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The Evolution of Evolution: Are Living Things Intelligently Designed to Evolve?

In his recent review (Genome Biology and Evolution, first published online January 24, 2012, doi:10.1093/gbe/evs008) of Professor James A. Shapiro’s new book, Evolution: a view from the 21st century (2011, FT Press: Upper Saddle River, N.J.), Adam S. Wilkins expresses his disagreement with Shapiro’s decidedly un-Darwinian view that natural selection’s importance for evolution has been hugely overstated:

My final disagreement with Jim [Shapiro]’s general argument concerns a truly fundamental point, however: the dismissal of natural selection as a shaping force in evolution. Thus, it is stated, at the very start of the book (top of p. 1): “Innovation, not selection, is the critical issue in evolutionary change. Without variation and novelty, selection has nothing to act upon.” While all evolutionists would agree whole-heartedly with the second sentence, most would reject the first. The matter of selection is then virtually ignored until the final section of the book. There we read, as one of nine bullet-points that summarize the core message: “The role of selection is to eliminate evolutionary novelties that prove to be non-functional and interfere with adaptive needs. Selection operates as a purifying but not creative force [emphasis added].”

Natural genetic engineering

Commenting on this claim, Wilkins highlights the fact that any adequate theory of evolution will have to account for the fact that cells are capable of what Shapiro calls “natural genetic engineering” – genetic change which is created by cellular systems, often in response to environmental challenges. What Shapiro is claiming, in a nutshell, is that cells are, to a large degree, capable of engineering their own evolution. In Wilkins’ words: “The cell is thus its own agent, its own engineer.” Or as Stephen Talbott puts it in a recent article for The New Atlantis (Fall 2011), entitled, Evolution and the Illusion of Randomness, “organisms are masterful participants in, and revisers of, their own genomes, taking a leading position in the most intricate, subtle, and intentional genomic ‘dance’ one could possibly imagine,” which enables the organism to respond “intelligently, and in accord with its own purposes, to whatever it encounters in its environment, including the environment of its own body.” That’s certainly a pretty impressive feat.

In his review, Wilkins acknowledges himself to be persuaded of the reality of natural genetic engineering, by virtue of the sheer weight of scientific evidence put forward by Shapiro (and by other scientists before him):

Altogether, the evidence marshalled in the book for genomic responses and remodelling in response to environmental and developmental cues is a long and impressive one. It includes such phenomena as: the gene rearrangements essential to and ubiquitous within the mammalian adaptive immune system; the restructuring of ciliate macronuclei; changes within the genomes of sporulating bacteria; the yeast mating type system; massive genome “restructuring” during plant hybridization; hybrid dysgenesis in Drosophila; a host of transposon and retrotransposon-mediated genetic changes in plants and animals; and much more… The general argument of the book, buttressed by all these examples – that genomes can be highly responsive to environmental influences, becoming “reformatted” to greater or lesser extent – is clearly important. It is not wholly new, however. It was made previously by Lynn Caporale (Caporale, 1999) and by Eva Jablonka and Marion Lamb (Jablonka and Lamb, 1995, 2005)…

How did cells originally acquire the ability to direct their own evolution?

However, what Wilkins finds puzzling is that Shapiro, having assembled a veritable mountain of scientific evidence that living things possess the remarkable ability to reformat their genomes in response to environmental changes, turns his back on what Wilkins regards as the only possible scientific explanation for their having this ability – namely, natural selection. The only alternative is Intelligent Design, which Wilkins regards as some kind of mystical mumbo-jumbo:

…[W]ith respect to this issue of selection, one might add that, in terms of Jim [Shapiro]’s particular thesis, it is hard to understand how cells could have the very capacities for “natural genetic engineering” attributed to them without those capacities having been evolved, in some manner and over long evolutionary spans, by natural selection. The evolution of such capabilities, favouring the process of “evolvability” (the capacity to give rise to new properties), is a fascinating subject, mentioned explicitly though only briefly in the book, and deserves more attention than it has traditionally received. Again, the only alternative for the origination of these capabilities, if one discards natural selection as the generative agent, is some supra-natural force, a position that I am certain is not being advocated here.

Given that cells are indeed capable of natural genetic engineering, could it be the case that cells are intelligently designed to evolve? And why might one prefer this hypothesis to the notion that cells acquired the ability to engineer their own evolution as a result of natural selection?

Natural genetic engineering is a striking and unexpected ability of living things, if Intelligent Design is not true

One reason for taking the Intelligent Design hypothesis seriously is that as I pointed out in my recent post, The Big Picture: 56 minutes that may change your life, the sheer complexity of the first self-replicating system, and the information needed to build it, imply Intelligent Design – a point that was tellingly made by Professor John C. Walton, a Fellow of the Royal Society of Chemistry, in a recent talk he gave on the origin of life. (Note: Before you play this video, press the PAUSE button and wait about two minutes, until the gray bar at the bottom has finished scrolling across to the right. Then press the PLAY button to start the video.) Professor Walton also argued that any hopes of beating the colossal odds against random formation of replicating RNA is based on ideology rather than science, and that no chemically or geologically plausible routes to nucleotides or RNA strands have ever been developed.

