Natural selection

Creation-Evolution Headlines on natural selection

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Time to ditch natural selection?

If NS were a law of nature, we would see every organism trending along the same trajectory: for instance, bearing more offspring. But NS explains opposite outcomes with equal ease (see Oct 1 entry for examples). It explains why the sloth is slow and the cheetah is fast. It explains why the roundworm is round and the flatworm is flat. It explains why some animals bear lots of young and why some bear few. We are led to believe that NS explains up, down, in, out and sideways by some mysterious, aimless force, and whatever results was caused by NS. For some time now, I have been calling NS the “Stuff Happens Law” because NS is simply a restatement of the phrase, “stuff happens.” The Stuff Happens Law is the polar opposite of scientific explanation. NS, therefore, is a charade, amounting to giving up and saying, “We don’t know; que sera, sera.”

Yes, CEH, but that is natural selection’s strength, not its weakness!

Any bimbo who can offer an opinion on Talk TV can “believe in” evolution. (Don’t ask him about the findings from the Large Hadron Collider or Saturn’s rings though … 😉 )

That’s the bar to clear. I believe that only the collapse of legacy mainstream media’s reputation as a serious source of information (resulting in a fire sale of bimbos) could help us clear it.

If governments adopt legacy MSM as their PR tool and try to suppress alternative sources, that will just turn the MSM into the old Soviet Pravda and TASS (no news in the truth and no truth in the news). So the news will still get out, just much more inconveniently.

Fortunately, the MSM seem to be extinguishing reasonable trust fairly swiftly.

Nothing is caused by natural selection. No evolutionist predicts natural selection. They never say (or can say) that “Given these boundary conditions, Gene X will mutate at the 152nd base, and this new adaptive function will result and overtake the competition.” Maybe under extremely well-controlled lab conditions with microbes they come close to this, but never in the wild. It’s always after-the-fact rationalization.

No, they never do and they never need to … yet.

Today’s selection theory seems very precise and mathematical. In journal papers, you can find neo-Darwinians measuring coefficients of selection and using them in differential equations. They speak of positive selection, negative selection, balancing selection, purifying selection, and epigenetic selection. In my experience, this is all hand-waving. … More.

Well, they get paid to do it and teach it.

See also: Natural selection: Could it be the single greatest idea ever invented?

and Talk to the fossils: Let’s see what they say back

5 Replies to “Creation-Evolution Headlines on natural selection

  1. 1
    bornagain77 says:

    Definitely a keeper! 🙂

  2. 2
    tjguy says:

    What is “MSM”?

  3. 3

    Natural selection sorts organisms in terms of survival / reproduction.

    When considering intelligent design then a table, a sewing machine, an airplane, are also functionally complex objects, just like organisms.

    The difference between the sewing machine and the organism, is that the organism is designed in terms of reproduction / survival, while the sewing machine is designed in terms of sewing. Every part of the organism contributes to survival / reproduction in some way.

    If natural selection is real, then an intelligent designer could use the law of natural selection to look into the future to see which organisms are fit for survival / reproduction.

    This is basically the logic of the quantum computer solves problem without running experiment.

    http://news.illinois.edu/NEWS/06/0222quantum.html

    But then it would be a natural and more sophisticated occurrence of it.

  4. 4
    Axel says:

    It was always a nonsense, since ‘selection’ implies a subject as well as a predicate. And Mother Nature as the implicit subject is an infantile periphrasis for God. (Who or what else?)

  5. 5
    forexhr says:

    One of the ways to refute Darwin’s theory is to show that evolution can build things by random chance alone and that natural selection has absolutely nothing to do with it, since even the most ardent advocates of evolution admit that organisms complexity is orders of magnitude too improbable to have come about by chance.

