A man walks into a store and tells the clerk, “I’m looking to buy a hat.” The clerk says, “We are all out of hats, but I do have a cat that I will sell to you at a good price.”  The man tells the clerk, “Close enough. I’ll take it.”

This story is silly. A cat is nothing like a hat despite the fact that the words look and sound similar. Words are just arbitrary symbolic representations of ideas. The letters or symbols in a word mean nothing unless they are assigned a meaning by an outside source like a dictionary or a codebook.

Because of the arbitrary nature of language, any symbol of group of symbols can be assigned any definition, as long as it is agreed upon or understood by those who wish to use these symbols to communicate ideas. In this way, some very similar ideas can be represented by very different looking words or some very different ideas can be represented by some very similar looking and sounding words.

For example, the words “admire” and “esteem” have very similar meanings, but look nothing like each other. The words “vacation” and “vocation” look and sound very similar, but have almost opposite meanings.

All languages are arbitrary in that symbols are given their meanings, and this meaning is independent of and greater than the symbols themselves.

Symbolic languages are not just limited to human communication. Every living thing uses symbolic language to communicate information in the form of genetic words written in the languages of DNA and protein. You will find in any biology textbook that the language of DNA is made up of words. Each of these words is given and arbitrary meaning by a codebook called the “Genetic Code.”

Proteins are also “written” using letters in a chemical alphabet called amino acids. There are 20 different amino acids just as there are 26 different letters in the English alphabet. Different arrangements of these letters in proteins spell out protein words, which are given an arbitrary meaning or function by the cell that makes them. Just as in any other symbolic language, there is no inherent meaning for a given protein outside of how the cell defines it.

For example, the protein called “insulin” is a signal to some cells in the human body to uptake glucose from the blood stream. The bovine insulin protein is made up of two protein words that are linked together. One of these words is 21 amino acids-letters in length. The other word is 30 long.ⁱ

There is nothing special about these words in and of themselves that tells a cell that it needs to uptake sugar. So, how does the cell “know” what to do when it comes in contact with insulin? The cell recognizes insulin through a specific receptor protein that senses insulin like a lock recognizes a key. Then, just like when a key turns a lock, this insulin receptor sends a signal to the cell that tells it to uptake sugar.

In other words, this lock is linked to an underlying system of function. The key that it recognizes is the insulin key, but this recognition is arbitrary. The same function could in fact be set up to recognize any other protein “words.”

The insulin molecule is simply a symbolic representation of an idea or a function that the cell recognizes. The cell recognizes insulin because it is programmed to recognize the language of the body that it is a part of. Specialized cells make the insulin protein as a symbolic message to other cells in the body that tell them when and how they need to use the blood sugar that is available to the body. They could just as easily have been programmed to use some other protein molecule or “word” for the same purpose.

The fact that living creatures use symbols to send messages and to perform functions is undeniable. The fact that these messages are arbitrary and dependent upon a pre-established code of definition also seems intuitive.

The question now is, how did these arbitrary languages and words of living things come about? For the English language, and all other known languages, the idea comes first, and then came the symbolic expressions of the ideas, since the symbols themselves have no inherent meaning.

The letters “cat” mean nothing aside from the attached idea that is arbitrarily given them by the English dictionary. Likewise, the letters in the insulin molecule mean nothing outside of the attached meaning given to them by a living cell or system. Do words change their meaning through an evolution of random letter changes, or through an evolution of ideas, which then seeks out some symbolic representation?

If I change the letters “cat” to read “hat,” does this change necessitate an evolution of recognition or function ? Obviously not. If the change read “cct” this change would have no meaning because “cct” is not defined in the English dictionary. Remember, the symbols or letters themselves have no inherent meaning whatsoever.

Definition and recognition must always come before a symbolic representation. So, if I change the letters in the insulin words around, would these changes necessitate a change in cell recognition and function? No, of course not. In fact, if the letters in the insulin words change too much, the cell would not recognize the new molecule at all. This new protein may not be defined in the cell’s dictionary of protein words.

However, it is of course possible to change a letter of a word randomly and have it mean something in the English dictionary, but this change would need to have a pre-existent definition waiting for it in the dictionary. Changing the “c” in the word “cat” to an “h” does in fact change the understood definition, but only because both “cat” and “hat” were predefined by the English dictionary. Similarly, it would be possible to change insulin into another functioning protein, if the cell had a pre-established system that recognized this new protein. This change would not create a new function, but would simply interact with a previously existing functional system.

