Category Archives: Intelligent Design

Evo-Info 3: Evolution is not search

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Introduction to Evolutionary Informatics, by Robert J. Marks II, the “Charles Darwin of Intelligent Design”; William A. Dembski, the “Isaac Newton of Information Theory”; and Winston Ewert, the “Charles Ingram of Active Information.” World Scientific, 332 pages.
Classification: Engineering mathematics. Engineering analysis. (TA347)
Subjects: Evolutionary computation. Information technology–Mathematics.

Marks, Dembski, and Ewert open Chapter 3 by stating the central fallacy of evolutionary informatics: “Evolution is often modeled by as [sic] a search process.” The long and the short of it is that they do not understand the models, and consequently mistake what a modeler does for what an engineer might do when searching for a solution to a given problem. What I hope to convey in this post, primarily by means of graphics, is that fine-tuning a model of evolution, and thereby obtaining an evolutionary process in which a maximally fit individual emerges rapidly, is nothing like informing evolution to search for the best solution to a problem. We consider, specifically, a simulation model presented by Christian apologist David Glass in a paper challenging evolutionary gradualism à la Dawkins. The behavior on exhibit below is qualitatively similar to that of various biological models of evolution.

Animation 1. Parental populations in the first 2000 generations of a run of the Glass model, with parameters (mutation rate .005, population size 500) tuned to speed the first occurrence of maximum fitness (1857 generations, on average), are shown in orange. Offspring are generated in pairs by recombination and mutation of heritable traits of randomly mated parents. The fitness of an individual in the parental population is, loosely, the number of pairs of offspring it is expected to leave. In each generation, the parental population is replaced by surviving offspring. Which of the offspring die is arbitrary. When the model is modified to begin with a maximally fit population, the long-term regime of the resulting process (blue) is the same as for the original process. Rather than seek out maximum fitness, the two evolutionary processes settle into statistical equilibrium.

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Introduction to Evolutionary Informatics

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Introduction to Evolutionary Informatics, by Robert J. Marks II, the “Charles Darwin of Intelligent Design”; William A. Dembski, the “Isaac Newton of Information Theory”; and Winston Ewert, the “Charles Ingram of Active Information.” World Scientific, 332 pages.
Classification: Engineering mathematics. Engineering analysis. (TA347)
Subjects: Evolutionary computation. Information technology–Mathematics.1

Yes, Tom English was right to warn us not to buy the book until the authors establish that their mathematical analysis of search applies to models of evolution.

But some of us have bought (or borrowed) the book nevertheless. As Denyse O’Leary said: It is surprisingly easy to read. I suppose she is right, as long as you do not try to follow their conclusions, but accept it as Gospel truth.

In the thread Who thinks Introduction to Evolutionary Informatics should be on your summer reading list? at Uncommon Descent, there is a list of endorsements – and I have to wonder if everyone who endorsed the book actually read it. “Rigorous and humorous”? Really?

Dembski, Marks, and Ewert will never explain how their work applies to models of evolution. But why not create at list of things which are problematic (or at least strange) with the book itself? Here is a start (partly copied from UD):
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Two planets with life are more miraculous than one

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The Sensuous Curmudgeon, who presently cannot post to his weblog, comments:

This Discoveroid article is amazing. Could Atheism Survive the Discovery of Extraterrestrial Life?. I wish I could make a new post about it. They say that if life is found elsewhere, that too is a miracle, so then you gotta believe in the intelligent designer. They say:

“The probability of life spontaneously self-assembling anywhere in this universe is mind-staggeringly unlikely; essentially zero. If you are so unquestioningly naïve as to believe we just got incredibly lucky, then bless your soul.”

Actually, “they” who posted at Evolution News and Views is someone we all love dearly, and see occasionally in the Zone — that master of arguments from improbability, Kirk Durston.

Is ID really a reasonable alternative to “it just happened”?

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One of our regular commenters explains why they stick with ID:

ID is a perfectly reasonable alternative to “it just happened, that’s all.”

Yet that “reasonable alternative” is just “it happened like that because it was Intelligently Designed“. ID as yet has no specifics as to who, when, what, how, why etc.

