“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.
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 →
… 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
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. Continue reading →
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”—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.
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 →
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.
World Scientific is pitchingIntroduction 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.
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.
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 firstname.lastname@example.org if you prefer.) Continue reading →
I am working on a series of tutorials to cover the basics of Intelligent Design, especially the mathematics of it. This is my tutorial on Specified Complexity, and I would appreciate any thoughtful criticism of it. Continue reading →
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 →
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.
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.]
The battle over cumulative selection and Dawkins’ Weasel program has raged on for some months [years?] here at TSZ and across numerous threads. So can it possibly be that we now, finally, have a definitive statement about cumulative selection?
Mung: And whether or not my program demonstrates the power of cumulative selection has not been settled…
To which keiths responded:
keiths: Anyone who understands cumulative selection can see that it doesn’t, because your fitness functions don’t reward proximity to the target — only an exact match. The fitness landscapes are flat except for a spike at the site of the target.
So there you have it. You need a target and a fitness function that rewards proximity to the target.
I was very struck by Glenn Williamson’s [vjt meant GlenDavidson] remark that creativity is not the same thing as complexity. Very deep. Glenn seems to think that people are good at the former, but the blind processes can outdo them in the latter. That’s an interesting view, but I’d want to see evidence that blind processes are actually capable of producing systems with a high degree of functional complexity, of the kind Axe described in his book. Even a computer simulation would be something.
What with all the experts in writing GA’s here at TSZ I was hoping VJT would have elicited more of a response.