligent Design is a scientific theory, Meyer presents six specific reasons. From this he concludes that Intelligent Design is a science by any measure of what science means to scientists and philosophers of science.121

Reason 1. The case for intelligent Design is based on empirical evidence. Some of the empirical arguments for intelligent design include: 1.The discovery of digital information in the cell. (Meyer, op. cit., note 2). 2. The “irreducible complexity” of molecular machines and circuits in the cell (Michael Behe, Darwin’s Black Box). 3.The pattern of appearance of the major groups of organisms in the fossil record (see particularly Meyer et al “The Cambrian Explosion: Biology’s Big Bang” in Darwinism, Design and Public Education, ed. John Campbell and Stephen Meyer, p. 323-402. East Lansing: Michigan State University Press, 2003). 4. The fine tuning of the laws and constants of physics (see, e.g., Barrow and Tipler on the Anthropic Principle vs. Divine Design). 5. The fine tuning of our terrestrial environment (Gonzalez and Richards, The Privileged Planet). 6. The information-processing system of the cell (Meyer, op. cit., note 2) and 7. “Homology” has often been used to support neo-Darwinism, but it can also can be interpreted to support intelligent design (Nelson and Wells, Homology in Biology).122

Reason 2. Advocates of Intelligent Design use established scientific methods. At least two scientific methods have been used to make the case for Intelligent Design. The primary method is the method of multiple competing hypotheses.123 This method is discussed at length in Chapter 15 of Meyer. Another method introduced by William Demski in The Design Inference and Chapter 16 of Meyer is “criteria by which intelligently designed systems can be identified by the kinds of patterns and probabilistic signatures they exhibit.”124 Demski also developed an “explanatory filter” to help investigators decide between natural objects and artifacts and to decide among different types of explanations: chance, necessity, and design. Demski’s method is rigorous, systematic evidence based on a method for detecting the effects of intelligence.125 The method is particularly helpful to allow the investigator to determine between intelligent design and appearance of design (by chance or necessity, for example).

Reason 3. Intelligent Design is a testable theory. The theory of intelligent design is testable in a number of interrelated ways.126

First. “Intelligent design is testable by comparing its explanatory power for explaining past events against competing theories.” For example, intelligent design can explain the origin of biological information better than its competitors.127

Second, it “is tested against our knowledge of the evidence in need of explanation and our knowledge of the cause-and-effect structure of the world.” For example “experience shows an intelligent agent is not only a known, but also the only known cause of specified, digitally coded information”. Intelligent design has passed the critical “tests of causal adequacy and causal existence,” thus standing “as the best explanation of the DNA enigma.”128

Third, intelligent design can and has generated discriminating predictions about what we should find in the natural world. In this way intelligent design not only distinguishes its theory from competing evolutionary theories, but also serves to confirm the design hypotheses rather than such hypotheses of chance or necessity.129 Several of these discriminating predictions and hypothesis confirmation of design are discussed in Paragraph XI For example much of so called “junk DNA” which is generally ignored with evolutionary hypotheses has been found to perform a diversity of important biological functions when examined under the hypothesis of intelligent design.130

Reason 4. The case for Intelligent Design exemplifies historical scientific reasoning. Meyer considers that historical sciences can generally be distinguished from nonhistorical sciences by four criteria. Intelligent Design fits well with each of the key features of a historical science.131

A. Distinctive Historical Objective. Historical sciences focus on questions like “What caused this event or that natural feature to arise?” rather than questions like “How does nature operated or function?” The theory of intelligent design asks such questions as what caused certain features in the natural world (like the digitally encoded, specified information in the cell) to come into existence.132

B. Distinctive Form of Inference Historical sciences typically do not infer generalizations or laws from particular facts (induction) but rather use abductive logic to infer a past event from a present fact or clue. Intelligent design infers a past unobservable cause (like a creative agency) from present facts in the natural world (like the specified information in DNA or the fine-tuning of the laws and constants in physics).133

C. Distinctive Type of Explanations “In historical explanations, past causal events, not laws or general physical properties do the explanatory work.”134 Present geological strata may be explained by a historical geologist by a series of past events (e.g., flood deposits). Advocates of design conceptualize the act or acts of a mental entity rather than purely physical events to explain the origin of present evidence.135 .

