Back in 2003 NATURE (vol 423, pp 139-144) published an article by Richard Lenski, Charles Ofria, Robert Pennock, and Christoph Adami titled “The Evolutionary Origin of Complex Features.” The abstract reads:
A long-standing challenge to evolutionary theory has been whether it can explain the origin of complex organismal features. We examined this issue using digital organisms—computer programs that self-replicate, mutate, compete and evolve. Populations of digital organisms often evolved the ability to perform complex logic functions requiring the coordinated execution of many genomic instructions. Complex functions evolved by building on simpler functions that had evolved earlier, provided that these were also selectively favoured. However, no particular intermediate stage was essential for evolving complex functions. The first genotypes able to perform complex functions differed from their non-performing parents by only one or two mutations, but differed from the ancestor by many mutations that were also crucial to the new functions. In some cases, mutations that were deleterious when they appeared served as stepping-stones in the evolution of complex features. These findings show how complex functions can originate by random mutation and natural selection.
At no point in the paper is ID or any proponent of ID cited. Yet, when co-author Christoph Adami gave a PowerPoint presentation on Avida at a AAAS meeting some time back in Washington DC, his concluding slide showed Behe and his book DARWIN’S BLACK BOX. Moreover, Adami indicated that the whole point of this work on Avida was to refute Behe. Likewise, when co-author Rob Pennock wrote his expert witness report for the Kitzmiller v. Dover case, he claimed that his work on this NATURE article constituted a refutation of Behe.
The hypocrisy here is breathtaking. On the one hand, we are told that ID is not science. On the other hand, articles in places like NATURE appear that are clearly motivated by ID. And yet, the articles themselves are scrupulous to avoid referencing ID, its proponents, or published writings lest we gain an entry in the Science Citation Index and thus can further strengthen the case that ID is indeed science.
It was clear to the authors of the NATURE article that the shrill, illogical reviews of Behe that appeared early on would not silence him. But it was also clear to them that addressing him forthrightly in a prominent scientific venue could backfire, indicating that Behe was on to something important even if he was ultimately wrong. Some scientific mistakes are illuminating. If Behe were charged with committing an illuminating scientific mistake, then he would still be doing science (rather than pseudoscience or religion). Hence the subterfuge of not citing him at all the in NATURE article.
In any case, a thorough deconstruction of Lenski et al.’s article and of Adami’s Avida program has been long overdue. That deconstruction is now available:
Winston Ewert, William A. Dembski and R.J. Marks II, “Evolutionary Synthesis of Nand Logic: Dissecting a Digital Organism,” Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics. San Antonio, TX, USA – October 2009, pp. 3047-3053.
Abstract: According to conservation of information theorems, performance of an arbitrarily chosen search, on average, does no better than blind search. Domain expertise and prior knowledge about search space structure or target location is therefore essential in crafting the search algorithm. The effectiveness of a given algorithm can be measured by the active information introduced to the search. We illustrate this by identifying sources of active information in Avida, a software program designed to search for logic functions using nand gates. Avida uses stair step active information by rewarding logic functions using a smaller number of nands to construct functions requiring more. Removing stair steps deteriorates Avida’s performance while removing deleterious instructions improves it. Some search algorithms use prior knowledge better than others. For the Avida digital organism, a simple evolutionary strategy generates the Avida target in far fewer instructions using only the prior knowledge available to Avida.