But if it is wildly unlikely that self-replicating systems developed from non-living matter without the need for an Intelligent Designer, it is even more unlikely that organisms with the startling ability to engineer their own evolution would have developed in this fashion.

Putting it another way: it is very easy to imagine a planet where life evolved, without subsequently evolving the ability to direct its own evolution, as life on Earth can. This invites the question: how did we get so lucky?

Intelligent Design overcomes two major objections to natural genetic engineering

Another good reason for supposing natural genetic engineering to have been intelligently designed is that if this was the case, then it would suffice to overcome two major objections to this evolutionary mechanism, which Wilkins highlights in his review:

The first concerns transmissibility of the induced genetic changes to future generations. Many of the phenomena involving multicellular organisms discussed extensively in the book involve DNA arrangements within the somatic cells and nuclei of those organisms… Being purely somatic, however, they are not transmitted to the next generation, and hence lack direct evolutionary potential. Indirect consequences of those genomic changes, affecting survival and ultimately “fitness” are, of course, a different matter…

Secondly, amongst the genomic remodelling events described here that can be transmitted across generations, none relate directly to developmental/morphological evolution, the main focus of traditional evolutionary biology. Instead, many of the phenomena listed that possess such direct evolutionary potential take place within the context of host-parasite “arms races”… Hence, there are (as yet) no cases of precisely targeted evoked genetic variation, to create specific new gene alleles, in response to environmental hazards…

However, if natural genetic engineering is the outcome of a program originally designed by an Intelligent Agent, then precisely targeted evoked genetic variation would not be so surprising after all. Indeed, it would be expected. Again, an intelligently designed program could allow organisms to pass down induced genetic changes to future generations, if they proved to be highly advantageous.

So, what might an Intelligent Design hypothesis of natural genetic engineering look like?

Living things are designed to evolve: Perry Marshall’s Intelligent Design hypothesis

Author Perry Marshall, in his blog article, Testable Hypothesis for Intelligent Design, Part 1, over at Cosmic Fingerprints.com, puts forward a testable Intelligent Design hypothesis, based on his belief that “evolution is an engineered process and is programmed to happen; and that the program itself is intelligent and operates in a top-down fashion”:

1) Evolutionary adaptation is the work of a “Mutation Algorithm.”

Cells employ a built-in algorithm, which engineers re-arrangement of Mobile Genetic Elements (as observed by McClintock and Shapiro). Genes and Chromosomes are re-arranged in a fantastically beautiful process which produces useful adaptations and new species.

I call this the Mutation Algorithm. It is a program which attempts to evolve when necessary and computes the optimal path to a desired result. This algorithm is described as exhibiting some form of intelligence.

This Mutation Algorithm, in combination with natural selection, explains what random mutation and natural selection cannot.

2) The Mutation Algorithm tests design options like blades on a Swiss army knife. DNA has a huge “bag of tricks” and is able to mix and match combinations of eyes, feet and claws, joints, digits, hair, skin and fur colors and patterns, switching out different “blades” as environments change.

It builds animals on a common chassis of head, spine, heart, lungs, stomach and limbs.
It ferociously defends this core chassis from being corrupted by random mutations, while switching out different variables in the head, spine, heart etc.

3) The Swiss army knife “blades” include variables that adjust the structure of incredibly complex systems with simple changes.

For example the length of a giraffe neck could be “dialed in” by a single gene which controls the length of nerve fibers, muscles, esophagus and number of vertebra, all at the same time.
This explains both small and large variations in species. DNA fills the ecosystem with every imaginable variety of life because it’s designed to.

It adjusts these variables until the creature is maximally adapted to its environment.

4) The Mutation Algorithm is normally at rest. It goes to work whenever the population is under extreme stress. This is why we see the pattern of “punctuated equilibrium” in the fossil record.

There are long periods of stability where there is no change, because the Mutation Algorithm is dormant. When there is a crisis, it activates and begins to test novel features.

5) The Mutation Algorithm operates within populations, not just individuals.

The Mutation Algorithm catalogs past mutation attempts so that it does not get “stuck” repeating past failures. Organisms somehow share information so that they can collectively test a wider variety of mutations than any one organism could attempt.

Efforts to find a mechanism by which organisms share this information will eventually be rewarded. And the mechanism that is discovered will be as surprising and revolutionary to biology as Einstein’s theory of relativity was to physics.

6) Evolutionary pathways are not random and purposeless, they are mathematically optimized in advance to reach desired destinations in the smallest possible number of steps.

An analogous process is the Taguchi method used in Quality Control, which creates a very small set of manufacturing experiments, which represent a very large number of possible manufacturing combinations.

It systematically tests them via a “design of experiments” process, then generates a new design which is a nearly optimal combination.

Thousands of possible design combinations are evaluated with only a few dozen tests….

I invite you to consider that DNA does something very similar with arrangements of modular biological components, literally calculating and anticipating possible evolutionary steps. It senses inputs from its environment and optimizes the experimental process….

My hypothesis is that DNA operates much the same way as a Kaizen / Six Sigma manufacturing operation. DNA not only actively participates in the mutation process, it also monitors the natural selection process.