D. Use of the Method of Multiple Competing Hypotheses. Historical scientists do not generally test hypotheses under controlled laboratory conditions. With “the method of multiple competing hypotheses, historical scientists test hypotheses by comparing their explanatory power against that of their competitors.”136 Meyer’s book uses this method extensively in comparing intelligent design against three types of evolutionary hypotheses.137

Reason 5. Intelligent Design addresses a specific question in biology. A central question in biology is explaining why biological organisms appear to be designed. There are two answers to this question of appearance of design. The classical Darwinian answer is “The appearance of design in biology does not result from actual design” The intelligent design answer is “The appearance of design in biology does result from actual design” Is not the second proposition as scientific as the first?138

Reason 6. Intelligent Design is supported by peer-reviewed scientific literature. It is well known that the proponents of new theories often find traditional publication avenues closed to them. This problem is no different for Intelligent Design, since the conventional evolutionary theories have been dominant in traditional publishing venues. Nevertheless, scientists developing “the case for intelligent design” have in many instances “published their work in peer-reviewed scientific journals, books, conferences, volumes, and anthologies.” This trend to publish in scientific venues is growing.139

XI. What are some scientific predictions from Intelligent Design?

Meyer discusses 13 specific examples of scientific predictions from Intelligent Design.140

I will cover five of them here as a sampling of what Intelligent Design can do in the way of scientific predictions.
“Junk DNA” is actually useful.
Functional sequences of amino acids should be extremely rare.
The flagellar motor genes should be older than those of a subsystem (T3SS) that code for proteins.
D. The fossil record should show evidence of discrete infusions of information into
the biosphere.
E. Studies of the putatively bad designs in organisms should show either 1) the designs have a hidden functional logic or 2) evidence of decay of originally good designs.

A. “Junk DNA”. DNA that does not code for proteins is frequently found in the genomes of both one-celled organisms and multicellular plants and animals. This DNA is generally thought of as nonfunctional DNA or “junk.” The explanation of evolutionary theories of origins, both chance and neo-Darwinian, is that this nonfunctional DNA accumulated in both the first simple (prokaryotic) organisms and the genomes of eukaryotic organisms (organisms whose cells contain nuclei) as useless or “junk” DNA. This “junk” DNA is thought by evolutionary theories to show “a kind of remnant of whatever undirected process first produced functional information in the cell.”141 These nonprotein coding regions have been taken as confirming the expectation of naturalistic evolutionary theories and disconfirming intelligent design. “As Michael Shermer argues, ‘Rather than being intelligently designed, the human genome looks more and more like a mosaic of mutations, fragmented copies, borrowed sequences, and discarded strings of DNA that were jerry-built over millions of years of evolution.’”142

Intelligent Design predicts significantly different results from “junk DNA” “We predict that the functional DNA (the signal) should dwarf the nonfunctional DNA (the noise), and not the reverse.”143 Evolutionary theories expect much useless DNA, while Intelligent Design expects most DNA, including “junk” DNA to exhibit function. Meyer states: “The discovery in recent years that nonprotein-coding DNA performs a diversity of important functions has confirmed this [ID] prediction.”144 Intelligent Design not only makes a discriminating prediction about the nature of “junk DNA”, but recent discoveries are showing its predictions to be true. As examples: Nonprotein-coding regions of the genome have been found to:

    1. direct the production of RNA molecules that regulate the use of protein-coding regions of DNA
    2. regulate DNA replication
    3. regulate transcription
    4. mark sites for programmed rearrangements of genetic material
    5. influence the proper folding and maintenance of chromosomes
    6. control the interactions of chromosomes with the nuclear membrane (and matrix)
    7. control RNA processing, editing, and splicing modulate translation, regulate embryological development
    8. repair DNA
    9. aid in immunodefense or fighting disease, and
    10. in some cases, to code functional genes.14

B. Rare functional sequences of amino acids. Intelligent design predicts that functional sequences of amino acids should be rare rather than common as expected by evolutionary theories. More specifically, the question to be answered is “How rare or common are functional protein folds within their corresponding amino-acid-sequence space?”146 Douglas Axe designed a specific test of the efficacy of the neo-Darwinian mechanism. He reasoned “that if functional sequences were common enough for mutations to stumble upon them relatively easily, mutation and selection might be able to build otherwise extremely improbable structures in small increments”. However if functional proteins are extremely rare within the sequence space, then mutations will not have a realistic chance of finding them in time for selection to have anything much to work on. This would greatly work against evolutionary explanations of a way to produce biological information. Axe has already done some experimental testing of this question. The first results published in the Journal of Molecular Biology show the ratio of functional to nonfunctional amino acids is extremely small, 1 in 1074 for a protein fold 150 amino acids in length.147 In other words, the functional sequences of amino acids are rare rather than common. Again an intelligent design prediction has, initially at least, been confirmed.

