Kirk Durston: A common either-or mistake both Darwinists and ID theorists make
|July 25, 2013||Posted by News under Biophysics|
Biophysicist Kirk Durston of the New Scholars Society offers an explanation below:
Note: Kirk Durston is back and this post has been stuck to the front page until late this evening EST, so that further comments and his responses may be noted. – News
There is a common either-or mistake made by most Darwinists and, quite frequently, by ID theorists as well. The mistake, which is an example of the fallacy known as the false dichotomy, can be described as occurring when one assumes that either no functional information encoded in the genomes of life can be produced by natural processes, or all of it was produced by natural processes. A closely related mistake made by Darwinists is the assumption that if natural processes can produce a trivial level of functional information, then we can safely conclude that natural processes can produce all biological information.
There are still challenges in mathematically defining functional information or functional complexity. For my purpose here, however, I will simply use the mathematical descriptions published by Hazen et al., and Durston et al. Both approaches cited are very closely related to an earlier equation published in 1951 by Leon Brillouin, which can be simply represented as
FI = -log nf/nt
Where nf = number of sequences that are functional and nt = the total number of possible sequences. It should be clear from the above equation that if nf is large enough for examples to be generated by random recombinations, then functional information (FI) can be generated by random natural processes, albeit a trivial level. For example, it is clear from work done at the Georgia Institute of Technology, that nf for simple binding pockets is pretty high, which entails that the FI required to code for binding pockets is relatively trivial.
Reflection on the above equation reveals that the FI required for a given function can range anywhere from zero to some very high number. It is, therefore, a mistake to assume that FI can only be generated by intelligence; a trivial level of FI can be produced by completely mindless processes, as should be obvious from the above equation, and as the Georgia Tech results illustrate.
It is also a mistake to assume, as many Darwinists do, that because mindless processes can generate a trivial level of FI, therefore mindless processes can generate high levels of FI. Again, reflection upon the above equation (or the more detailed equations published by Hazen or Durston) reveal that the higher the FI required, the less probable it becomes (i.e., the nf/nt ratio approaches zero).
The fatal mistake made by Darwinists at this point is to invoke what has become the Darwinist god-of-the-gaps, namely selection. As we can illustrate from evolutionary algorithms, selection requires a fitness function which, itself requires FI to encode. Of course, it follows from what I am arguing here that trivial levels of selection can be produced with trivial levels of FI. The question is whether natural selection has sufficient information to locate stable, functional, biological proteins. All our work to date seems to falsify that option and verify the need and actual role for intelligent design (in this case human) when producing artificial proteins of any significant structure. To clarify, recent building of artificial proteins is an example of intelligent design in action.
The Georgia Tech work has led some Darwinists to believe that because binding pockets are relatively trivial to encode in a sequence that, therefore, we have somehow explained how natural processes could have encoded biological proteins. In real life, however, proteins are about a lot more than simple binding. Binding to the right molecule is important, at the right time, at the right location and with the right binding strength so that the bond can be broken at the right time and place, etc. This can often require a larger 3D structure for proper functionality, that has a nf/nt ratio approaching zero. For example, if we take the results published for 35 protein families by Durston et al., and solve for nf/nt, we observe that it is extremely small for many protein families.
My contention is that the ability to generate statistically significant levels of functional information is unique to intelligence. It follows from this that if a function can be achieved with a statistically insignificant level of FI, then intelligence is not required. Statistical significance, therefore, is the safeguard against false positives and can be measured in a variety of ways, such as measuring the adjusted residual of the outcome and choosing a cutoff that represents a very high confidence level, such as 99.9% or greater. With this in mind, an executive summary of my own case for intelligent design in biological life is available here.