    In order to successfully demonstrate this point we first have to define the meaning of the word “solution” in biology, of course in the context of evolution. Since the DNA is a molecule that carries most of the genetic instructions used in the development and functioning of all known life, the solution in biology is nothing but some arrangement or combination of nucleotides in a DNA. To be more precise, it is the combination of nucleotides that contains the information on how to billd some biological structure with the ability to cope with a particular problem at the level of environment, cell or the whole organism.

    Let us now look at some examples to illustrate this point. Imagine that we have an ecological or environmental area that is inhabited by some organisms. Sources of food in this area are drying up and population of organisms is introduced into a new environment. In this new enviorment there is a plenty of energy rich substances. But, the problem is that genes for metabolic pathway to convert this substance into usable energy do not exist in a gene pool of that population. Metabolic pathway that can convert this new food into useable energy consists of 2 enzymes. So the information on how to bulid those enzymes is not present in the DNA, just like information on how to bulid eyes was not present in the genetic material of the first self-replicating organism. So, here evolution needs to find a solution to this problem which means, evolution needs to find the right combination of nucleotides in the DNA so that cell can produce functional enzymes with the ability to convert new energy rich substance into a usable energy. Once this is done and solution enters the gene pool, natural selection can kick in and spread this new solution through the population. So, this was an example of finding a solution in the context of the enviorment or by filling of ecological niches.

    For the problem solving at the intracellular level we can use intronic insertions problem. Genes of today’s eukaryotic cells are interrupted by noncoding sequences called introns that need to be removed via splicing machine from the RNA molecule before the process of protein synthesis can begin otherwise they would destroy the protein-coding capacity of genes. So, from the evolutionary point of view the splicing machine is the complex evolutionary solution to the intron insertions problem, that began early in a cellular live, once one of these early cells get one of these introns inserted into a critical gene.

    Now that we know what the concept of solution in biology is, we can turn towards the critical point of this demonstration and show why fundamental assumption behind darwin’s theory of evolution is false.
    We will do that with the help of one simple analogy in the context of previous intronic insertions example. By using this analogy we will try to solve one problem via evolutionary mechanisms. Ok, let’s start.

    Imagine that someone offers to pay you one million U.S. dollars if you can provide the correct answer to the question written down on paper. So, you will be rewarded if you provide the right combination of letters, just as the cell in our intron insertions example would be rewarded if evolution provides the right combination of nucleotides in the DNA with the information to make splicing machine. The principle is the same in both problems.

    In answering a question you are allowed to use whatever method you want. You can use encyclopedias and textbooks, you can do a Google search, you can conduct science experiments, communicate with other people, and so on. But, you have only one constraint – you are required to use mechanisms of Darwinian evolution. You say, ok, I am fine with that, evolution is a powerful method of finding solutions, as demonstrated in nature and by evolutionary programming so this shouldn’t be a problem.

    Finally you ask: so what is this million dollar question? And the person replies: well, you are not allowed to see the question. Remember, you are required to use mechanisms of evolution. And we know that evolution have no intelligence and no mind so evolution can’t see, read, think, percieve,… evolution cannot grasp the problem. The only thing evolution can do in finding solutions is a random shuffling of nucleotides in the DNA and once the solution emerges natural selection process can kick in and spread this solution through the population. In the same way, you are alowed to combine existing letters, words and sentences that exist in books, newspapers, magazines,dictionaries, internet or in your mind. You can do whatever you want in creating new combinations of linguistic elements. The only constraint is your inability to use engineering and inteligent design principles in solving a problem. You are unable to notice or become aware of the question, or in other words, you are unable to create a mental representation of perceived question and then, using your cognitive faculties, to co-opt the right combination of letters, words and sentences according to this mental representation. In short, no intelligence is allowed.

    Now you just thing about the extent of the problem. The subject of the question can be any aspect of the reality that can be expressed in words. So there is a potential for nearly infinite number of potential questions. And since you do not know what the question is you don’t know what words or letters to use, how to combine them, you don’t know what amount of words constitute the correct answer. You just pick letters and words randomly, put them together randomly and hope the correct solution will pop up, so that you can win a million dollars.