C. Flagellar motor genes relative age older than subsystem that codes for proteins.

This is prediction that comes from the work of Michael Behe who “argues that the many miniature machines and circuits that have been discovered in cells provide strong evidence for intelligent design.” His basic argument is that certain miniature machines, like the bacterial flagellar motor, “could not have been developed from simpler precursors in a gradual step-by-step fashion.” As an example of “irreducible complexity” the flagellar motor resulted “from an idea in the mind of a designing intelligence,” rather than “from a process of gradual step-by-step evolution from a series of simpler material precursors.”148

Critics however have proposed that the flagellar motor could have arisen from some other parts of the motor, in particular “a tiny molecular syringe called a type-3 secretory system (T3SS)” that normally codes for proteins and is sometimes found in bacteria without the other parts of the flagellar motor.149

To test this hypothesis the two theories (evolution from simpler parts versus intelligent design) of the flagellar motor origin, it was recognized that the relative ages of the genes that produce the flagellar motor versus the genes that produce the T3SS could settle this issue. Evolution expects the simpler T3SS genes to be an older precursor system whereas intelligent design predicts the genes for the flagellar motor to be older since T3SS operating alone is likely to have resulted from degenerative evolution. Recent phylogenetic studies suggest that the flagellar motor genes are in fact older than the T3SS genes thus confirming the intelligent design hypothesis.150

D. The fossil record should show evidence of intelligent design

The fossil record whether explained by evolutionary methods or intelligent design usually look at the same evidence, but supply different interpretations of the fossil patterns.. Neo-Darwinism prefers patterns of the fossil record that in general show “common descent” from simpler to more complex forms. Design theorists take one of two possible routes for the pattern of fossils. One approach is the “front-loaded” design where it is thought “that the information necessary to produce new forms of life was front-loaded in the initial conditions of the universe.” They believe “the fine-tuning of the laws of physics … would demonstrate biologically relevant self-organizing tendencies” and would predict along with neo-Darwinism the traditional evidences for common descent.151

Other design theorists think organisms were designed as functionally integrated systems with so many parts and subsystems that it would be difficult to alter any parts significantly without destroying the whole system. For example alterations that consist of blind mutations searching for increased functionality would likely damage working systems rather than create more complex functions. “These ID theorists predict there should be significant and discoverable limits to the amount of change that various organisms can endure and the major body plans should exhibit significant stasis over time in the fossil record. This latter design theory is most easily discriminated from neo-Darwinism in its predictions of the fossil evidence. For example rather than “bottom up” appearance of fossils, it would expect a “top down” pattern of appearance in which large scale differences in form (as phyla and classes) would appear suddenly and prior to lower level differences in form (e.g. species and genus) and show a pattern of morphological stasis over time in the fossil record.152

Fossil patterns that support the top-down approach would clearly support intelligent design, since it is completely counter to neo-Darwinism. Patterns that support common ancestry can be argued as also supporting intelligent design, depending on the interpretation provided, but the determination of “best explanation” would need to rely on other supporting evidence.

