The testability of scientific ideas by making predictions about reality is a favorite theme with Darwinists and the atheists who love them. In The God Delusion, Richard Dawkins endorses a new atheist Ten Commandments, whose seventh commandment reads: “Test all things; always check your ideas against the facts, and be read to discard even a cherished belief it if does not conform to them.” Incidentally, that would replace the old seventh commandment, “Thou shalt not commit adultery.”
Dawkins hails evolution’s “strong prediction that if a single fossil turned up in the wrong geological stratrum, the theory would be blown out of the water.” He contrasts this with the Bible’s record of predictions. In another New Atheist tract, God: The Failed Hypothesis, physicist Victor Stenger writes, “We have no risky prediction in the scriptures that has come true.”
So with Darwinian activists, quite a lot hangs on predictions and testability. Intelligent design advocates argue that their idea is empirically testable, and Stephen Meyer lists a variety of applicable tests in his new book Signature in the Cell: DNA and the Evidence for Intelligent Design. The heart of Dawkins’ argument for atheism is a critique of the design hypothesis. If it’s true that ID can be successfully tested by making predictions about empirical reality, what of Darwinian theory? Is it enough to say, as J.B. Haldane quipped, that Darwinism would be falsified if fossil rabbits were discovered in the Cambrian strata?
Molecular biophysicist and Discovery Institute fellow Cornelius Hunter puts Darwin to the test in a new website that is really a free, easily printed book in itself: Darwin’s Predictions. His argument? Darwinian evolution indeed makes predictions — which, however, routinely fail. This requires evolutionary scientists to come up with increasingly baroque additions to and speculations upon their theory to make the data fit with the theory. It all becomes increasingly, suspiciously complicated. For example, Darwinism has a very hard time explaining altruism. Selflessness, especially toward those outside one’s family, is not what you’d expect from the evolutionary scenario. Darwinists strain to come up with explanations, resulting in many serendipitous just-so stories that are less and less tethered to scientific fact.
ENV interviewed Dr. Hunter about Darwinism’s confounded expectations, which Hunter illustrates in areas including DNA coding, molecular processes, the genomes of similar and distant species, mechanisms of biological change, animal and human behavior, and more.
ENV: Thanks for taking the time to answer some questions, Dr. Hunter. And congratulations, Darwin’s Predictions is a very readable, very accessible, and provocative piece of writing. Devastating, I would think. First of all, your subject seems like such an obvious one. Have Darwinism’s failed predictions not been covered before? Were you the first to notice the pattern? How did the idea come to you?
CH: Well, believe it or not, evolutionists are not very meticulous when it comes to tallying their failures. In fact, quite the opposite, evolutionists are positively triumphant, saying that evolution is as much a fact as is gravity. So you can see that false predictions just don’t seem very relevant to evolutionists. Who cares? The theory is a fact.
ENV: Would you give us a little historical background on testing by prediction? It goes back famously to Karl Popper, but how did the idea enter the canon of scientific thinking?
CH: Yes, Popper tried to establish criteria for what constitutes legitimate science — the demarcation problem — but simply as a matter of practicing science, the idea of testing predictions was around long before Popper. The problem is, however, you cannot just use predictions alone to evaluate scientific theories. Many different theory-evaluation methods have been proposed, and there is no winner. There is no cookbook approach to deciding if a theory should be discarded. So theory evaluation for theories in the gray area can be difficult. But a great many of the theories developed by scientists are not anywhere close to the gray area. Most fall by the wayside because they are obviously not good theories, and they do not require complex philosophical thought to evaluate. Evolution falls into this category. I don’t say that evolution is false simply because statements about truth value carry a much greater burden. What is obvious, though, is that evolution is not a good scientific theory.
ENV: Does evolutionary theory make any successful predictions that are meaningful and interesting?
CH: Well, I like the way you phrase the question. Evolution certainly does make successful predictions, but meaningful and interesting ones are difficult to locate. For instance, evolution predicts many similarities in species that are close together in the evolutionary tree, and few similarities in species that are far apart in the evolutionary tree. And we find such evidence in biology. But we routinely find significant contradictions as well. So the prediction becomes a soft prediction rather than a hard prediction. The prediction predicts the pattern where the pattern is found, but not where the pattern is not found. So the prediction is really not very meaningful or interesting.
ENV: You compare the state of evolutionary thinking to geocentrism, the idea that the sun and planets go around the earth. To explain the way planets sometimes traveled one way then another in the sky, contrary to what a geocentric model would predict, astronomers invented fictional epicycles to make sense of their unexpected observations. Would you give us a simple example of a Darwinian “epicycle”?
CH: This is where things get interesting, I think. In order to fix a false prediction the theory needs to be adjusted so that it no longer makes the false prediction. So for geocentrism the false predictions were corrected by having the planets and other objects travel in very complicated patterns, involving epicycles. In fact, using epicycles the model became very accurate, and before Kepler and Newton there was no physical reason to think that objects in the sky could not move in such patterns. But the model became highly complex — it is a great illustration of the tradeoff that often occurs between the complexity and the accuracy of a scientific theory.
You can always maintain accuracy by adding more complexity to the explanation, but then the question arises: is the explanation a description of the way nature really works, or just a description of the observables? This is a key distinction in the philosophy of science, and geocentrism is a good example of a theory with very high accuracy that was merely describing the observables, rather than nature itself.
What I think is actually more interesting than evolution’s false predictions are the reactions to those false predictions, and the incredibly complex additions to the theory that were required. Like geocentrism, evolution has a large number of epicycles. For instance, dramatic similarities are sometimes found in otherwise distant species. The eye of the squid and the human, for example, are incredibly similar. Such design convergence is rampant in biology, in spite of the evolutionary expectation. Evolutionists explain convergences as arising from similar environmental pressures.
But it has always been absolutely fundamental to the theory of evolution that biological variation be blind, not responsive, to environmental pressures. Natural selection works according to the environmental pressures, but selection only works on preexisting designs. The idea that the incredibly similar complexity of the eye just happened to arise twice independently — in very different environments — is an excellent example of an epicycle.
Tomorrow: Part II of ENV’s interview with Cornelius Hunter!