Millionaire or Not
Now, let me pose a scenario. You are the next contestant in a game show called Millionaire or Not. In front of you is a safety deposit box with a million dollars in it. On the front of the box is an apparatus that looks like a slot machine. It has 15 rotating wheels, each with the 26 letters of the alphabet on it.

The host tells you that there are one million different winning combinations of 15 letters that will open the safety deposit box. You can rotate each wheel at will and then press a button to see if the combination that you chose is one of the one million winning combinations.

You think that this game is a synch. With one million winning combinations possible, you are practically guaranteed to win. However, if you never choose the same combination twice and if you test a new combination every second, how long will it take you on average to find any one of the one million correct combinations? It would take you a bit over 53 million years.

It is definitely not as easy as it looks anymore is it? It sure would help if you could figure our which combination that you chose was closest to any of the winning combinations. However, there is no function except the winning function to any combination that you try. There is no “close” function. No lights go off when you are getting warmer or colder.

Without some indication, without some intelligible function or signal attached to the losing combinations, you will never know if you are even getting close to a winning combination. Likewise, in living cells, there are far less usable or recognized proteins than there are possible proteins. Getting from one recognized protein to another recognized protein by random mutation is next to impossible because of the loss of all function along the way. There is no way for nature to detect function just as a player of “Millionaire or Not” would be blind without an ability to detect function in non-functional sequences.

Methinks it is like a Weasel
The theory of evolution is in serious crisis because of this very problem, although many have tried to explain it away. The famous British evolutionary biologist Richard Dawkins made one valiant attempt. In his 1986 book The Blind Watchmaker, Dawkins describes an experiment of his that showed how evolution is supposed to work.

He programmed a computer to generate random sequences of letters to see if the computer would, over time, generate the line from Hamlet, “Methinks it is like a Weasel.” This line has 28 characters including spaces, so the computer was programmed to make 28 selections using the 26 letters of the alphabet plus a space to make 27 possible characters to pick from. A typical output looked like this: “MWR SWINUZMLDCLEUBXTQHNZVJQF.”

With this information, a calculation of the probability of picking the “correct” sequence can be made, as well as how long it would take, on average, to find this correct sequence. Dawkins figured that it would take his computer a trillion trillion trillion years (1 x 10^36 years), on average.

Well, this is clearly way too long for the current theory. So, how could evolution possibly take place? Dawkins now put some “natural selection” into the computer program to simulate “real life” more closely. The computer made multiple copies of  “MWR SWINUZMLDCLEUBXTQHNZVJQF” (symbolizing offspring) while introducing random “errors” (symbolizing mutations) into the copies.

The computer then examined all the mutated “offspring” and selected the one that had the closest match to, “METHINKS IT IS LIKE A WEASEL.” This selection by the computer (symbolizing nature) was now used to make new copies and random mutations (in a “new generation”), from which the best copy was selected again, and so on.

By ten “generations” the sequence had “evolved” to read, “MDLDMNLS ITJISWHRQEZ MECS P.” By the thirtieth generation it read “METHINGS IT ISWLIKE B WECSEL.” Instead of taking many trillions and zillions of years this time, the computer came up with the “fittest” phrase in only forty-three generations.ⁱⁱ

I am sure you recognize the obvious problem with this “experiment.” The most obvious problem is that the computer already had the “correct” phrase programmed into it ahead of time, which it could use to compare any future phrases to see if they were getting closer. Evolving something that is already there is not evolution of anything new at all. If nature already has what it needs, then it does not need to “evolve it.”

If computers could be so easily creative in the way Dawkins describes, we would not need Shakespeare now would we? If somehow all of Shakespeare’s works were destroyed Dawkins would say, “Do not worry! I have a computer program that can evolve them back again in no time!”

Another problem with Dawkins’s illustration is that nature cannot select for what is functioning. Nature does not “see” the actual letters of words (in DNA or Protein). All that nature can see is what function results. Since function is arbitrarily attached to words by an outside source of information as previously described, a gradual change in the letters of the words themselves is not going to result in a gradual evolution of their meaning or function.

A gradual change in a recognized word will most likely destroy its original meaning. And, even if a new word with a new meaning does happen to evolve by chance, the definition itself (the function) had to have already existed. Without function the entire way, natural selection is blind and even Dawkins will admit that without natural selection to guide evolution, evolution is statistically impossible.
   