E. Putatively bad designs in organisms

The theory of intelligent design generally affirms that complex biological structures were designed for functional reasons. Therefore it predicts that “poorly designed” structures in organisms should show either 1) the designs have a hidden functional logic or 2) evidence of decay of originally good designs.153

The backward wiring of the vertebrate retina is an example of the first, a design which is arguably poor, but upon deeper investigation shows a hidden functional logic. George Ayoub and Michael Denton have identified a number of functional reasons that support the backward wiring as a superior design. Ayoub points out that the vertebrate retina is “an excellent example of … constrained optimization, in which several competing design objectives are elegantly balanced to achieve an optimal overall design.”154

An example of the second, decay of originally good design is provided by the existence of disease producing bacteria. Surely an intelligent and benevolent designer would not have created such organisms. The intelligent design prediction regarding this type of bad design is that the “virulent bacterial systems are degenerative systems that have resulted from a loss of original genetic information.”155 Intelligent design predicts “that the virulence capacity in Yersinia pestis, the bacterium that caused the black plague in medieval Europe, resulted from genetic mutations that stopped it from manufacturing molecules and structures recognized by the human immune system.”156 Scott Minnich, microbiologist from the University of Idaho, has already shown that similar but less virulent bacterium that causes gastroenteritis has “resulted from the mutational degradation of genes that produce flagellin.” Flagellin is “a protein that the human immune system recognizes in flagellar motors of bacteria.” When Minnich restored the gene for producing flagellin the virulence of the bacterium was reduced.157 These types of results are valuable contributions of intelligent design to medical science.

XII. Why is Intelligent Design the best scientific explanation of the origin of life?

This part provides a summary of the major reasons intelligent design is the best scientific explanation of the origin of life. It will not repeat the details supporting these reasons that are discussed at length in the other parts. The major reasons that intelligent design is the best explanation of the origin of life are:

1. No other causally adequate explanations exist. Meyer examined major theories from three classes of evolutionary explanations of the origin of life: chance, necessity, and combination of chance and necessity. He found that none of these evolutionary approaches revealed “any cause or process capable of producing biologically relevant amounts of specified information.”158 In his survey of other explanations “Every attempt to explain the origin of biological information either failed because it transferred the problem elsewhere or ‘succeeded’ only by presupposing unexplained sources of information,” a procedure Meyer labels the “displacement problem”159

Chance explanations by themselves failed because the probabilistic odds of success were so low that to succeed in producing only one molecule of DNA, RNA, or a functional protein required more probabilistic resources than have existed in the entire universe since the big bang.

Self-organizational laws (processes of necessity) cannot generate new information. “Laws of nature describe highly regular patterns or order, not the aperiodic complexity that characterizes information rich digital code”160

Combinational models end up facing both the problems of chance and necessity alone. “Since the law-like processes of necessity do not generate new information, these … models invariably rely upon chance events to do most, if not all, of the work in producing new information.” By eventually relying on chance these models face the same limitations as chance models alone.161

2. Experimental evidence confirms causal adequacy of intelligent design.

Meyer discovered that the experimental evidence from simulation experiments conducted over 50 years shows that without using mind or intelligence little or no information arises. He discusses “three separate types of experimental results confirm this lesson”162

A. Prebiotic Simulation Experiments. Simulations of the early prebiotic environments capable of producing life, like those of Stanley Miller, invariably failed to demonstrate plausible chemical evolution under realistic prebiotic conditions. “Simulation experiments have repeatedly shown that … destructive chemical processes would have predominated in any realistic prebiotic chemical environment.163 In all of these simulation experiments, chemists intervene using traps or other techniques to isolate and remove undesirable chemicals that would alter or destroy the desirable building blocks. For example the formose reaction that produces ribose sugars also produce products that will destroy the ribose. These are removed by intervention of the chemist. The point made by Meyer is that intelligent agents are responsible for imparting information into chemical systems to produce biologically relevant molecules. Therefore, prebiotic simulation experiments provide positive evidence for the causal adequacy of intelligent design.164

B. Evolutionary Algorithms. None of the evolutionary algorithms reviewed by Meyer “demonstrated the ability of undirected chance and necessity to produce specified information.” When “computer simulations depend on causal powers that natural selection lacks” such as foresight and creativity, as they must do “to generate functional information and outcomes--they are provided by the knowledge and intelligence of the programmer, not the computer.” Therefore, “evolutionary algorithms demonstrate the causal power of intelligent design.”165