I hypothesize that the genome got from single cells to humans in an incredibly short period of time – that 3 billion years from cells to mankind is an engineering feat of the highest order. That such a feat required the most advanced forms of optimization and as little waste as possible.

Perry Marshall’s hypothesis sounds like a very attractive one. It’s testable, and its explanatory power is very broad. Marshall also manages to provide a mechanism – an intelligently designed “Mutation Algorithm” – which overcomes a vital flaw of Darwinian evolutionary models: their inability to explain how evolution proceeded from microbe to man in the space of just a few billion years.

Intelligently designed evolution takes just the right amount of time to account for life on Earth

Mathematician Gregory Chaitin pointed out this glaring defect of neo-Darwinism, in a talk he gave at PPGC UFRGS (Portal do Programa de Pos-Graduacao em Computacao da Universidade Federal do Rio Grande do Sul.Mestrado), in Brazil, on 2 May 2011, entitled, Life as Evolving Software, which I blogged about here. During his talk, Chaitin (who is a Darwinist) acknowledged that Darwinian evolution seems to take far too long to generate the variety of life-forms we find on Earth today, judging from the software models he has developed, with the aim of putting Darwinian evolution on a mathematically rigorous footing and demonstrating its feasibility:

So what happens if we do that, which is sort of cumulative random evolution, the real thing? Well, here’s the result. You’re going to reach Busy Beaver function N in a time that is – you can estimate it to be between order of N squared and order of N cubed. Actually this is an upper bound. I don’t have a lower bound on this. This is a piece of research which I would like to see somebody do – or myself for that matter – but for now it’s just an upper bound. OK, so what does this mean? This means, I will put it this way. I was very pleased initially with this.

Table:
Exhaustive search reaches fitness BB(N) in time 2^N.
Intelligent Design reaches fitness BB(N) in time N. (That’s the fastest possible regime.)
Random evolution reaches fitness BB(N) in time between N^2 and N^3.

This means that picking the mutations at random is almost as good as picking them the best possible way. It’s doing a hell of a lot better than exhaustive search. This is BB(N) at time N and this is between N squared and N cubed. So I was delighted with this result, and I would only be more delighted if I could prove that in fact this [here Chaitin points to Darwinian evolution] will be slower than this [here he points to Intelligent Design]. I’d like to separate these three possibilities. But I don’t have that yet.

But I told a friend of mine … about this result. He doesn’t like Darwinian evolution, and he told me, “Well, you can look at this the other way if you want. This is actually much too slow to justify Darwinian evolution on planet Earth. And if you think about it, he’s right… If you make an estimate, the human genome is something on the order of a gigabyte of bits. So it’s … let’s say a billion bits – actually 6 x 10^9 bits, I think it is, roughly – … so we’re looking at programs up to about that size [here Chaitin points to N^2 on the slide] in bits, and N is about of the order of a billion, 10^9, and the time, he said … that’s a very big number, and you would need this to be linear, for this to have happened on planet Earth, because if you take something of the order of 10^9 and you square it or you cube it, well … forget it. There isn’t enough time in the history of the Earth… Even though it’s fast theoretically, it’s too slow to work. He said, “You really need something more or less linear.” And he has a point….

The time has come for scientists to publicly acknowledge that any version of evolution which is not intelligently designed – be it Darwin’s or Shapiro’s – (i) couldn’t possibly work in the time available; (ii) is incapable of generating the massive cellular and morphological changes that have occurred in the history of living things; and (iii) fails to acount for the emergence of the remarkable ability of organisms to reformat their genomes in response to environmental changes and thereby direct their own evolution.

Before I finish, I’d like to draw readers’ attention to one more prediction made by Perry Marshall’s model of intelligently designed evolution: the “Swiss Army knife” that he describes must have been there from the very beginning. If early fossil organisms were discovered that lacked the ability for natural genetic engineering, that would falsify his hypothesis.

So, what do readers think of Perry Marshall’s “Swiss Army knife” model of intelligently designed evolution? I’d like to invite readers to have their say, and subject Marshall’s model to the detailed scientific scrutiny it deserves.

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35 Responses to The Evolution of Evolution: Are Living Things Intelligently Designed to Evolve?

  1. The time has come for scientists to publicly acknowledge that any version of evolution which is not intelligently designed – be it Darwin’s or Shapiro’s – (i) couldn’t possibly work in the time available;

    That isn’t Shapiro’s message. It’s just another version of God of the gaps.

    But it would be nice to get beyond the bogus claim that evolutions as currently observed is not capable of innovation.

  2. More to the point, how is evolvability, the production of chunky mutations and rearrangements of working code conceptually different from any other complex function?

    You have just discovered another complexity, except this one is easily reducibility. Evolution by smaller variations is simply slower.

    But it is nice to see ID advocates noticing that perhaps current living things, at least since the Cambrian, have found ways to increase the production of useful variants by shuffling blocks of working code.

    We can perhaps agree that the mystery of the Cambrian explosion has a potential solution?

  3. “Perry Marshall’s hypothesis sounds like a very attractive one. It’s testable,”

    How?