    Also, in this process you are not able to communicate with the asker about a partial accuracy of the answer since communication is intelligent activity, and we know that evolution does not have intelligence and therefore its not able to communicate. In our intron insertions problem, solution consists of at least five subprocesses: to recognize mRNA and its intron-exon boundaries, then to cut the RNA, to rearrange cuted parts, to join and finally to release the mRNA molecule. Only when combination of nucleotides in the DNA that contains all five subprocesses exists only then natural selection can act. And not before. For example: If we assume the existance of splicing helper proteins that assembly at the intron-exon borders to guide small nuclear ribo proteins to form a splicing machine, this partial correctness of the splicing process won’t cause introns to magically disappear without a complete splicing machine. This partial correctness won’t cause random, blind and unintelligent process to put aside these helper proteins because they’re good for the future splicing function. Evolution has no long term goal, it cannot plan. There is no long distance target to serve as a criterion for selection.

    In the same way you will be selected by the author of the question and rewarded one million dollars only when complete and acurate answer is provided. Selection process cannot help you in finding solution. If that is the case then the only available way for you to find a solution is by pure chance. At this poin we can clearly conclude that evolution is refuted since there are 10^390 possible dipeptides for a single average protein of 300 amino acids. Since less than 10^90 of them exist as clusters of active proteins, even if all physical events that have occurred in the thermodynamic lifespan of the observable cosmos were used to find a single average protein, the probability of finding this single protein is less than a 10^150. So, to find even one average protein by chance is like winning the same lottery with the same numbers 20 times in a row.

    Finally, we will unmask the empty rhetoric and logical flaws behind the rationalizations invoked in the “covering up” of the fact that evolution proceed by random chance alone. Besides mentioned, natural selection, this rationalizations are usage of terms like “functional shift,” “exaptation,” “co-option”. We will se how absurd they sound when they are put alongside our previous examples. At the end we will see how intelligent design is presuposed in the rationalization called evolutionary algorithms.

    Functional shift is an idea in evolutionary biology where some cellular or morphological element adopts a new function. And this is said to be the process by which evolutionary novelty is generated. In the words of our analogy, you are alowed to change one semantically correct word into another, or one syntactically correct sentence into another so that existing words and sentences adopt new semantic or syntactic function or meanings. But, what that has to do with providing the right answer?? Absolutly nothing. The problem is not in creating some new random and functional word or sentence the problem is creating words and sentences which will allow you to win one million dollars. In the same way the problem in biology is not in creating some new random function, problem is in creating function that solves a particular enviormental or intracellular problem, like enzymes with the ability to convert new food into usable energy or molecular machine with the ability to cut introns.
    So the claims like: the acquisition of new functions by molecules involved in developmental pathways is suspected to cause important morphologic novelties…
    http://www.ncbi.nlm.nih.gov/pubmed/10376014
    …are nothing but empty claims. They are like saing: the acquisition of new meaning by words involved in writing a novel is suspected to cause important linguistic novelties. So, proponents of evolution completely ignore the question of how evolution finds the solution. Instead, they just appeal to the empty terms and abstract hypothetical scenarios that do not exist in reality.

    Second therm, co-option, says that the parts nessecary to create molecular machines could be taken from other molecular machines and combined into the new machine being constructed. In the words of our analogy this is like saing: words nessecary to create the correct answer could be taken from dictionary or some textbook. As we can see, this is again completely irrelevant since the problem is not in creating the new combination of words. Problem is in creating the correct combination of words in the space of nearly infinite number of possible combinations. But there is also another problem. The co-option argument presupposes that all functional parts already exist. But this is not evolution. The hypothetical first self-replicator, which is the starting point of the evolution, did not contain genes for three-dimensional cellular structures and arrangements like organs or organ systems. You cant co-opt parts of the organism like bacteria and expect kidneys to emerge. In the context of our analogy this is like using only 1 percent of the dictionary and then trying to evolve new words by randomly shuffling letters of existing words. Now imagine that after the long, long shuffling process, finally one semantically correct word pops up. This is like evolving one new functional protein for future splicing process. Since you dont know what the question is, this new word is completely useless to you. The potential for providing the correct answer and win one million dollar by using this new word is the same as using any other functional word. So, the ability to evolve new functional proteins does nor explain problem-solution relationship that we observe at every level of biological organization.

