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Friday, September 11, 2009

Logical Practicum 2 - Evolution part 3

Now that we have defined some of the terminology used and misused in the debate, let us examine the limitations and shortcomings of evolution and the scientific method as applied to origins science.

Firstly, note that the scientific method cannot say anything about origins science. This is because no observation can be made of what happened in the distant past ('distant' being relative, but accurate enough regardless). Currently, no experiments can be realistically devised or conducted that would prove or disprove that Homo erectus evolved to become Homo sapiens. Certainly, one cannot repeat these experiments - origins science deals with a sequence of events that occurred once in history that we know of. Therefore, neither evolution nor creationism can properly be called theories. They cannot even be called hypotheses, because we have not observed either in action (again, remember that evolution is the arising of new traits and new descendant species from ancestor species through random, undirected processes). At best, they are models, a framework through which we interpret evidence.

In other words, both of these models are just the updated versions of Kipling's "Just So" stories.

Secondly, evolution flies in the face of Occam's Razor -but in order to understand this, we need to digress a little into the world of statistics. If you have a standard 6-sided die, which is truly fair and truly random, then each time you roll it, the probability that you roll any given number (say 1) is 1/6, because each outcome is equally likely. Likewise, the probability of any given sequence of number rolls is equally likely, hence 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 is just as likely as any other sequence of 15 rolled numbers. Statisticians would say that therefore, you shouldn't be surprised if you get this sequence of rolls.

Well, yes. Statistically, this is true. However, in the real world, by the time you roll the 7th '1' in a D&D game, odds are overwhelmingly in your favour that (a) you're fucking up the die roll or (b) someone has gimmicked the die or the surface on which you roll to give you continuous critical failure rolls. This is because you are no longer operating in a vacuum.

Evolution also does not operate in a vacuum. In order for it to be a viable explanation/model, it must explain a large series of steps, some of which I highlight below;

  1. Life from non-life
  2. Multicellular from unicellular
  3. Sexual reproduction from asexual reproduction
  4. Animal from plant (or vice versa)
  5. ...
  6. Verterbrate from invertebrate
  7. ...
  8. Warm-blooded from cold-blooded
  9. ...
  10. Irreducibly complex systems from scratch
Each ellipse represents several more steps that needs to be explained. Taken one step at a time, maybe you can explain the evolutionary pressure and possibilities, but remember, this is all random and undirected. It's not as if the organisms in question can decide to evolve lungs from gills and start the process going for several generations.

But just to give you a hint of how difficult it is, the simplest self-sufficient organism currently known to mankind is the Mycoplasma genitalium, with 580,000 base pairs. In genetics, the four amino acids that form our genes (and the base pairs) are AGTC; adenine, guanine, thymine and cytosine. They come paired, so essentially, our genes are both digital binary storage systems and binary computers. The chances of evolution bringing this organism to life (remember that life is an atomic state; either something is alive or it is not alive) in one fell swoop is 1/2^580,000. It's too large for the Windows calculator to output, but to give you a hint? 2^100,000 is 10^30103. That's step 1. You calculate the rest of it.

Thirdly, evolution flies in the face of information science. We know that information exchange must involve at least one intelligent source, and our genes are computers, with DNA being information. Take a good look at the simple organism above. Its genes, amongst other things, have functions for redundancy, repair, replication, energy conversion and locomotion, as well as other cellular activities. And all of this is achieved with essentially half a megabit (or 64KB) of information. How does it do that? Well, it uses a very sophisticated compression algorithm, because if you took the genetic data from position 1-8, for example, it does one valid thing, and if you took positions 2-9, it does another valid thing. This is the stuff of legends, stuff that only Mel the Real Programmer would pull.

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