    His algorithm also has the disadvantage that transposition and recombination appear, by all observations I’m aware of, to be random with respect to need, often having deleterious effects.

  4. From Wilkins’ review:

    Finally, with respect to this issue of selection, one might add that, in terms of Jim’s particular thesis, it is hard to understand how cells could have the very capacities for “natural genetic engineering” attributed to them without those capacities having been
    evolved, in some manner and over long evolutionary spans, by natural selection. The evolution of such capabilities, favouring the process of “evolvability” (the capacity to give rise to new properties), is a fascinating subject, mentioned explicitly though only briefly in the book, and deserves more attention than it has traditionally received. Again, the only alternative for the origination of these capabilities, if one discards natural selection as the generative agent, is some supra-natural force, a position that I am certain is not being advocated here.

  5. Something explicitly noted by Shapiro, although he merely says it is impossible to predict need.

    Am I wrong in thinking Shapiro is mainly focused on microbes, where reproduction rates are higher?

    I also suspect that high risk kinds of mutations are likely to be more common in sperm cells, where fatal mutations are less of a threat to reproduction, since only one in hundreds of millions needs to be viable. The “mechanical” reason why mutations would be more common in sperm than in eggs is that they have undergone more replications and are exposed to a more mutagenic environment.

  6. Yep – gene starts, stops and promoters and repressors, and the final nature of the edited transcript, are invisible to mutators of DNA. They would have to ‘know’ the operating system, and the context in the emergent organism. If such a system existed, I would eat Behe’s hat.

  7. I commented on some of this in the earlier thread. I don’t think Shapiro’s view is as un-Darwinian as Shapiro or Wilkins takes it to be. That said, there is some sort of apparently purposeful behavior found in biological systems. Biologists have coined the word “teleonomy” for this, so as to allow them to avoid writing “teleology” in their papers.

    I’m not afraid to use the term “teleology”. However, I see no need for any actual external designer here. It seems to me that it is all explainable as due to naturally occurring homestasis. I explored this last year in a series of posts at my blog.

  8. It seems to me that “teleonomy” is a genuinely useful word, as it captures the notion of function without the baggage of “purpose”.

    Biological machinery clearly serves the function of maintaining the organism and/or the population, whereas human designed machinery is clearly designed by something external to the machinery (us) in order to serve that external agent (us).

    The parallel would be a bacterium designing its own flagellum, which I don’t think anyone – certainly not an IDist, and not Shapiro either – suggests.

    So it seems useful to me to have a separate word. A person designing their own tattoo is a teleological phenomenon; a person benefiting from their inherited capacity to tan in the sun is a teleonomic phenomenon.

  9. It would seem to depend on the degree to which the future can be foreseen in detail. Not whether there is an intelligent agent is around to foresee it, but whether the nature of the dynamic system allows prediction.

    This is not something that can simply be extracted by pure logic. It is something that must be considered on a case by case basis.

    Architects, for example, can foresee many kinds of stresses and events, and can plan and design for them. Things like weather and earthquakes and corrosion have likely ranges of values.

    It is more difficult to predict the future of economic systems in detail, and ecologies are analogous to economic systems. Even if one could solve what seems like the insurmountable of protein and regulatory design in living things, you haven’t predicted need.

    This could be why evolution appears to solve the problem of prediction by trying everything within reach. Quite bluntly, this is what happens in the human financial marketplace, regardless of whether the actors are intelligent and foresightful. Over time former winners get ploughed under and new winners emerge.

  10. 10

    All you’re doing is moving around definitions. Some take the mindless process of variation and selection and try to call it “intelligent.” You’re describing the behavior of purposeful intelligence and looking for a way to reason the intelligence out if it.

    These definitions and words do no good at all.

    Any process that exhibits foresight to combine unrelated components into a system and innovates in anticipation of a future outcome is intelligent or has intelligent input. It goes back to the mechanisms. Can a given mechanism or process do those things or not? It’s entirely irrelevant what we would hypothetically call a process that can hypothetically do such things.

  11. Marshall’s ‘Intelligent Evolution’ model has always struck a wrong cord in me. For it ignores the very same exact major hurdle that neo-Darwinists are ignoring. That of finding novel functional sequences in sequence space. As Chaitin pointed out in his work, the ‘oracle’ in the computer algorithm would have to possess the active information to guide the ‘bottom up’ evolution of increased functionality along its path (which is complete accordance with Dembski-Marks’s work on the conservation of information). In fact it was found for for ‘unlimited evolution’ to be possible, the oracle, in the algorithm, would have to possess ‘infinite information’ in the Chaitin algorithm, per PaV. Exactly where is this huge reservoir of hidden active information stored at in microbes so that ‘Intelligent Evolution’ by ‘Natural Genetic Engineering’ would be plausible??? Thus, though the ‘Intelligent Evolution’, ‘Natural Genetic Engineering’, model may look nice on paper, at the end of the day we are still stuck with the very same exact problem we were at the beginning of it all with the neo-Darwinists; namely, ‘where is the information coming from since it is certainly not coming from natural processes!?!’