    Finally, we will demonstrate how proponents od evolution implicitly presuppose existance of inteligence in their explanations. They are doing this when claiming that programming techniques known as genetic algorithms mimic biological evolution as a problem-solving strategy. We will first ask a question: can you solve your million dollar question by using evolutionary algorithms. Of course not, because you dont know what the question is so you are not able to calculate fitness. To calculate fitness you have to comunicate with the asker, but we know that communication, which is an intelligent activity, is not available to evolution.

    To ilustrate this consider the following example: you start with population of 20 individuals located at the center of the soccer field. Individuals will be rewarded(selected) if they manage to reach the right corner of the field using the following metod: they are alowed to move one step at a time, in one of four different directions; left, right, forward, or backward. Direction of every step is determined randomly. We know that chances od finding solution by using this type of random search are extremely low. This is similar of answering our million dolar question by chance.
    But, we can do the following. We start our simulation and every individual is randomly moved one step in one of four mentioned directions. When this is done we measure the distance between individual and the right corner of the field. We repeat this calculation for every individual. Now using this data we calculate fitness of each individual. Next step is the selection process. We want to be constantly improving ourindividuas overall fitness. Selection helps us to keep the best individuals in the population – so individuals who are most distant from the corner are out. Now we have our next generation and we can start again the whole procces until we reach the right corner.

    Without further elaboration, we can easily see what technique is used here. At each step of the simulation we have a communication bettwen a solution and the current state of the individual. In other words, we have an a priori knowledge of the solution before the solution is reached. Without this a priori knowledge about the search space structure evolutionary programing does no better than blind search.
    The use of a priori knowledge is called planing. Plan is defined as a set of actions that have been thought of as a way to do or achieve something. By creating plans we, as inteligent agents, are creating solution before the solution exists. This solution or representation to show the construction or appearance of something, is created in the form of architectural blueprints, engineering drawings, schemes, models, prototypes and so on. Then, by using our cognitive faculties we design objects by comparing this plans with a current state of the object. In short, this activity is called inteligent design.
    So the proponents of evolution are explaining the power of evolution to the general public by attributing the design methods of intelligent agents to evolution.

    Best example of this manipulation is Dawkins weasel program presented in chapter 3 of his book The Blind Watchmaker. Dawkins knows that a purely random approach to generating biological solutions is theoretically impossible, due to the excessively huge search space. So he created WEASE program where he aims to show that the process that drives evolutionary systems — random variation and natural selection — is different from pure chance. So, how he did it? Short answer. By inteligent design. Now, long answer. Program begins by choosing a random sequence of 28 letters, it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL. By repeating the procedure, a randomly generated sequence of 28 letters and spaces will be gradually changed each generation until target phrase “METHINKS IT IS LIKE A WEASEL” is reached.

    Here Dawkins is using an a priori knowledge of the target phrase or solution – METHINKS IT IS LIKE A WEASEL- and then in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to this target phrase. So, Dawkins proved that the process that drives evolutionary systems is different from pure chance by using engineering principles and methods of inteligent design.
    Now here’s an interesting consequence of this manipulation with evolutionary programing. When creating arguments about the creative power of Darwinian evolution, proponents of evolution are implicitly presupposing the existence of intelligence. And then in the conclusion of the argument they are denying the existence of intelligence, and in the same time they mock people who are claming that living things are best explained by an intelligent cause. Isnt that intresting?

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