So it seems to me that said commenter has just replaced “it just happened” with another phrase that means exactly the same thing but now they can be an intellectually fulfilled theist.  Continue reading →

Evo-Info review: Do not buy the book until…

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Introduction to Evolutionary Informatics, by Robert J. Marks II, the “Charles Darwin of Intelligent Design”; William A. Dembski, the “Isaac Newton of Information Theory”; and Winston Ewert, the “Charles Ingram of Active Information.” World Scientific, 332 pages.
Classification: Engineering mathematics. Engineering analysis. (TA347)
Subjects: Evolutionary computation. Information technology–Mathematics.

… the authors establish that their mathematical analysis of search applies to models of evolution.

I have all sorts of fancy stuff to say about the new book by Marks, Dembski, and Ewert. But I wonder whether I should say anything fancy at all. There is a ginormous flaw in evolutionary informatics, quite easy to see when it’s pointed out to you. The authors develop mathematical analysis of apples, and then apply it to oranges. You need not know what apples and oranges are to see that the authors have got some explaining to do. When applying the analysis to an orange, they must identify their assumptions about apples, and show that the assumptions hold also for the orange. Otherwise the results are meaningless.

The authors have proved that there is “conservation of information” in search for a solution to a problem. I have simplified, generalized, and trivialized their results. I have also explained that their measure of “information” is actually a measure of performance. But I see now that the technical points really do not matter. What matters is that the authors have never identified, let alone justified, the assumptions of the math in their studies of evolutionary models.a They have measured “information” in models, and made a big deal of it because “information” is conserved in search for a solution to a problem. What does search for a solution to a problem have to do with modeling of evolution? Search me. In the absence of a demonstration that their “conservation of information” math applies to a model of evolution, their measurement of “information” means nothing. It especially does not mean that the evolutionary process in the model is intelligently designed by the modeler.1

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Evo-Info sidebar: Conservation of performance in search

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Introduction to Evolutionary Informatics, by Robert J. Marks II, the “Charles Darwin of Intelligent Design”; William A. Dembski, the “Isaac Newton of Information Theory”; and Winston Ewert, the “Charles Ingram of Active Information.” World Scientific, 332 pages.
Classification: Engineering mathematics. Engineering analysis. (TA347)
Subjects: Evolutionary computation. Information technology–Mathematics.

Denyse O’Leary, an advocacy journalist employed by one of the principals of the Center for Evolutionary Informatics, reports that I have essentially retracted the first of my papers on the “no free lunch” theorems for search (1996). What I actually have done in my online copy of the paper, marked “emended and amplified,” is to correct an expository error that Dembski and Marks elevated to “English’s Principle of Conservation of Information” in the first of their publications, “Conservation of Information in Search: Measuring the Cost of Success.” Marks, Dembski, and Ewert have responded, in their new book, by deleting me from the history of “no free lunch.” And the consequence is rather amusing. For now, when explaining conservation of information in terms of no free lunch, they refer over and over to performance.1 It doesn’t take a computer scientist, or even a rocket scientist, to see that they are describing conservation of performance, and calling it conservation of information.

The mathematical results of my paper are correct, though poorly argued. In fact, the theorem I provide is more general than the main theorem of Wolpert and Macready, which was published the following year.2 If you’re going to refer to one of the two theorems as the No Free Lunch Theorem, then it really should be mine. Where I go awry is in the exposition of my results. I mistake a lemma as indicating that conservation of performance in search is due ultimately to conservation of information in search.
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Evolution and Functional Information

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Here, one of my brilliant MD PhD students and I study one of the “information” arguments against evolution. What do you think of our study?

I recently put this preprint in biorxiv. To be clear, this study is not yet peer-reviewed, and I do not want anyone to miss this point. This is an “experiment” too. I’m curious to see if these types of studies are publishable. If they are, you might see more from me. Currently it is under review at a very good journal. So it might actually turn the corner and get out there. An a parallel question: do you think this type of work should be published?

 

I’m curious what the community thinks. I hope it is clear enough for non-experts to follow too. We went to great lengths to make the source code for the simulations available in an easy to read and annotated format. My hope is that a college level student could follow the details. And even if you can’t, you can weigh in on if the scientific community should publish this type of work.