    Further up in your article Dr. Torley, this quote by Wilkins caught my eye;

    Again, the only alternative for the origination of these capabilities, if one discards natural selection as the generative agent, is some supra-natural force, a position that I am certain is not being advocated here.

    Though there are many lines of evidence I could cite against ‘Natural Selection’, as any sort of creative force whatsoever, this one particular line of evidence, against Natural Selection, I find particularly devastating;

    “Although living things occupy a three-dimensional space, their internal physiology and anatomy operate as if they were four-dimensional. Quarter-power scaling laws are perhaps as universal and as uniquely biological as the biochemical pathways of metabolism, the structure and function of the genetic code and the process of natural selection.,,, The conclusion here is inescapable, that the driving force for these invariant scaling laws cannot have been natural selection.”
    Jerry Fodor and Massimo Piatelli-Palmarini, What Darwin Got Wrong (London: Profile Books, 2010), p. 78-79

    4-Dimensional Quarter Power Scaling In Biology – video
    http://www.metacafe.com/w/5964041/

    Though Jerry Fodor and Massimo Piatelli-Palmarini rightly find it inexplicable for ‘random’ Natural Selection to be the rational explanation for the invariant scaling of the physiology, and anatomy, of living things to four-dimensional parameters, they do not seem to fully realize the implications this ‘four dimensional scaling’ of living things presents. This 4-D scaling is something we should rightly expect from a Intelligent Design perspective. This is because Intelligent Design holds that ‘higher dimensional transcendent information’ is more foundational to life, and even to the universe itself, than either matter or energy are. This higher dimensional ‘expectation’ for life, from a Intelligent Design perspective, is directly opposed to the expectation of the Darwinian framework, which holds that information, and indeed even the essence of life itself, is merely an ‘emergent’ property of the 3-D material realm.

    And indeed empirical evidence for this ‘higher dimensional information’ expectation from Intelligent Design has been forthcoming. It has recently been found that ‘higher dimensional’, non-local, quantum information/entanglement is what is, in fact, constraining the molecules of the cell to be so far out of thermodynamic equilibrium; Here are some notes to that effect:

    Quantum Information/Entanglement In DNA & Protein Folding – short video
    http://www.metacafe.com/watch/5936605/

    Information and entropy – top-down or bottom-up development in living systems? A.C. McINTOSH
    Excerpt: This paper highlights the distinctive and non-material nature of information and its relationship with matter, energy and natural forces. It is proposed in conclusion that it is the non-material information (transcendent to the matter and energy) that is actually itself constraining the local thermodynamics to be in ordered disequilibrium and with specified raised free energy levels necessary for the molecular and cellular machinery to operate.
    http://journals.witpress.com/paperinfo.asp?pid=420

    Quantum entanglement holds together life’s blueprint – 2010
    Excerpt: When the researchers analysed the DNA without its helical structure, they found that the electron clouds were not entangled. But when they incorporated DNA’s helical structure into the model, they saw that the electron clouds of each base pair became entangled with those of its neighbours. “If you didn’t have entanglement, then DNA would have a simple flat structure, and you would never get the twist that seems to be important to the functioning of DNA,” says team member Vlatko Vedral of the University of Oxford.
    http://neshealthblog.wordpress.....blueprint/

    The relevance of continuous variable entanglement in DNA – July 2010
    Excerpt: We consider a chain of harmonic oscillators with dipole-dipole interaction between nearest neighbours resulting in a van der Waals type bonding. The binding energies between entangled and classically correlated states are compared. We apply our model to DNA. By comparing our model with numerical simulations we conclude that entanglement may play a crucial role in explaining the stability of the DNA double helix.
    http://arxiv.org/abs/1006.4053v1

    Non-local Quantum Action confirmed in DNA by direct empirical research here;

    DNA Can Discern Between Two Quantum States, Research Shows – June 2011
    Excerpt: — DNA — can discern between quantum states known as spin. – The researchers fabricated self-assembling, single layers of DNA attached to a gold substrate. They then exposed the DNA to mixed groups of electrons with both directions of spin. Indeed, the team’s results surpassed expectations: The biological molecules reacted strongly with the electrons carrying one of those spins, and hardly at all with the others. The longer the molecule, the more efficient it was at choosing electrons with the desired spin, while single strands and damaged bits of DNA did not exhibit this property.
    http://www.sciencedaily.com/re.....104014.htm

    Does DNA Have Telepathic Properties?-A Galaxy Insight – 2009
    Excerpt: The recognition of similar sequences in DNA’s chemical subunits, occurs in a way unrecognized by science. There is no known reason why the DNA is able to combine the way it does, and from a current theoretical standpoint this feat should be chemically impossible.
    http://www.dailygalaxy.com/my_.....ave-t.html

    The Real Bioinformatics Revolution – Proteins and Nucleic Acids ‘Singing’ to One Another?
    Excerpt: the molecules send out specific frequencies of electromagnetic waves which not only enable them to ‘see’ and ‘hear’ each other, as both photon and phonon modes exist for electromagnetic waves, but also to influence each other at a distance and become ineluctably drawn to each other if vibrating out of phase (in a complementary way).,,, More than 1,000 proteins from over 30 functional groups have been analysed. Remarkably, the results showed that proteins with the same biological function share a single frequency peak while there is no significant peak in common for proteins with different functions; furthermore the characteristic peak frequency differs for different biological functions.,,, The same results were obtained when regulatory DNA sequences were analysed.
    http://www.i-sis.org.uk/TheRea.....lution.php