There in fact is no direct experimental evidence in literature detailing the evolution on any biological system or gene with a unique function. Michael Behe, a professor of biochemistry at Leigh University, says, “Molecular evolution is not based on scientific authority. There is no publication in the scientific literature in prestigious journals, specialty journals, or books that describe how molecular evolution of any real, complex, biochemical system either did occur or even might have occurred. There are assertions that such evolution occurred, but absolutely none are supported by pertinent experiments or calculations.”ⁱⁱⁱ

The changes and mutations that are observed that result in changes in function, such as in sickle-cell anemia, hemophilia, bacterial antibiotic resistance, cave fish without eyes, and changes in finch beaks do not result in any change in type of protein function. All of these changes are changes in the amount of protein function, but there is no example showing a change in type of protein function.

For example, let’s say that I have a key that fits into a particular lock. If the key gets mutated so that it fits the lock better, it might turn the lock easier. However, the same function happens after the lock is turned. If the key is mutated so that it no longer fits the lock, then the lock will not turn and the previous function that resulted from turning the lock such as launching a missile, starting a car, or opening a diary will be lost. In each case, the same function occurred or did not occur. In none of these cases did a new type of function result from mutating the key.

A loss of gene or change in the amount of its expression might make a creature look different or maybe even survive better in certain environments, such as flightless birds on windy islands or cavefish without eyes, but this is not evolution in that no new genes with new functions evolved.

Should these facts be passed by unacknowledged by the scientific mind? It seems like evolutionary theories have had ample time to prove themselves. “It is good to keep in mind…that nobody has ever succeeded in producing even one new species by the accumulation of micromutations. Darwin’s theory of natural selection [as a creative force] has never had any proof, yet it has been universally accepted.”^iv

If significant evolution could happen in just a few generations as Dawkins indicates, then why is it not being observed in cells like bacteria that have very short generation times? Over the past 50 years, greater than one million generations of E. coli have been observed, radiated, drugged, burned, frozen, dissected, mutated, selected, and manipulated in every conceivable manner and yet not even one functionally unique gene has evolved in E. coli in all those generations. This seems especially strange when one considers that humans supposedly evolved from apes in less than 200,000 generations using a much lower mutation rate: one mutation per gene per 100,000 generations.^v,vi

Why is this? Dr. Robert Macnab seems to be asking the same question when he states, “one can only marvel at the intricacy in a simple bacterium, of the total motor and sensory system which has been the subject of this review and remark that our concept of evolution by selective advantage must surely be an oversimplification. What advantage could derive, for example, from a ‘preflagellum’ (meaning a subset of its components), and yet what is the probability of ‘simultaneous’ development of the organelle at a level where it becomes advantageous?”^vii

Gordon Taylor also observes, “In all the thousands of fly-breeding experiments carried out all over the world for more than fifty years, a distinct new species has never been seen to emerge… or even a new enzyme.”^viii

“An intelligible communication via radio signal from some distant galaxy would be widely hailed as evidence of an intelligent source. Why then doesn’t the message sequence on the DNA molecule also constitute prima facie evidence for an intelligent source? After all, DNA information is not just analogous to a message sequence such as Morse code, it is such a message sequence.”^ix Has design theory come full circle? Many, even among the most respected scientific minds, seem to be giving it another look.

i Lubert Stryer, Biochemistry (1988): 153, 744.
ii Richard Dawkins, The Blind Watchmaker (1987).
iii Michael J. Behe, Darwin’s Black Box (The Free Press, 1966).
iv R. Goldschmidt, PhD, DSc Prof. Zoology, University of California, Material Basis of Evolution (Yale University Press).
v Achilles Dugaiczyk, “Lecture Notes, Biochemistry 110-A” (Riverside: University of California, Fall 1999).
vi Francisco J. Ayala, Teleological Explanations in Evolutionary Biology (Philosophy of Science, March 1970): 3.
vii Rober Macnab, “Bacterial Mobility and Chemataxis: The Molecular Biology of a Behavioral system,” CRC Critical Reviews in Biochemistry volume 5 4 (December 1978): 291-341.
viii Gordon Taylor, The Great Evolution Mystery (New York: Harper and Row, 1983): 34, 38.
ix Charles B. Thaxton, Walter L. Bradley, Robert L. Olsen, The Mystery of Life’s Origin, Reassessing Current Theories (New York Philosophical Library, 1984): 211-212.