First of all, it is insulting terminology to refer to professional biologists as “minions” of anyone.
Secondly, I have read them, but unlike some readers I distinguish between scientific claims and philosophical claims. Many scientists make claims for the implications of science that are really philosophical claims. Time to protest the science? Not at all. I do not feel that I have to throw out the baby of good science out with the bathwater of bad philosophy.
For example, Lawrence Krauss is an astrophysicist who claims that astrophysics proves that there is no creator of the universe and there is no such thing as spiritual reality. I vehemently disagree with Krauss’ philosophical claims, but I do not feel that I have to reject the Big Bang theory or even multi-verse theory on that basis. The fact that someone misuses a scientific theory does not have any relevance to the question of whether the theory constitutes good science. Plenty of Christian astrophysicists believe that even the multi-verse theory can be reconciled with belief in God; even an astrophysics-heavy apologetics ministry like Reasons to Believe has taken that position (here and here).
In the same way, some biologists misuse evolution to make atheistic philosophical claims. So what? I do not have to throw out the baby of good biological science along with the bathwater of bad philosophy.
I have read many of your articles and compared them to the peer-reviewed biological literature. I honestly do not know how you could possibly arrive at your conclusions. At one time I shared your opinion, but then I read the literature with an open mind and eventually realized that Behe, Stephen Meyer, William Dembski, et al. made some serious scientific mistakes on the road to their well-intentioned but erroneous conclusions. Your conclusions strike me as similarly well-intentioned and similarly unaware of the strong evidential foundation for the theory of evolution.
Actually, it is very much like astronomy, which relies solely on reconstructing the past based on Bayesian inference from observational data that exhibit patterns of statistical randomness. Laplace showed about 200 years ago that Legendre’s least squares method, when fit to a set of observations with random errors, would maximize the likelihood function and minimize the posterior error. And yes, he provided applications to astronomy, specifically with respect to planetary orbits.
Likewise, ask most people what Einstein received the Nobel prize for, and they will respond, “the theory of relativity.” And they will be wrong! Instead, he received it for his 1905 paper on Brownian motion (published the same year as his paper on special relativity). As gargantuan as the theory of relativity seems, I think the Nobel committee got it right when they honored his Brownian motion paper instead because it established statistical methods–in particular, the applications of mathematical randomness*–as foundational to the practice of physics.
That’s right, Einstein’s application of statistical randomness was judged a more important contribution to physics than the theory of relativity! However, my friend @NonlinOrg, one would never gain that impression by reading your blog. Your statements about randomness and science lag behind the practice of science by a considerable margin.
Thus when biologists like @glipsnort use statistical analysis of genomic similarities and divergences to infer neutral drift, mutations, and natural selection–and then build/test predictive models on that analysis–their methods are fundamentally parallel to the methods of physics and astronomy. Your assertions to the contrary serve only to illustrate your lack of formal/extensive training in the disciplines. The fact that you do not possess that training is no crime, of course.
In fact, here’s another illustration of the relationship between physics and biology: Steve Schaffner earned his Ph.D. in physics and now works as a computational biologist.
Have a great weekend!
Grace and peace,
Chris Falter
- Note that I am using the term mathematical randomness, which is not the same as ontological randomness. Mathematical randomness does not necessitate ontological randomness.