Scientists at Rockefeller University think they can one-up Darwin. According to Science Daily, they think they can predict evolution’s next best move. Evolution is supposed to be aimless, so it is not clear how they think they can predict chance or decide what is best. The dubious nature of their quest, however, is only exceeded by the chutzpah in their hype:
Biologists today are doing what Darwin thought impossible. They are studying the process of evolution not through fossils but directly, as it is happening. Now, by modeling the steps evolution takes to build, from scratch, an adaptive biochemical network, biophysicists Eric D. Siggia and Paul Francois at Rockefeller University have gone one step further. Instead of watching evolution in action, they show that they can predict its next best move.
In Darwinian evolution, even the slightest, infinitesimal beginnings can lead to tools as complex as the human eye. But how do innovations like these get started and propagated by natural selection when their raw material is merely individual random genetic mutations? By looking at the series of mutations in evolutionary space, Siggia, head of the Laboratory of Theoretical Condensed Matter Physics and Paul Francois, a postdoc in his lab, now provide a computational answer to one of Darwin’s biggest questions.
They generated an algorithm that, “like Darwinian evolution, showed no mercy.” Only the fittest networks were allowed to survive and reproduce. Apparently it did not occur to them that the algorithm they wrote was doing the selecting by intelligent design:
Francois and Siggia found that certain mutations automatically increased a network’s fitness and thus were immediately selected. “When you look at systems like the eye or structures like the human spinal cord, you think how could these have evolved from a simple network,” says Francois. In their current study, Siggia and Francois looked at how a complex biochemical network could evolve, and an answer came together: It is built through a specific series of mutations that is repeated over and over again, from scratch, every time they restart their simulations.
“So this is really the idea,” says Francois. “From one step to the next, you know, more or less, evolution’s next best move. In our simulations, that’s what we see.”
But can you really get something for nothing? William Dembski proved in No Free Lunch that no evolutionary algorithm works better than blind search when intelligently-inserted auxiliary information from the side door is disqualified from the algorithm (09/04/2008 and 11/18/2002 commentaries). When you see an evolutionary simulation making progress toward a goal, you can be sure of one thing: someone’s cheating.
Stupid Evolution Quote of the Week would not do justice to the insanity of this article, so this new original cartoon of the Bearded Buddha, drawn for CEH by Brett Miller, is awarded for a more appropriate level of disgrace (click cartoon for larger version, complete with sacrifices). If Obama and Biden get their way, public school students will line up at the shrine and make their offerings. Now, quickly, for your mental health, read the next entry (11/03/2008).