EV Ware: Dissection of a Digital Organism
| December 28, 2008 | Posted by Baylor Bear under Intelligent Design |
Can undirected Darwinian evolution create information?
In a celebrated paper titled “Evolution of Biological Information,” a computer program named ev, says yes. It claims to illustrate the following properties of evolution.
- “[Ev shows] how life gains information.” Specifically “that biological information… can rapidly appear in genetic control systems subjected to replication, mutation and selection.”
- Ev illustrate punctuated equilibrium: “The transition [i.e. convergence] is rapid, demonstrating that information gain can occur by punctuated equilibrium.”
- Ev disprove “Behe’s … definition of ‘irreducible complexity’ … (`a single system composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning’. “
In a wonderful friendly GUI (graphic user interface) from the people at EvoInfo.org, it is easy to show that without front loaded programmed information about the search, ev simply will not work. 
These claims therefore ring hollow.
The goal of ev is to identify a given string of bits (ones and zeros). The reason the ev program works is because of the structure created by the writer of the ev computer program. A Hamming oracle in ev, for example, tells you how close your guess is to the correct answer. Contrast this to undirected random search where you either told: No, your guess is wrong or, Yes, your guess is right. At a trillion trials per second, it would take “about 12 566 000 000 000 000 000 ([over] twelve and a half quintillion) years” to find the ev target using undirected random search. To identify the target string of bits, the Hamming oracle allows reduction of the number of trials to thousands, hundreds, and even tens.
EvoInfo’s EV Ware GUI works on your browser and is easy to use.
- A tutorial on the EV Ware GUI is here: http://EvoInfo.org/Resources/EvWare/
- And the GUI is here: http://EvoInfo.org/Resources/EvWare/ev_simulation.htm
ALSO: See the GUI autopsy results for Dawkins’s METHINKS*IT*IS*LIKE*A*WEASEL at EvoInfo.org
- Description of Weasel Ware: http://EvoInfo.org/WeaselWare.html
- Weasel Ware GUI: http://EvoInfo.org/WeaselGUI.html
61 Responses to EV Ware: Dissection of a Digital Organism
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Atom, thanks. This is a nit-picky issue, but at least it’s concrete enough for all of us to come to agreement on it, which is pretty rare in this debate.
Again, there are bigger issues. Here’s another one: Not only is the active info metric a function of the search as whole rather than of the individual components, it’s actually a function of a search model, not the modeled process itself. If we want to use the active info metric to draw conclusions about the underlying process, we have to establish some non-arbitrary way of modeling processes as searches.
Take ev for example. Schneider did not cast ev as a search — it was Marks and Dembski who did that. They could have lumped the perceptron into the fitness function, in which case the search space would be of size 4^261 with a good-sized chunk occupied by what they would call the target. This search model would have significantly less active info than their model has.
Even worse, they could have defined the target any way they wanted to, as Schneider said nothing about a target. Had they defined it to be the opposite of the message that gets conveyed to the genome, the search would be an guaranteed failure with tons of negative active information.
BTW, Schneider needs to be careful with his approach too, as it has the same problem of arbitrary modeling. For instance, what part of a signal constitutes a message, and what part is noise? It depends on how you model it. Given Schneider’s approach, I see nothing wrong with his statements about information gain, but his conclusions regarding the underlying biology may not be justified.