After Rob Pennock’s testimony the other day, Casey Luskin – who now works for the Discovery Institute – wrote an attempted critique of Pennock’s claims concerning digital evolution. Pennock is the co-author of a paper published in Nature based on research from the Digital Evolution Lab at Michigan State (Go Spartans, crush the Wolverines tomorrow), where Pennock has a faculty appointment. In that paper, they used a digital evolution program called AVIDA to model the evolution of complex features, features that would fit Behe’s definition of irreducible complexity. Not only did irreducibly complex features evolve step by step, they evolved step by step in nearly two dozen different ways. In other words, the experiment showed that there are multiple pathways to functional complexity to solve the same problem, a powerful blow against the notion of irreducible complexity.
Luskin’s criticism of that paper was nothing new. He simply cribbed criticisms that had been made by IDers before. This is not a surprise, since Luskin has no expertise whatsoever with genetic algorythms or digital evolution simulation software. But Richard Hoppe, a PT contributor and owner of a company that uses genetic algorythms to model investment markets,, does have such expertise and experience and his response shows what a critical difference that makes in understanding how it works and what it means.