From The Design Matrix:
A core element of the non-teleological perspective of evolution is that mutations are random with regard to fitness. This means that mutations are not inherently forward- or outward-looking. Instead, a mutation simply occurs in a random fashion (a genuine mistake) and whether or not it benefits the organism depends on contingency, for as far as we know, evolution does not create targeted mutations to solve specific problems.
What you have instead are a large number of cells each mutating their genomes at random. The population of cells is effectively playing the lottery. The one genome that happens to mutate the “right” spot wins the prize, as this genome is at a selective advantage in comparison and will then spread its progeny throughout the population. The problem is that the lottery winners, over time, cannot be predicted and such winners may explore trajectories that not only were not intended by a designer, but may actually hinder the ability to design across time using reproduction. All of this unintended evolution can thus be considered noise.If a designer is trying to use reproduction to perpetuate a design far into the future, how does one control for all the noise that Darwinian evolution will produce along the way? What would prevent this noise from drowning out the signal of design? How can a designer solve these problems?
One strategy is to design reproduction such that random mutations cannot occur. But since random mutation is built into the quantum fabric of reality, this option does not exist for our human-like designer.
Another strategy is to design organisms such that all mutations are always deleterious. For example, it might be possible to design life using a set of amino acids that are all quite diff erent and using a genetic code that works in a way that is contrary to the Universal Optimal Code discussed in Chapter 4. With this code, all mutations could result in amino acid substitutions such that all changes are deleterious. In this case, Darwinian evolution would be used to eliminate every variant that popped into existence, ensuring that only the designed states could survive and propagate. This solution renders these designed cells fragile and unable to respond and adapt to all the contingencies of the environment. These cells would likely die at some point, and with their extinction, the whole design contained within them would be gone forever. Variation itself is necessary in order to propagate the rest of the design across time and changing environmental conditions. Attempts to eliminate the ability to produce variants would eliminate the propagation of the design.
Rather than working against mutation and Darwinian evolution, using a more subtle, yet ingenious plan, an intelligent designer might seek to enlist and exploit random mutation and natural selection. If we are faced with an obstacle that is too hard or costly to eliminate, we can turn the obstacle into something that serves our end. One clue that this approach may be at work stems from the writings of Ken Miller who, after describing how DNA is inevitably mutated, observes that “life is built around a chemistry that provides an amplifying mechanism for quantum events.”5 In other words, the DNA molecules may have been designed to tap into the indeterminate nature of quantum reality, allowing organisms to constantly sample, at random, from an immensely large pool of variants. Life was designed not only to reproduce, but to spawn variants on a theme.
At this point, let us return to the principle of mutations being random with regard to fitness. Does this really speak against the design of life and evolution? Say we expose a population of bacteria to an antibiotic. Someone might think that if bacteria and evolution were designed, the bacteria would be able to mutate only those nucleotide positions that would thwart the activity of the antibiotic. But how would you design that? Each cell would have to be endowed with an elaborate computer that would process all the data about the environment. The computer would then map all this information to a complete abstract representation of the dynamic biochemistry of the cell. From there, the computer would determine the nature of the threat of the antibiotic, its biochemical mechanism, and then realize the problem could be solved by mutating a particular position within a particular gene. Then the computer activates a pathway that precisely targets a specific “A” in a sea of A’s, T’s, C’s, and G’s. Is this even feasible? If so, is it feasible for a bacterial cell to contain such a computer? How much energy would it take to run it and faithfully propagate it for billions of years? How would the computer be propagated without losing its ability to function across deep time?
Now let us take the problem out of the lab where a single species is being challenged with a single variable. Imagine an animal living in a forest. Can a computer ever capture all the information about the dynamic, contingent environment? Including the feeding behavior of, say, a recently introduced predator? Is this feasible?
Maybe a designer developed a better solution: Let the population of cells be the computer. This population can then be thought of as a neural network, where all cells are connected, at the very least, through the same genetic program called “survive.” There is no need to install a computer in each cell that monitors the environment and programs specific changes in the genome in response to environmental challenges. That objective is carried out by the population of cells, where different solutions to an environmental challenge are put on the table through a random mutagenic walk, and the solution that works ends up changing the population. Variation among a population followed by natural selection is exactly the type of strategy a designer might employ when endowing cells with the ability to adapt and learn against the backdrop of a sea of contingency.