This is the true story about how an Intelligent Design Theorist was bested by a Genetic Algorithm! It began in the summer of 2006, when Dave Thomas posted on Panda’s Thumb about how creationists of all varieties point out that a computer demonstration of cumulative selection from Richard Dawkins’ book The Blind Watchmaker had the ultimate answer, the phrase “Methinks it is like a weasel,” available to the algorithm for every step of the whole simulation. Top Intelligent Design mathematician William Dembski wrote
And nevertheless, it remains the case that no genetic algorithm or evolutionary computation has designed a complex, multipart, functionally integrated, irreducibly complex system without stacking the deck by incorporating the very solution that was supposed to be attained from scratch (Dawkins 1986 and Schneider 2000 are among the worst offenders here)
Dave’s July 2006 article, “Target? TARGET? We don’t need no stinkin’ Target!” introduced his new genetic algorithm for solving the Steiner Problem, finding the shortest set of straight-line segments connecting a given set of nodes. Unlike the Weasel, the Genetic Algorithm finds networks that satisfy the Steiner problem, without the advantage of the actual solution being provided. When Dave tried his latest algorithm on a six-node system, he was expecting the solution to be the “Double Bowtie,” as shown below.
The result of a few hours of genetic computations surprised him – the actual Steiner Solution for the six nodes looks like the following.
If Genetic Algorithm answers can surprise their authors, that should conclusively disprove the claim that these algorithms succeed only by being fed the final answers. The series of blog posts continued that summer, with responses being provided by members of William Dembski’s “Uncommon Descent” blog. When creationists claimed that the final Steiner designs were being smuggled into the solution via the Fitness Function, Dave challenged them to reverse engineer his published code, and use it to find the answer to the six-node problem, in the Design Challenge post. While ID blogger Sal Cordova was unable to find the actual solution, the Genetic Algorithm succeeded, proving once again Leslie Orgel’s Second Rule, “Evolution is Cleverer than You Are.”
Thomas wrote about this saga in the May/June 2010 issue of Skeptical Inquirer (Vol. 34, Issue 3), “War of the Weasels: An Evolutionary Algorithm Beats Intelligent Design.”
Dave published an update on NMSR.org in 2016, “The War of the Weasels is Back!“, responding to the critique of the Steiner Genetic Algorithm by william Dembski et. al.
A slide presentation from an NMSR talk, “War of the Weasels: The Creationist Assault on Genetic Algorithms“, was given in December 2019.
Another update by Dave Thomas appeared in the June/July 2020 issue of Skeptical Inquirer (Vol. 44, Issue 3), “ID Movement Still Stymied By Genetic Algorithms: War Of The Weasels Update.”
From the conclusion of the 2020 article:
There is a flaw in the ID concept of “Specified Complex Information” (CSI). While the CSI concept is usually presented as “obvious” (the solutions must be complex, and specified as well), the mathematical definition of CSI has been carefully crafted so as to make the success of either evolution or GAs absolutely impossible. Dembski et. al. have defined CSI as the property of having “500 bits of complexity”. If the Genetic Algorithm under consideration always gets the answer to the posed problem, it thus has ZERO CSI (Dembski 2002). Even Dawkins’ “Methinks it is like a Weasel” has obvious complexity, but Dembski scores it as zero CSI, because the Dawkins algorithm always converges. If, like my Steiner algorithm, the GA does get the correct answer, say, only once in about 200 trials, it has less than 8 Bits of CSI (2^8 = 256). Only if the Genetic Algorithm gets the solution rarely (literally, once in 2^500 ~ 10^150 trials), does it finally achieve the honor of possessing “500 Bits of CSI.” This is as rare as tossing a fair coin 500 times, and getting heads every time. The Game is RIGGED: Neither Genetic Algorithms nor Evolution can ever create CSI! The creationist assault on GAs is interesting, but falls far, far short of the mark.