    Further notes:

    Falsification Of Neo-Darwinism by Quantum Entanglement/Information
    https://docs.google.com/document/d/1p8AQgqFqiRQwyaF8t1_CKTPQ9duN8FHU9-pV4oBDOVs/edit?hl=en_US

  12. As Chaitin pointed out in his work, the ‘oracle’ in the computer algorithm would have to possess the active information to guide the ‘bottom up’ evolution of increased functionality along its path…

    That is self-evidently wrong. An oracle only needs to compare the functionality to two or more variants. It does not need to know why one is “better” than another, and it does not care if it is moving toward a target.

    This is easily illustrated by the traveling salesman problem, in which one only has to compare the lengths of routes. The does not have to be any advance knowledge of the shortest possible route, nor any knowledge of when the best route is found. Nor does the programmer need to know the answer.

  13. You are simply wrong Petrushka (as usual). Watch the Chaitin video and please quote exactly where and when he says the ‘oracle’ does not have to have advance knowledge of the problem.

  14. That would be difficult because my computer has no speakers attached.

    Tell me what he says.

  15. Petrushka, Dr. Torley has a nice synapses here;

    At last, a Darwinist mathematician tells the truth about evolution
    http://www.uncommondescent.com.....evolution/

    quote of note:

    In Chaitin’s own words, “You’re allowed to ask God or someone to give you the answer to some question where you can’t compute the answer, and the oracle will immediately give you the answer, and you go on ahead.”

    Verses and Music:

    John 15:5
    “I am the vine; you are the branches. If a man remains in me and I in him, he will bear much fruit; apart from me you can do nothing.

    James 1:5
    If any of you lacks wisdom, he should ask God, who gives generously to all without finding fault, and it will be given to him.

    Carrie Underwood – Jesus, Take The Wheel
    http://www.youtube.com/watch?v=lydBPm2KRaU

  16. Regarding your quote of note, I don’t even know what it’s supposed to mean. It isn’t responsive to my post.

  17. Well Petrushka you claimed:

    An oracle only needs to compare the functionality to two or more variants. It does not need to know why one is “better” than another, and it does not care if it is moving toward a target.

    And Chaitin states;

    In Chaitin’s own words, “You’re allowed to ask God or someone to give you the answer to some question where you can’t compute the answer, and the oracle will immediately give you the answer, and you go on ahead.”

    Seems blatantly obvious to me that your claim is completely wrong. But that is par for the course for you. At least you are consistent. :)

  18. Reading the linked post doesn’t clear things up. I think some features of biology can be modeled and others can’t.

    Chemistry can’t be perfectly modelled by any known software, so if you try to claim DNA is a computing system you run into the problem that the programs are not transferable to other media. That’s kind of a show stopper.

    Feel free to cite evidence that there is a theoretical way to predict folding and regulation with enough precision to design living things.

  19. Petrushka, I’m satisfied that you are shown to be wrong in your primary claim. What do I care that you aren’t man enough to admit it but try to change the subject?

  20. OT: Dr. Torley, You ought to get a smile or two out of this:

    Courting rules: how to tell if a woman is a committed Christian – Wintery Knight – January 31, 2012
    http://winteryknight.wordpress.....an-or-not/

  21. More from Chaitin on the prospects of natural evolution:

    This paper advances beyond the previous work on metabiology by proposing a better concept of mutation. Instead of changing, deleting or inserting one or more adjacent bits in a binary program, we now have high-level mutations: we can use an arbitrary algorithm M to map the organism A into the mutated organism A’ = M(A). Furthermore, the probability of the mutation M is now furnished by algorithmic information theory: it depends on the size in bits of the self-delimiting program for M. It is very important that we now have a natural, universal probability distribution on the space of all possible mutations, and that this is such a rich space.

    Using this new notion of mutation, these much more powerful mutations, enables us to accomplish the following:

    * We are now able to show that random evolution will become cumulative and will reach fitness BB(N) in time that grows roughly as N^2, so that random evolution behaves much more like intelligent design than it does like exhaustive search

    * We also have a version of our model in which we can show that hierarchical structure will evolve, a conspicuous feature of biological organisms that previously was beyond our reach.

  22. I’m a bit puzzled why Chaitin thinks his is the first attempt to evolve algorithms. Perhaps the book will be more thorough.

