Trial-And-Error: Unthinking Process or Argument for Intelligence?

For my 100th post, I decided to finally finish something I've been working on for some time.

Trial-and-error is the process by which naturalistic evolution, or as The Free Dictionary puts it, “Change in the genetic composition of a population during successive generations, as a result of natural selection acting on the genetic variation among individuals, and resulting in the development of new species,” is advanced. This is an idea Carl Sagan wrote about when discussing fossils, “The fossil record implies trial and error, the inability to anticipate the future, features inconsistent with a Great Designer (though not a Designer of a more remote and indirect temperament.)” Trial-and-error in evolutionary process is also supported by sites like What Is Life, who state, “Evolution works because it produces change through trial and error.” So, with so many Evolutionists and resources touting trial-and-error as natural selection’s mechanism, then why even question the contrary?

First we must ask the question, “What exactly constitutes trial-and-error?” The term is defined by Dictionary.com as “experimentation or investigation in which various methods or means are tried and faulty ones eliminated in order to find the correct solution or to achieve the desired result or effect.” Really, how else would evolution be able to work as it “finds” out which biological arrangements are going to work in the genetic scheme of things and which arrangements just won’t stand a chance? However, I believe the more time one spends thinking about this evolutionary process, the more it doesn’t make atheistic sense. Have you ever just sat down and thought about how complicated biological trial-and-error would be?

While doing research for this article I came upon a question in Yahoo! Answers about the lack of trial-and-error evidence in the fossil record. One of the answers was priceless as it explained that trial-and-error change involves very small changes such as slightly higher levels of hemoglobin. For those who don’t know, hemoglobin is a protein found in the red blood cells which carry oxygen throughout the body using the blood stream. Now, this got me thinking about what it would take to actually evolve hemoglobin to the levels we find today in the human body.

Let’s start with the normal concentration of hemoglobin in the blood of the average human at birth. According to Medscape, the normal concentration is a mean of 16.5 g/dL with a range of 14-24 g/dL. When the hemoglobin concentration starts deviating from the normal range, health problems start to occur. According to Medscape, a low hemoglobin level is categorized as anemia. As the concentration decreases to critical levels, the person is susceptible to congestive heart failure, myocardial infarction (heart attack), and stroke (Hemoglobin Test, 2011). High hemoglobin concentration is often a product of polycythemia (high volume of red blood cells in the blood) and is just as dangerous as anemia because the condition can lead to thrombosis (spontaneous clotting), congenital heart conditions, and stroke (Besa, 2012). Every one of these disease processes is lethal without the intervention of modern medical therapies.  

So, let’s explore the process by which the correct levels of hemoglobin in the human body were determined by evolutionary processes. There are many articles upon review which describe aspects of the evolution of hemoglobin (like this one); however, a literature review using the phrase hemoglobin and trial and error yielded no such description of the trial and error process in relation to hemoglobin. Thus, we must critically think about how such a process would work in reference to trial-and-error. 

Obviously, it would have initially involved a wide range of hemoglobin levels within different hominids or else not enough hominids would have survived the process and this current conversation could not even happen. This process should be fairly simple because the early humans who exhibited anemic or extremely high levels would just die out and leave those within the correct levels alive. This is where we run into trouble. How did natural selection determine that outlying levels of hemoglobin killed these organisms? Evolution from single-celled organisms to what we have today is a process that is said to have occurred over 4 billion years and, therefore, many millions of biologic processes, structures, and mechanism had to be evolving at the same time. Within the same time frame that natural selection is determining the correct levels of hemoglobin in the blood, it might be determining correct hormonal balances, the correct steps of clotting cascade, or any of the other billions of essential mechanisms inside an organism. 

Another problem arises from this inquiry, millions upon millions of biologic mechanisms within the cells and tissues must work correctly just to keep us alive.  At all times, cells are constantly transporting sodium and potassium ions across their membranes using Sodium-Potassium ATPase pumps to maintain resting potential. This process allows our cells to react to changes in the environment, to communicate with other cells, and to help keep cells working. Membrane potential is an essential part of the transportation of neurotransmitters and hormones throughout the body which are used for everything from temperature regulation to energy consumption. An example would be Insulin which is an essential hormone that regulates glucose levels and diabetics can tell you all about its biologic necessity. 

The point of all this scientific jargon is to show that hemoglobin would not have been the only thing being fine-tuned at the time of its development in hominids. Natural selection would have had to single out hemoglobin out of all the other developing biomechanics to determine inadequate levels as the culprit for an organism’s death. That would be highly suspect because human intelligence would be hard-pressed to figure this out let alone an unthinking process such as natural selection. 

Let’s say then that natural selection did indeed determine that inadequate hemoglobin levels killed the organism. We now have a problem with sample size. Any researcher knows that sample size is the key for any experimental trial to determine statistical significance. Sakpal (2010) demonstrates that small sample size can lead to under-estimation and result in a lack of statistical significance.

With all of these processes developing in an organism at one time, the rate of death would have to be extremely high while natural selection is fine-tuning. Thus, with the millions of ways one can die from the failure of compensatory mechanisms, how could the sample size for human evolution ever be large enough? Millions of factors means that millions or even billions of subjects have to be alive at one time and even with these numbers, the sample size of viable organisms would be relatively small leading to statistical insignificance. In the biological selection process, statistical insignificance would prevent natural selection from determining with any certainty the correct hemoglobin range. 

Evolution and natural selection are solid until one has to really think about the difficult questions. Inquiries into the process of trial-and-error which superficially seems like a slam dunk for the theory actually can destroy it. Can evolution really be explained by an unthinking trial-and-error process or is intelligence inherent in the intricacies of biology? In light of the arguments posited in this article, the latter idea makes much more sense.    

References:

Besa, E.C. (2012). Polycythemia Vera. Medscape. Retrieved from http://emedicine.medscape.com/article/205114-overview.

Mayo Clinic. (2011). Hemoglobin Test. Retrieved from http://www.mayoclinic.org/tests-procedures/hemoglobin-test/basics/definition/prc-20015022.

Merritt, B.Y. (2012). Hemoglobin concentration. Medscape. Retrieved from http://emedicine.medscape.com/article/2085614-overview#aw2aab6b3.  

Sakpal, T.V. (2010). Sample Size estimation in clinical trial. Perspectives in Clinical Research, 1(2), 67-69.