Darwinism Intelligent Design

Stephen L. Talbott: “Let’s Not Begin with Natural Selection”

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Talbott, a Third Way* scientist, has been writing a book for some years online as a critique of Darwinism. Here’s some information from a recent instalment where he talks about the fact that “natural selection” acting on random mutation to produce the immense diversity of living things is so simple an idea that many felt it really didn’t need evidence, just acceptance. But:

Look at it this way: everything depends on what organisms actually do — and, as has long been recognized, one of the most remarkable things they are capable of doing is to give consistent, generation-by-generation expression to the character of their own kind. Whether that kind needed to be understood as a static or dynamic reality could only be resolved through empirical investigation.

Moreover, once we see that species have in fact evolved, we are still left with the most basic questions about how they have done so:

– What sorts of directionality, if any, will we discover in evolutionary change? For example, might change be directed toward more complex or less complex forms of life? Toward greater individuality or more collective interdependence? Toward some sort of diversity, balance, and qualitative completeness upon the earth as a whole? Toward the realization of human potentials?

– What pathways of change are open to any given species at a particular time, and what pathways are closed off by the character of the organisms themselves or of the surrounding world? In what ways will molecular and physiological processes be conserved in different organisms during evolution, and in what ways will they diverge?

– How much convergent evolution should we expect? (“Convergent evolution” refers to the independent development of similar features in distinct branches of the “tree of life” — something now known to be strikingly common, as when the “camera-eye” of the octopus and of humans developed independently of each other)?

– How much diversity of life should we expect, and how radically disparate are the possible forms of life?

– Is evolutionary change more or less possible today than at various times in the past?

– Do populations evolve sporadically or continuously, and why?

– What accounts for the uncanny qualitative unity of an organism — a unity leading one observer to say of the sloth, for example, that “every detail speaks ‘sloth’” (Holdrege 1999).

I can think of no fundamental question about evolution whose answer is suggested by the advertised formula for natural selection. Everything depends on what the amazingly diverse sorts of organism actually do as they respond to and shape their environments. Contrary to Susan Blackmore’s exultant insight, nothing in the “algorithmic logic” of natural selection tells us that evolution must have happened — and, given that it has happened, the logic by itself tells us little about what we should expect to find in the fossil record. We may ask then, “What, in truth, is being celebrated as the revolutionary principle of natural selection?”

Stephen L. Talbott, “Chapter 19: Let’s Not Begin With Natural Selection” at Nature Institute

*The Third Way of Evolution seems to want to rescue science from the twin perils of pulpit-banging about creation and, for example, the Darwinbird of pop science (theses about nature whose only merit is support of Darwinian ideas).

It’ll certainly be an interesting book when he finishes it.

Hat tip: Philip Cunningham

5 Replies to “Stephen L. Talbott: “Let’s Not Begin with Natural Selection”

  1. 1
    polistra says:

    Natural selection isn’t an algorithm, it’s just an uninteresting tautology.

    Survivors survive.

    I suppose you could write this in computer code, but it would be an unnecessary step, like

    if (x == 5) then XisFive = TRUE

  2. 2
    ET says:

    Natural selection is nothing more than contingent serendipity.

  3. 3
    bornagain77 says:

    Is Natural Selection Like a Computer Algorithm? – July 23, 2014
    Excerpt: The only algorithm possible for evolutionary theory is what we might dub (after Berlinski) the SDLA: the “Sheer Dumb Luck” Algorithm. Unfortunately, that algorithm is weighted heavily in favor of entropy and extinction. We would hope that Darwinists would not try to transfer their algorithm back onto the computer scientists. It may be too late for the economists.

    Top Ten Questions and Objections to ‘Introduction to Evolutionary Informatics’ – Robert J. Marks II – June 12, 2017
    Excerpt: “There exists no model successfully describing undirected Darwinian evolution. Hard sciences are built on foundations of mathematics or definitive simulations. Examples include electromagnetics, Newtonian mechanics, geophysics, relativity, thermodynamics, quantum mechanics, optics, and many areas in biology. Those hoping to establish Darwinian evolution as a hard science with a model have either failed or inadvertently cheated. These models contain guidance mechanisms to land the airplane squarely on the target runway despite stochastic wind gusts. Not only can the guiding assistance be specifically identified in each proposed evolution model, its contribution to the success can be measured, in bits, as active information.,,,”,,, “there exists no model successfully describing undirected Darwinian evolution. According to our current understanding, there never will be.,,,”

    The Turing Test Is Dead. Long Live the Lovelace Test.
    Robert J. Marks II – July 3, 2014
    The limitations invoked by the law of conservation of information in computer programming have been a fundamental topic of investigation by Winston Ewert, William Dembski and me at the Evolutionary Informatics Lab. We have successfully and repeatedly debunked claims that computer programs simulating evolution are capable of generating information any greater than that intended by the programmer.8,9,10,11,12,13

    Algorithmic Information Theory, Free Will and the Turing Test – Douglas S. Robertson
    Excerpt: Chaitin’s Algorithmic Information Theory shows that information is conserved under formal mathematical operations and, equivalently, under computer operations. This conservation law puts a new perspective on many familiar problems related to artificial intelligence. For example, the famous “Turing test” for artificial intelligence could be defeated by simply asking for a new axiom in mathematics. Human mathematicians are able to create axioms, but a computer program cannot do this without violating information conservation. Creating new axioms and free will are shown to be different aspects of the same phenomena: the creation of new information.

    “To the skeptic, the proposition that the genetic programmes of higher organisms, consisting of something close to a thousand million bits of information, equivalent to the sequence of letters in a small library of one thousand volumes, containing in encoded form countless thousands of intricate algorithms controlling, specifying and ordering the growth and development of billions and billions of cells into the form of a complex organism, were composed by a purely random process is simply an affront to reason. But to the Darwinist the idea is accepted without a ripple of doubt – the paradigm takes precedence!”
    Michael Denton, Evolution: A Theory In Crisis, London: Burnett Books, 1985, p. 351

  4. 4
    ET says:

    Evos are so clueless they think that casinos use natural selection to make money. How desperate and ignorant are those people, anyway?

    Casinos making money is nothing like biology, you desperate fools.

  5. 5
    ET says:

    The reason casinos make money is due to intelligent design. That is how it is set up by people who know what they are doing. It is very telling that evos are too dull to grasp that fact.

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