A Member of the National Academy of Sciences Made an Argument For Evolution That Isn’t Even Wrong

An obvious problem with evolution is its claim that complex designs arose spontaneously. Imagine some spark plugs, valves and other assorted mechanical parts coming together to form an engine. It’s unlikely no matter how many years you have. What evolutionists would need to show is that there is a long, long sequence of simpler, intermediate designs which gradually lead from a lifeless warm little pond to the incredible species in today’s world. Of course they have shown no such thing—not even close. So instead evolutionists use sophistry—explanations that are so flawed and illogical they cannot even be said to be wrong. For example, professor and National Academy of Sciences member John Avise makes this argument:

Another ID sentiment is that the emergence of biotic complexity via natural processes (unlike under intelligent auspices) is highly improbable, a notion that proponents of ID sometimes claim to document statistically. An undisputed law of statistics states that the probability of the joint occurrence of two or more independent events is calculated by multiplying together the separate probabilities of those events. For example, suppose that independent events A and B occur with random probabilities of 1 in 10 million (i.e., 10^-7) and 1 in 100 million (10^-8), respectively. The probability that both events occur together, by chance, is thus minuscule: one in a quadrillion (i.e., 10^-7 x 10^-8 = 10^-15). Mutations are examples of such rare and independent events, each typically occurring at a rate of about 10^-7 or 10^-8 per gene per generation. Suppose that a complex adaptation (such as a metabolic resistance to two different categories of otherwise lethal drugs) requires the joint presence in an organism of two mechanistically independent mutations. A proponent of ID might conclude that this adaptation is effectively unachievable by natural forces because its random probability is so very low. Divine intervention then becomes the default explanation.

But this is a gross misapplication of statistics, as the following example will illustrate. Consider a small colony of a billion bacterial cells, housed in a test tube, that lacks the genetic capacity to survive the antibiotics penicillin and streptomycin. New mutations for penicillin resistance (p+) and streptomycin resistance (s+) are known to arise randomly in bacteria, at low frequency. If the mutation rate to p+ is a plausible 10^-7, then a culture of 10^9 bacteria should by chance contain about 100 cells with penicillin resistance. When penicillin is added to the culture, all bacteria die except for those lucky 100 cells which then quickly divide and multiply to bring their number back up to a billion cells (all now carrying the p+ mutation). In this new colony, about 10 cells should by chance be resistant to streptomycin, assuming that the mutation rate to s+ is a plausible 10^-8. If streptomycin is then added to the culture, all of the bacteria die except for these 10 cells, which again divide and multiply to repopulate the test tube with a billion descendants (all of which are now p+ and s+ jointly). By this stepwise process, the unconscious operation of selection has made virtually inevitable what might otherwise have been deemed impossible—the evolution of a complex adaptation. [Inside the Human Genome, Oxford, 2010, p. 33-5]

The logic here is astonishing. In the hands of the evolutionist a failure of his theory is transformed into a victory with what can only be described as sheer absurdity. The underlying, unspoken, premise is that the stepwise fixation of single, high fitness, point mutations is no different than the evolution of all biological complexities. In fact there are precisely zero such designs that are known to be constructable via such a sequence. Indeed, quite the opposite, science points us in the opposite direction. Even the evolution a single protein falls 27 orders of magnitude short of reality, and that is according to evolutionist’s own, outrageously optimistic assumptions.

Avise’s argument is simply jaw-dropping. It is a complete misrepresentation of what we know from science.