Physicist Brian Miller writes:

Jason Rosenhouse, a mathematician who teaches at James Madison University, is the author of the recent book

The Failures of Mathematical Anti-Evolutionism. The purpose of the book is to discredit the mathematical and algorithmic arguments presented by ID proponents against the plausibility of undirected evolution crafting complex novelties. Rosenhouse focuses much of his critique on William Dembski’s design-detection formalism based on specified complexity. Dembski responded in detail to Rosenhouse’s arguments, highlighting Rosenhouse’s confusion over Dembski’s theoretical framework and its application to biological systems (here, here). Rosenhouse in turn responded to Dembski’s critique. His counter-response, published atPanda’s Thumb, reveals that his opposition to Dembski is not based on any flaws in the substance of Dembski’s work but instead on Rosenhouse’s unassailable faith in the limitless creative power of natural selection.

## Rosenhouse’s Response

Rosenhouse responds to Dembski and his colleagues by asserting that their research has no relevance to biological evolution. This, in his mind, is for several key reasons. First, he claims that probabilities cannot be reliably assessed for the origin of biological structures:

Anti-evolutionists routinely present spurious probability calculations meant to refute evolution. In a lengthy chapter on probability, I explain that a proper calculation must take place in the context of what mathematicians refer to as a “probability space”. For our purposes, this means that you must have a good grasp on the range of possible outcomes, as well as an understanding of the probability distribution appropriate to those outcomes. In the context of the evolution of complex adaptations, we never have what we need to do this. As Harvard biologist Martin Nowak put it, “You cannot calculate the probability that an eye came about. We don’t have the information to make this calculation.”

## Imagination Superseding Evidence

Rosenhouse’s response to Dembski ultimately fails since it is based on what he imagines to be true about biology instead of what has been empirically demonstrated. The assertion that probabilities cannot be evaluated for biological systems is highly misleading. Exact probabilities are typically impossible to compute but calculating upper bounds to probabilities is often tractable.

Douglas Axe demonstrated for the beta-lactamase enzyme that the upper bound for the enzyme’s larger domain is 1 functional sequence in every 10

^{77 }randomly selected ones. Rosenhouse attempts to discredit this estimate by citing Arthur Hunt’s critique, but he fails to acknowledge that Axe and others showed that such negative assessments reflect misunderstandings of his research and the technical literature (here, here, here, here).

In addition, Ola Hössjer, Günter Bechly, and Ann Gauger published a mathematical model for the time required for coordinated mutations to appear in a population. Their model demonstrates that for most animals the time available for major transitions is insufficient for even a few new regulatory sequences to emerge. Yet the evolution of a structure as simple as a lens for a vertebrate eye requires dozens if not hundreds of such specified sequences (here, here). An upper bound to the probability for such a large quantity of specified complexity to arise is minuscule.

## Parallels with Human Engineering

In addition, engineers working with biologists have concluded that living systems demonstrate the same specified patterns as is seen in human engineering. For instance, leading experts in bacterial flagella have not simply concluded that these molecular machines resemble rotary motors. Instead, they concluded that they

arerotary motors (here, here, here). And flagellar navigation systems perform perfect robust adaptation, which is only achievable by two classes of control modules (here, here). The conclusion that such biological systems display specified complexity is indisputable.

Finally, the view that nature provides the information for evolutionary searches conflicts with a torrent of recent literature that demonstrates that evolutionary/adaptive processes almost exclusively tweak preexistent structures or choose from a preexistent library of traits (here, here, here). Genetic information is never gained in significant quantities, but it is at best maintained and often lost (here, here, here). In short, Rosenhouse’s belief in the creative power of evolutionary processes is based not on hard data but on his faith in the philosophy of scientific materialism and on circular reasoning.

Full article at *Evolution News.*

Arguments and counter-arguments serve a purpose in arriving at a truthful conclusion. But what if one side simply jumps ship when the waves of counter-argument become unassailable?