C. Ribozyme Engineering.

“Ribozyme engineers attempt to enhance the capacity of RNA catalysts in order to demonstrate the plausibility of the RNA world.” They “want to show that linking enzymes called RNA ligases can acquire true polymerase function, making possible template-directed self-replication.” Again as with the other experiments, ribozyme engineers themselves have to supply critical specific sequence information to produce successful ribozyme engineering experiments. They must intervene by anticipating future functions not yet present in the emerging ligase itself. They start by selecting molecules with slightly enhanced ligase capacity. Then they preserve and optimize these molecules by “repeated selection and amplification.” In this way the investigators (not nature) are really doing the selection of RNA sequences based on their knowledge of conditions needed to assure template-directed self-replication. Meyer shows that this example is only one of several ways ribozyme engineers introduce their own intelligence into the experiments. This is the third type of experimental evidence to demonstrate the causal power of intelligent design.166

3. Intelligent design is the only known cause of specified information. To explain the origins of DNA and RNA molecules, and functional proteins requires first explaining the origin of large amount of specified information critical to the origin of life itself. “Undirected materialistic causes” have not as yet “demonstrated the capacity to generate significant amounts of specified information.” On the other hand, “conscious intelligence has repeatedly shown itself capable of producing such information.”167 Historical scientific reasoning must establish that any acceptable explanation must first show a given cause can produce the effect in question, and then demonstrate that the cause was actually present in order to do so. The historical scientist can show a causal-existence criterion for intelligent design by applying the method used by Meyer. This requires a thorough examination of all the competing causal explanations and showing that only one of the competing causes has demonstrated the ability to produce the main or salient effect in question. Meyer has made a thorough examination of all the competing explanations and found none that could produce large amounts of specified information, whether starting with DNA-first, RNA-first, or protein-first solutions. Only an intelligent agency can be shown to produce specified information such as that which exists in cells. Specified information in the cell establishes existence and past action of intelligent activity in the origin of life. “Experience shows that large amounts of specified complexity or information (especially codes and languages) invariably result from an intelligent source.”168

4. Intelligent design makes useful predictions. Part XI above summarizes several of the specific examples Meyer provides on the capability of intelligent design to not only make scientific predictions which discriminate from evolutionary predictions on research issues, but frequently these predictions have been confirmed thus showing the superiority of ID over competing theories. “Junk DNA” explanations of competing theories are used primarily to demonstrate past evolutionary mistakes (or trial and error) is inferior to ID explanations that further the knowledge of biological operations. This is because showing useful functions of junk DNA also explains how the biological cell works in greater detail than the competing theories that essentially disregard the important aspects of nonprotein coding DNA. Another example of the superiority of ID to other theories of explanation was shown in the two differing explanations of the design of disease causing bacteria. Evolutionary theories discuss such disease as explaining how the bacteria came to be with no purpose but for whatever reasons cause disease. ID theories predict that organisms that have no purpose other than to cause disease could be a degenerative version of something which was once good. The current experiments with a bacterium that cause gastroenteritis do show they have mutated genes, which once restored reduce their virulence. Thus ID predictions can stimulate useful research in medicine that has been ignored by the evolutionary theories.