  23. Life as Evolving Software – Chaitin – January 2012
    Excerpt 4.6 Hidden Use of Oracles;
    Just as oracles would be needed to actually fi nd fi tter organisms, they are also necessary because a random mutation may never halt and produce a mutated organism. So to actually apply our random mutations to organisms we would need to use an oracle in order to avoid non-terminating mutations.
    http://www.cs.umaine.edu/~chaitin/darwin.pdf

    also of note from the conclusion of paper:

    The issue of balance between the power of the organisms and the power of the mutations is an important one. In the current version of the theory, both have equal power, but as a matter of aesthetics it would be bad form for
    a proof to overemphasize the mutations at the expense of the organisms. In future versions of the theory perhaps it will be desirable to limit the power of mutations in some manner by at.
    In this connection, note that there are two uses of oracles in this theory, one to decide which of two organisms is tter, and another to eliminate nonterminating mutations. It is perfectly ne for a proof to be based on taking advantage of the oracle for organisms, but taking advantage of the oracle for mutations is questionable.

  24. correction: In this connection, note that there are two uses of oracles in this theory, one to decide which of two organisms is fitter, and another to eliminate nonterminating mutations. It is perfectly fine for a proof to be based on taking advantage of the oracle for organisms, but taking advantage of the oracle for mutations is questionable.

  25. Hi ScottAndrews,

    All you’re doing is moving around definitions. Some take the mindless process of variation and selection and try to call it “intelligent.”

    The problem has always been that ID refuses to provide one canonical definition of the word “intelligent”. Sometimes ID uses the word to describe a specific ability (the ability to generate CSI; Dembski has used this definition). Other times, it means something with conscious experience of foresight (“a conscious rational being” is what Meyer says). Other times, it is equated with some sort of free will (an “ability to choose” that transcends chance and necessity). Still other times, it is just described as some set of general mental abilities (learning, problem solving, etc).

    But if a non-IDer uses the same term in a way that doesn’t suit your purposes, you object: Evolutionary processes are systems that use memory storage and negative feedback to implement a generate-and-test problem solver. Learning and problem solving are certainly important aspects of what we call “intelligence”, so it is perfectly reasonable to call evolution intelligent.

    You may argue that there are other attributes that are required in order for some system to earn the label “intelligent”. But how do you decide which attributes are necessary, and which are sufficient, in order for some system to qualify as being “intelligent”?

    Also, since “intelligence” is the sole explanatory construct of ID theory (it is actually the entire theory in a single word), one would think that the technical definition would have been offered by now, and we wouldn’t have to try and work it out in our comments here.

    You’re describing the behavior of purposeful intelligence and looking for a way to reason the intelligence out if it.

    I think the idea is to understand how it works. Just saying “it’s intelligent” doesn’t actually explain anything.

    These definitions and words do no good at all.

    Words do good when we have shared definitions for them. ID folks resist defining their key term “intelligence”, because once you do, you realize that you have to actually say something specific about what you’re talking about. The word conjures up a rich set of associations in us because of our own mentality, but the term is notoriously difficult to pin down. It turns out that it is like Justic Potter Stewart’s famous definition of pornography: “I know it when I see it!”.

    Any process that exhibits foresight to combine unrelated components into a system and innovates in anticipation of a future outcome is intelligent or has intelligent input. It goes back to the mechanisms. Can a given mechanism or process do those things or not?

    There is no way to answer this question (it is the central question of artificial intelligence) except empirically. Nobody knows the answer yet.

    It’s entirely irrelevant what we would hypothetically call a process that can hypothetically do such things.

    ??? I thought that is what ID is all about – a hypothetical thing that can hypothetically create CSI?

  26. I freely admit to not understating your point.

  27. Petrushka,

    You’re quite right – the claim that evolution couldn’t work in the time available isn’t Shapiro’s message, and I didn’t claim it was. As my post shows, it’s suggested by the work of mathematician Gregory Chaitin, a Darwinist who wants to prove that Darwinism can work.

    Regarding the possibility of innovation: as I argued in my post, It’s all about information, Professor Feser , complex specified information still has to come from somewhere. New structures may appear at certain points in evolutionary history; but the CSI required to generate those structures must have been input at some stage – either long before they appeared (as in front-loading) or at the time when they appeared. I’m quite happy with the idea of the first cell having been originally engineered with the capacity to direct its own evolution, in response to changes in its surroundings. It may also have been designed with a built-in tendency to evolve towards long-term goals billions of years in the future. Right now, the question I’m trying to answer in my own mind is: if the first cell was designed to evolve towards goals in the long-term future, how would it look different (at a biochemical level) from a cell that had merely been designed with a built-in capacity to respond to environmental challenges in its immediate surroundings, with no reference to goals in the distant future?

    If you have any ideas, I’m all ears.

  28. It’s a good question, vjtorley. It’s the one that has to be answered if ID is to make any progress as empirical science.

  29. Please explain that one.

    Q:if the first cell was designed to evolve towards goals in the long-term future, how would it look different (at a biochemical level) from a cell that had merely been designed with a built-in capacity to respond to environmental challenges in its immediate surroundings, with no reference to goals in the distant future?

    It’s a good question, vjtorley. It’s the one that has to be answered if ID is to make any progress as empirical science.

    Why is that?

    I ask because AFAIK the only way to make the determination VJ asks about is by either designer input or unlocking the internal programming- ie figuring out the software (and no, the DNA is not the software).

    And just by getting there we will have made a ton of progress and doing that would be the “creme de la creme”- well no figuring out how to program and download would be…

  30. We can perhaps agree that the mystery of the Cambrian explosion has a potential solution?

    Yes, the solution is design.

