(Lanham, Maryland:Rowman & Littlefield Publishers, Inc., 2002, 404pp.)
Review commentary by Wesley R. Elsberry
I got my copy of "No Free Lunch" today (2002/01/17) and have just finished skimming through it. Fortunately, I'm quite familiar with Dembski's prior work, and this made it relatively easy to skim.
"No Free Lunch" brings us up to date with Dembski's thoughts on evolution and intelligent design. For those who are proponents of intelligent design antievolution, this book will be a must-read, as Dembski is the foremost philosopher for the ID movement. The first two chapters give a summary of Dembski's framework for making "design inferences". Those who have read Dembski's monograph, "The Design Inference", will see much that is familiar -- and a few things that have changed a bit. This is where we learn about "specified complexity" and what makes a "specification" a good thing in inferring design. The third chapter makes an argument that specified complexity and information theory are closely related, ending up with Dembski's assertion of a fourth law of thermodynamics, a conservation law for "complex specified information" (CSI). Chapter four moves on to Dembski's take on evolutionary algorithms, those computational analogues of biological natural selection. This is where Dembski deploys Wolpert and MacReady's "No Free Lunch" results to argue that evolutionary algorithms are incapable of producing the CSI we might identify in biological systems. Chapter five takes us to a discussion of Michael Behe's concept of "irreducible complexity" (IC), asserting relationships between specified complexity and IC, and offering a new, improved version of IC to boot. Chapter six gives us Dembski's view of how his notion of specified complexity in particular and intelligent design in general can be usefully deployed as a scientific research program.
Throughout the book, Dembski takes up arguments that critics have made. As one of those critics, I can offer my opinion that Dembski fails to track those critical arguments in certain crucial respects. For instance, Dembski brushes off a criticism concerning the reliability of his "explanatory filter" by noting that the objection is the problem of induction, but fails to either solve the problem of induction or retract the claim of reliability. In other places, Dembski fails to take up the arguments of critics, as in Dembski's mischaracterization of a program written by Richard Dawkins. Two out of three of the steps that Dembski says characterize the program are, in fact, Dembski's own invention, appearing nowhere in Dawkins's work. The sad thing is that criticism of precisely this point was made by me in email to Dembski back in October of 2000. It would have been easy for Dembski to fix, but it did not happen.
The most disappointing aspect of "No Free Lunch", though, has to do with section 5.10, "Doing The Calculation". Dembski had promised, under critical questioning, to publish an example of the application of his framework for inferring design from "The Design Inference" as it would be applied to a non-trivial example of a biological system. Section 5.10 is apparently what Dembski intended to serve as payment on that promissory note. However, it fails to deliver on several points. Dembski does not establish that the example, that of a bacterial flagellum, has a specification according to the usage in "The Design Inference". Dembski also fails to enumerate and then eliminate multiple relevant chance hypotheses, as indicated in "The Design Inference". Dembski especially does not evaluate the hypothesis that the bacterial flagellum developed through evolutionary change; a curious omission given the context. The single "chance" hypothesis that Dembski does bother to consider is a marginal refinement on the old antievolution standby, "random assembly". At least, the technical jargon looks denser around Dembski's argument than I've seen around "tornado in a junkyard" presentations. But all in all, section 5.10 does little to help those who wanted to see how a design inference could be rigorously applied to biological examples.
This book brings together in one place many of Dembski's ideas. The arguments range from very technical mathematical and logical formulations to pop culture examples to illustrate points. In my opinion, the book suffers from some very deep flaws -- it seems to me that Dembski misuses the NFL results to argue against the capacity of evolutionary algorithms to solve problems. Many more minor problems are apparent to me in even my brief acquaintance with the book. Still, if one wished to buy one book of Dembski's rather than the four that now grace my bookshelf, "No Free Lunch" would be the one to get.