1. Francis Crick, for example, does not attribute the intelligent complexity of the DNA molecule to God, but wonders if it could have come from other intelligences somewhere in the universe. Some atheists have actually changed their beliefs and others find intelligent design a plausible argument. In December 2004, renowned British philosopher Anthony Flew repudiated his lifelong dedication to atheism, and announced his change of view on origins to something like “American design theorists” in large part due to the evidence of intelligent design in the DNA molecule. In 2009 noted atheist and philosopher Thomas Nagel at New York University selected Meyer’s book Signature in the Cell as one of the books of the year for the Times Literary Supplement because of Meyer’s impressive argument for intelligent design. Nagel states: “Meyer is a Christian, but atheists, and theists who believe God never intervenes in the natural world, will be instructed by his careful presentation of this fiendishly difficult problem.”
2. Meyer, Stephen (2009) Signature in the Cell; DNA and the Evidence for Intelligent Design, New York: HarperCollins.
3. Ibid, p. 29. Meyer discusses the differences between operations sciences and origins science as credited to Thaxton and colleagues from The Mystery of Life’s Origin.
4. Ibid. p. 122.
5. Ibid, p. 135.
6. Ibid, p. 92.
7.The four nucleotides that make up the DNA letters are (A) adenine, (C) cytosine, (G) guanine and (T) thymine. The four letters (nucleotides) are strung along two DNA strands in base pairs (like rungs on a ladder). The strands form the backbone of DNA made up of sugars and phosphates. A sequence of base pairs on the ladder rungs make up a sequence which is specified and coded into words along the strands.
8. The base pairs are always A and G together and C and T together. The base pairs are ordered in groups of three that make up three letter words. The words make up 61 different combinations that code for the 20 amino acids. For example, the DNA word (base triplet) AGA specifies the amino acid arginine. Three words code for the word STOP.
9. Meyer, op. cit., Note 2, p 97.
10. Scientists now know that more than one hundred proteins are required.
11. All of these quotes are cited in Meyer, op.cit. note 2, pp. 132-4..
12. Historical scientists have developed two key criteria for deciding among a group of competing causes which cause provides the “best explanation” for a relevant body of evidence. The first and most important criterion is “causal adequacy.” (Meyer, op. cit., note 2, p 159) Historical scientists must identify causes known to have the power to produce the event in need of explanation. In general, causes that are known to produce the effect in question are judged to be better explanations than those that are not. The second criterion is determining if there are more than one known cause for the effect in question. (Meyer, op. cit., note 2, p 161) Assessments of explanatory power lead to sound inferences only when it can be shown that there is only one known cause for the event historians are trying to explain. For example, a historical geologist who knows that a volcanic eruption is the only known cause of widespread deposits of volcanic ash will infer (with high confidence) that a past eruption caused the ash layer discovered today. Meyer, op. cit., note 2, p. 168). If there are more than one causally adequate explanation, scientists must look for additional evidence until they can find an explanation which best explains all the evidence that can be gathered. Meyer has done this with his book, carefully examining all the evidence for competing causal explanations and then one by one eliminating them with evidence and analysis which shows them to be inadequate, leaving only one as the best explanation.
13. Abductive reasoning infers unseen facts, events, or causes from the past from clues or facts in the present. One can compare abductive reasoning with inductive reasoning – a universal law or principle is established from repeated observations of the same phenomena, or deductive reasoning, in which a particular fact is deduced by applying a general law to another particular fact or case. American philosopher and logician Charles Sanders Peirce first described abductive reasoning and pointed out a particular problem with abductive reasoning. When trying to infer the past from the present there are often many possible causes of a given effect. Contempory philosophers of science apply a method “inference to the best explanation” which is most applicable to trying to explain origins from the past. See note 12 and Meyer, op. cit., note 2. p.153-154.
