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How Convergent Animal Algorithms Challenge Darwinism

Evolution News
Image source: Discovery Institute Press.

A new ID the Future episode spotlights the new book Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts. Host and Baylor University computer engineering professor Robert J. Marks talks with Animal Algorithms author Eric Cassell about the sophisticated algorithms that appear to be embedded in the brains of colony insects, granting them impressive instinctive abilities. Could these complex programmed behaviors have evolved through a blind Darwinian process? Cassell and Marks discuss the challenges to that idea, beginning with the fact that in our ordinary experience, when random changes are made to a computer algorithm, it inevitably degrades function rather than enhancing it. Digging deeper, they discuss the No Free Lunch theorems of William Macready and David Wolpert, and the problem of blind searches for everything from Rubik’s cube solutions to the formula for WD-40.

Another challenge facing attempts to explain complex programmed behaviors in evolutionary terms: There are cases where only extremely distantly related insects share certain complex instinctive behavioral strategies. This is the problem of convergence, and Cassell explains why in these cases it doesn’t work to appeal to engineering constraints as an explanation. Cassell says there’s a better explanation than mindless evolution but he suspects that many are blocked from considering it by what he terms “teleophobia.” The discussion is a taste of what Cassell explores more fully in his book. Download the podcast or listen to it here.