  31. Hi rhampton7,

    Thanks for the quote. However, Chaitin adds a caveat at the end of his paper :

    In this connection, note that there are two uses of oracles in this theory, one to decide which of two organisms is be tter, and another to eliminate non-terminating mutations. It is perfectly fine for a proof to be based on taking advantage of the oracle for organisms, but taking advantage of the oracle for mutations is questionable.

    We have by no means presented in this paper a mathematical theory of evolution and biological creativity comme il faut. But at this point in time we believe that metabiology is still a possible contender for such a theory. The ultimate goal must be to find in the Platonic world of mathematical ideas that ideal model of evolution by natural selection which real, messy biological evolution can but approach asymptotically in the limit from below.

    (I see bornagain77 picked up on the same point in his comment below.)

    Rhampton7, regarding your quote from Chaitin about the time taken by random evolution:

    We are now able to show that random evolution will become cumulative and will reach fitness BB(N) in time that grows roughly as N^2, so that random evolution behaves much more like intelligent design than it does like exhaustive search…

    the problem is that N^2 is too long. As Chaitin pointed out in his talk (see http://www.youtube.com/watch?v=RlYS_GiAnK8 ), which I quoted from above,

    if you take something of the order of 10^9 and you square it or you cube it, well … forget it. There isn’t enough time in the history of the Earth… Even though it’s fast theoretically, it’s too slow to work. He [Chaitin's friendly critic] said [to Chaitin], “You really need something more or less linear.”

    Chaitin is talking here about the information in human DNA, which is about 10^9 bits (actually 6 x 10^9). 10^9 squared is 10^18. That’s too many steps for evolution on Earth.

    The history of life on Earth appears to beyond the reach of random variation culled by natural selection. Of that we can be reasonably certain.

  32. Regarding the possibility of innovation: as I argued in my post, It’s all about information, Professor Feser , complex specified information still has to come from somewhere.

    I’m willing to entertain the likelihood that universes could exist in which the “spontaneous” formation of life is impossible. I just don’t think this is one of those universes.

    I also make no claim as to how the properties of this universe arose. It seems to be a question that interests some physicists, but they fall back on possibilities rather than on evidence.

    So I think Denton’s position is logically consistent and rational. I don’t buy in in the sense that I think it’s true, but I think it’s interesting.

    For purely personal reasons I find the concept of frequent intervention philosophically ugly, and the idea that life isn’t an emergent property of our universe only slightly less so.

    I know I pound the nail of the missing ID theory a lot. It annoys a lot of people. But I am fascinated by the idea that it may be impossible to map protein folding to any theory; that each and every coding sequence is unique and its attributes not reducible.

    I fail to see why that isn’t interesting to people who hate reductionism. Imagine a physical reality in which complex things cannot be reduced to some transformation of their components.

    Such a reality would constantly be open to new things under the sun. Contradicting the adage, but enabling actual freedom and actual invention.

    It does not make design impossible, but it means that at some level one cannot foresee the results of change. It also means that change is most likely to follow a path of groping rather than leaping.

  33. “The history of life on Earth appears to beyond the reach of random variation culled by natural selection. Of that we can be reasonably certain.”

    Corrected:

    “The history of life on Earth appears to beyond the reach of random variation via an exhaustive search culled by natural selection. Of that we can be reasonably certain.”

    ID presumes – without evidence – (which current evolutionary theory permits) is that a naturally occurring, random search can be non-exhaustive. Chaitin’s use of oracles in the development of his model does not detract from this point.

    This is what makes Chaitin’s work so potentially damaging to ID theory as currently formulated — all of the probability assessments are based on this flawed assumption.

  34. It seems that you do not understand what is meant by “eliminate nonterminating mutations”

    In Chaitin’s model, the algorithm (a stand-in for a given life form) must be able to be solved in order for its fitness to be tested and its fate to be determined? (a stand-in for natural selection). The mutant algorithms able to solve a problem more efficiently are allowed to reproduce whereas those less efficient become an evolutionary dead-end.

    This requires the algorithm to be able to, eventually, solve itself. Unfortunately some computational problems may be halting incomplete, that is, incapable of ending.

    Now if a computer were to run such a program, it would never be able to advance to the next run in the simulation, much less finish, and thus forcing the operator to terminate the program before results could be obtained. Obviously, that’s unacceptable, hence the oracle. It is tasked to determine which mutations are halting complete – those that aren’t are removed from the simulation, preventing the program from failing.

    So how does Chaitin’s model and its use of an oracle relate to the real world?
    * If an organism dies, then it is halting complete.
    * If an organism reproduces, it is also halting complete.
    * If an organism does not die nor reproduce, then it is halting incomplete.

    In other words, only immortal virgins are deliberately removed from consideration in Chaitin’s model of evolution — which seems to me to be perfectly reasonable “cheat”. Do you have a problem with that?

  35. OK, the “Modern Synthesis” is a p*ss poor batch of hypotheses. They are shamelessly crappy. We all know it. Even Lizzy knows it. But if we stick to materialism it’s all we have.

    God, humans are blind.

    Merry February.

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