14. Meyer, op. cit. note 2, p.174 where he cites Monad’s definition of chance.
15. Ibid, p 48-54.
16. Ibid. p.196
17. Ibid, p.230.
18. Ibid, p 230.
19. Ibid. p 232.
20. .Ibid, p.232-3
21. Ibid, p.261.
22. Ibid p.261.
23. Ibid p. 261
24. Ibid. p.272
25. Ibid, p.275
26. Ibid, p.278.
27. Ibid. p.297
28. Ibid. p.298
29. Ibid. p.299-300.
30. Ibid. p.283
31. Ibid. p.195.
32. Ibid, p.195
33. Ibid. p.195-6.
34. Wald, G. cited in Meyer, Ibid. p. 195
35. Meyer, op. cit., note 2,. p. 175
36. Ibid. p.180
37. Ibid. p.180
38. In nature, nearly every amino acid found in proteins has two versions. One is a left-handed version (or L-form) and the other a right-handed form (or D-form). They are mirror images of themselves and called optical isomers. Meyer (p. 207) shows an example of the optical isomers of the same amino acid. In abiotic amino acid production both right and left handed isomers are produced with approximately equal frequency. But functioning proteins in a cell will only accept left-handed amino acids.
39. Meyer, op. cit. note 2. Meyer discusses the three requirements that decrease the chance of forming a workable protein in pages 206-208.
40. Ibid. p. 208.
41. Ibid. p. 207. In numerous cases, several different base triplet words will code for the same amino acid. For example GTT, GTC, GTA, and GTG, each code for the amino acid valine.
42. Ibid. p. 208.
43. Ibid. p. 208
44. Ibid. p. 210.
45. Ibid. p. 212
46. Ibid. p. 212
47. Ibid. p. 212
48. Ibid, p. 212
49. Ibid. p. 188-189
50. Ibid. p. 189, 215
51. Ibid. p. 216-217
52. Ibid. p. 217-219
53. Ibid. p. 230
54. Ibid. p. 230.
55. Ibid. p. 234
56. Ibid p. 234
57. Ibid. p. 235-236
58. Ibid. p. 236
59 Polanyi, M, 1968. “Life’s Irreducible Structure” Science and 1967, “Life Transcending Physics and Chemistry” Chemical and Engineering News. Cited in Meyer, op. cit. note 2, p. 237
60. Ibid. and cited in Meyer, op. cit. note 2, pp 239-240.
61. Meyer, op. cit. note 2, p. 251
62. Ibid. p. 253.
63. Ibid. p. 255.
64. Yockey, Hubert in Meyer, op. cit., note 2, p. 255.
65.. Meyer, op. cit., note 2, p. 262
66. Ibid. p. 262-264
67. Ibid. p. 264
68. Ibid. p. 262
69. Ibid. p. 263
70. Ibid. p. 263
71. Ibid. p. 266
72. Ibid. p. 266.
73. Ibid. p. 266.
74. Ibid. p. 267.
75. Ibid. p. 277
76. Ibid. p. 277
77. Quasler, in Meyer, op. cit., note 2.. p. 278
78. Berlinski, David in Meyer, op. cit note 2, p. 282..
79. Meyer, op. cit., note 2, p. 284.
80. Ibid. p. 289.
81. Ibid. p. 301-304
82. Ibid p. 304
83. Ibid p. 305.
84. Ibid. p. 306
85. Ibid. p. 305-306
86. Ibid p.. 306
87. Ibid p. 308-312
88. Ibid. p. 312
89. Ibid. p. 315-316
90. Ibid p..318
91. Ibid p. 319.
92. Ibid. p. 321
93. Ibid. p. 352
94. Ibid. p. 352
95. Ibid. p 352. Meyer provides a similar example with a lock and students.
96. Ibid. p..255
97. Ibid. p. 356
98. Ibid. p. 360
99. Ibid. p. 363
100. Ibid. p.364
101. Ibid. p.364
102 Ibid. p.365
103. Ibid. p.365
104. Ibid. p.365
105. Ibid. p.365
106. Ibid. p.367
107. Ibid. p.371
108. Ibid. p.371
109. Ibid. p.372
110. Ibid p.386
111 Ibid. p.376-377
112. Ibid. p.379
113. Ibid. p.381
114. Ibid. p.384
115. Ibid. p.384
116. Ibid. p.384
117. Ibid. p.386
118. Ibid. p.386-387
119. Ibid. p.387
120. Ibid. p.388
121. Ibid. p.399-402
122. Ibid. p.403
123. Ibid. p.403
124. Ibid. p.404
125. Ibid. p.404
126. Ibid. p.404
127. Ibid. p.404
128. Ibid. p.405
129. Ibid. p.405
130. Ibid. p.406-407
131. Ibid. p.408
132. Ibid. p.408
133. Ibid. p.409
134. Ibid. p.409
135. Ibid. p.409
136. Ibid. p.409
137. Ibid. p.409
138. Ibid. p.411
139. For comprehensive annotated bibliography of Intelligent Design publications see
140. Meyer, op. cit., note 2 p.406-407 and Appendix .A. Some Predictions of Intelligent
Design p.481-497.
141. Ibid. p.406
142. Shermer, Michael quoted in Meyer op. cit., note 2, p. 406.
143. Meyer, op. cit., note 2, p.406-407
144. Ibid, p.407
145. Meyer provides experimental citations for each of these recent discoveries of the use of “junk DNA” Ibid. p.407
146. Ibid. p.494-495
147. Ibid.p.495
148. Behe, William quoted in Meyer, op. cit., note 2, p. 492
149. Meyer, op. cit., note 2, p. 492
150. Ibid. p.493
151. Ibid. p.488
152. Ibid. p.488-489
153. Ibid. p.490
154. Ibid. p.491
155. Ibid. p.491
156. Ibid. p.491
157. Ibid. p.491
158. Ibid. p.330
159. Ibid. p.332
160. Ibid. p.331
161. Ibid. p.331
162. Ibid. p.334
163. Ibid. p.334
164. Ibid. p.335
165. Ibid. p.336-337
166. Ibid. p.338-339
167. Ibid p.341
168. Ibid. p.343


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