Functional Information and Evolution

http://www.biorxiv.org/content/early/2017/03/06/114132

“Functional Information”—estimated from the mutual information of protein sequence alignments—has been proposed as a reliable way of estimating the number of proteins with a specified function and the consequent difficulty of evolving a new function. The fantastic rarity of functional proteins computed by this approach emboldens some to argue that evolution is impossible. Random searches, it seems, would have no hope of finding new functions. Here, we use simulations to demonstrate that sequence alignments are a poor estimate of functional information. The mutual information of sequence alignments fantastically underestimates of the true number of functional proteins. In addition to functional constraints, mutual information is also strongly influenced by a family’s history, mutational bias, and selection. Regardless, even if functional information could be reliably calculated, it tells us nothing about the difficulty of evolving new functions, because it does not estimate the distance between a new function and existing functions. Moreover, the pervasive observation of multifunctional proteins suggests that functions are actually very close to one another and abundant. Multifunctional proteins would be impossible if the FI argument against evolution were true.

Evo-Info: Publication delayed, supporting materials online

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Introduction to Evolutionary Informatics, by Robert J. Marks II, the “Charles Darwin of Intelligent Design”; William A. Dembski, the “Isaac Newton of Information Theory”; and Winston Ewert, the “Charles Ingram of Active Information.” World Scientific, 350 pages. Jan 31 May 1, 2017.
Classification: Engineering mathematics. Engineering analysis. (TA347)
Subjects: Evolutionary computation. Information technology–Mathematics.

I cannot tell you exactly what will be in the forthcoming book by Marks, Dembski, and Ewert. I made it clear in Evo-Info 1 and Evo-Info 2 that I was responding primarily to technical papers on which the book is based. With publication delayed once again, I worry that the authors will revise the manuscript to deflect my criticisms. Thus I’m going to focus for a while on the recent contributions to the “evolutionary informatics” strain of creationism by George D. Montañez, a former advisee of Marks who is presently a doctoral candidate in machine learning at Carnegie Mellon University (advisor: Cosma Shalizi). My advice for George is that if he wants not to taken for a duck, then he had better not walk like a duck and swim like a duck and quack like a duck. Continue reading →

Poker as a Proxy Turing Test

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I found the recent contest in which an algorithm was able to successfully defeat four professional poker players in a particular version of poker to be very interesting.

What strikes me is not the fact that the algorithm was successful but the way in which it accomplished the task.

check this out it’s all interesting but pay close attention from about the 8 minute mark

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Evo-Info 2: Teaser for algorithmic specified complexity

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Introduction to Evolutionary Informatics, by Robert J. Marks II, the “Charles Darwin of Intelligent Design”; William A. Dembski, the “Isaac Newton of Information Theory”; and Winston Ewert, the “Charles Ingram of Active Information.” World Scientific, 350 pages. January 30, 2017.
Classification: Engineering mathematics. Engineering analysis. (TA347)
Subjects: Evolutionary computation. Information technology–Mathematics.

The introduction to this series ended with a promise of insights into evolutionary informatics that the forthcoming book by Marks, Dembski, and Ewert is unlikely to afford. There will be little doubt at the end of the fourth installment that I have delivered the goods. First I want to assure you that, although I subscribe to the philosophy “Into Each Life, Some Math Must Fall,” the downpour of abstract notions, Greek letters, and squiggly marks will be intermittent, not unrelenting.

1280pxFujRusSunset in the Garden of Id

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Evo-Info 1: Engineering analysis construed as metaphysics

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Introduction to Evolutionary Informatics, by Robert J. Marks II, the “Charles Darwin of Intelligent Design”; William A. Dembski, the “Isaac Newton of Information Theory”; and Winston Ewert, the “Charles Ingram of Active Information.” World Scientific, 350 pages. January 30, 2017.
Classification: Engineering mathematics. Engineering analysis. (TA347)
Subjects: Evolutionary computation. Information technology–Mathematics.

World Scientific is pitching Introduction to Evolutionary Informatics, by Robert Marks, William Dembski, and Winston Ewert, to a general readership, but with particular note of enthusiasts of apologetics. The book features the Conservation of Information Theorem, which was the centerpiece of Dembski’s religio-philosophical treatise Being as Communion: A Metaphysics of Information (2014). So there is no denying that the authors regard their mathematical arguments as support for their religious views. And there is no great surprise in learning that the nonprofit Center for Evolutionary Informatics, operated by Marks and Dembski, has the alternate name Arbor Ministries in public records. The forthcoming book includes a section titled “The Genesis,” and this leads me to hope that the authors, mindful of the canonical teachings of Jesus, have made a clear statement of faith.

No one lights a lamp and hides it in a clay jar or puts it under a bed. Instead, they put it on a stand, so that those who come in can see the light. For there is nothing hidden that will not be disclosed, and nothing concealed that will not be known or brought out into the open. Therefore consider carefully how you listen. Whoever has will be given more; whoever does not have, even what they think they have will be taken from them.

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Chesil Beach is high in algorithmic specified complexity

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Winston Ewert, William A. Dembski, and Robert J. Marks II rebranded specified complexity as a measure of meaningful information, at the Engineering and Metaphysics 2012 Conference. In my mind, that was quite a remarkable event in the history of the “intelligent design” (ID) offshoot of “creation science” — particularly in light of the fact that Dembski and Marks changed the meaning of information in the Law of Conservation of Information from specified complexity to active information, back in 2008. But the organizer of that conference, Jonathan Bartlett, seems not to have noticed. He recently undertook to explain algorithmic specified complexity to the unwashed masses, but made no mention at all of meaning.

Jonathan approves of my observation, posted here in The Skeptical Zone, that the “conga lines” formed by hermit crabs are high in algorithmic specified complexity (emphasis added):

Tom English asked about Hermit Crabs forming a line. I agree that this exhibits high ASC for certain things (remember, ASC depends on what you are comparing it to). It gives a high ASC for the line compared to the hermit crabs just walking around. That seems like a success, not a fail, as you have successfully determined that they are lined up intentionally. Even though you don’t have all of the prerequisites for a design inference (at least in your post here), you have at least shown that intentionality on behalf of the hermit crabs is a live possibility. Since they are lining up for a particular purpose, that seems to line up with reality.

He has not responded to my main point (emphasis in original):

Distinguishable entities operating identically by simple rules can form structures high in specified complexity. That is, the crabs in the video differ in size, but not in the “program” they execute. Want more specified complexity? Just add crabs.

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Take the Evolutionary Turing Test!

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The challenge, for all and sundry but especially for “Darwin doubters”, should you wish to take it, is to submit a one-paragraph summary of the theory of evolution. The idea is to see if you understand it well enough to fairly summarize the theory so that you pass as a proponent of evolution. We also need some examples from proponents to test the null hypothesis!

To ensure anonymity, please submit your paragraph by private message to me or another admin and we will add it in edit. (Or email it to me at alanfox@free.fr if you prefer.) Continue reading →

An Intelligent Design Turing Test

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This is an open challenge to all and sundry!

Can anyone represent the views of someone he disagrees with well enough to pass the “Turing Test” and be mistaken for a real proponent of those views? Barry Arrington has recently issued this challenge for skeptics of “Intelligent Design”. He seems to have overlooked the point that the test should be anonymous and also that most remaining active ID skeptics are unable or unwilling (or both, in my case) to participate at “Uncommon descent”. Continue reading →

Dice Entropy – A Programming Challenge

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Given the importance of information theory to some intelligent design arguments I thought it might be nice to have a toolkit of some basic functions related to the sorts of calculations associated with information theory, regardless of which side of the debate one is on.

What would those functions consist of?

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Active information defined… for the fourth time in nine years?

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Yesterday, a couple of folks let me know of a paper that crypto-creationist [ETA: perhaps under reform] George Montañez had just posted at arXiv, “The Famine of Forte: Few Search Problems Greatly Favor Your Algorithm.” Below you’ll find my response to one of them. I should explain a few things, by way of introduction.

Montañez is a former advisee of the “Charles Darwin of intelligent design,” Baylor University professor Robert J. Marks II. Last I heard, he was pursuing doctoral studies in machine learning at Carnegie Mellon University. He worked not only with Marks, but also with William A. Dembski, the “Isaac Newton of information theory,” and Winston Ewert, the “Pooh Bear of evolutionary informatics,” on applications of measures of active information. He is still affiliated with them at the Evolutionary Informatics Lab. I refer to the core of affiliates who actually contribute to the output of the Lab — Marks, Dembski, Ewert, and Montañez — as Team EIL. The first three of them have a book scheduled for release by World Scientific on January 30, 2017. The title is Introduction to Evolutionary Informatics. I am trying to pull together a series of posts with the same title.

My email note follows.

[ETA: George Montañez has kindly responded here at TSZ. Contrary to what I guess below, he is not presently collaborating with the authors of the book.]

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