Category Archives: Evolution

More on Marks, Dembski, and No Free Lunch, by Tom English

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Tom English has a great post at his blog, Bounded Science, which I have his permission to cross post here:

Bob Marks grossly misunderstands “no free lunch”

And so does Bill Dembski. But it is Marks who, in a “Darwin or Design?” interview, reveals plainly the fallacy at the core of his and Dembski’s notion of “active information.” (He gets going at 7:50. To select a time, it’s best to put the player in full-screen mode. I’ve corrected slips of the tongue in my transcript.)

[The “no free lunch” theorem of Wolpert and Macready] said that with a lack of any knowledge about anything, that one search was as good as any other search. [14:15]And what Wolpert and Macready said was, my goodness, none of these [“search”] algorithms work as well as [better than] any other one, on the average, if you have no idea what you’re doing. And so the question is… and what we’ve done here is, if indeed that is true, and an algorithm works, then that means information has been added to the search. And what we’ve been able to do is take this baseline, that all searches are the same, and we’ve been able to, in cases where searches work, measure the information that is placed into the algorithm in bits. And we have looked at some of the evolutionary algorithms, and we found out that, strikingly, they are not responsible for any creation of information. [14:40]

And according to “no free lunch” theorems, astonishingly, any search, without information about the problem that you’re looking for, will operate at the same level as blind search.” And that’s… It’s a mind-boggling result. [28:10]

Bob has read into the “no free lunch” (NFL) theorem what he believed in the first place, namely that if something works, it must have been designed to do so. Although he gets off to a good start by referring to the subjective state of the practitioner (“with a lack of knowledge,” “if you have no idea what you’re doing”), he errs catastrophically by making a claim about the objective state of affairs (“one search is as good as any other search,” “all searches are the same”).

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Natural Selection- What is it and what does it do?

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Well let’s look at what natural selection is-

 “Natural selection is the result of differences in survival and reproduction among individuals of a population that vary in one or more heritable traits.” Page 11 “Biology: Concepts and Applications” Starr fifth edition

“Natural selection is the simple result of variation, differential reproduction, and heredity—it is mindless and mechanistic.” UBerkley

“Natural selection is the blind watchmaker, blind because it does not see ahead, does not plan consequences, has no purpose in view.” Dawkins in “The Blind Watchmaker”?

“Natural selection is therefore a result of three processes, as first described by Darwin:

Variation
Inheritance
Fecundity

which together result in non-random, unequal survival and reproduction of individuals, which results in changes in the phenotypes present in populations of organisms over time.”- Allen McNeill prof. introductory biology and evolution at Cornell University

OK so it is a result of three processes- ie an output. But is it really non-random as Allen said? Nope, whatever survives to reproduce survives to reproduce. And that can be any number of variations taht exist in a population.

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Intention and action

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The subject of intention and action has come up few times, so I thought I’d start a thread.

From my point of view as a cognitive neuroscientist,  decision-making (which action to take) is best conceived of as a kind of winner-take-all arm-wrestling competition, in which competing programs (represented as networks of active neurons) of action exert a mutually inhibitory effect on on the other, while each receives excitatory input from various other other networks, each of which in turn are engaged in a kind of subsidiary arm-wrestling match with some networks and a mutually cheer-leading match with others.

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No Free Lunch

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My husband, mother, father, myself, and my four-year-old son were going out for a walk.  It was raining. My son refused (as usual) to wear his raincoat.  Instead, he carried a cup, which he held out in front of him.  He argued that he was going to catch the rain drops in the cup so that by the time he got to the place the raindrops had been, they’d be in the cup and he’d be dry. Half an hour later, four adults were still standing around, drawing diagrams on the backs of envelopes, arguing about Pythagoras and trigonometry, all to no avail.  We went out, with cup, sans rain coat.  My son got wet.  He insisted he remained dry.

Bryce Canyon, Utah.

I’ve got as far as Chapter 5 of Dembski’s book No Free Lunch, the chapter called Evolutionary Algorithms, and about which he says in his Preface: “This chapter is the climax of the book”.  He claims that in it he shows that “An elementary combinatorial analysis shows that evolutionary algorithms can no more generate specified complexity than can five letters fill ten mailboxes.”

I think he’s making the same kind of error as my son made.

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Intelligence and Design.

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My copy of No Free Lunch arrived a few days ago, and there are a couple of posts I want to make about it, but the first thing that struck me, reading the preface, and not for the first time, is how little Dembski (and other Intelligent Design proponents) seem to know about either Intelligence or Design.

As it happens, I have a relevant background in both.  I’m a cognitive scientist, and I came into cognitive science from a background in educational psychology, so I’ve always been interested in intelligence – how it works, how it is measured, what factors affect it, etc.  And, somewhat unusually for a cognitive scientist, I also have a training in design – I trained as an architect, a design training that is specifically focussed on “problem solving”, but I also applied that training to other “design” modalities, including composing music, and writing children’s books that attempted to explain something, both to commission, and therefore with a “design brief”.

And in both areas, what is abundantly clear, is that learning is critical.

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Creating CSI with NS

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Imagine a coin-tossing game.  On each turn, players toss a fair coin 500 times.  As they do so, they record all runs of heads, so that if they toss H T T H H H T H T T H H H H T T T, they will record: 1, 3, 1, 4, representing the number of heads in each run.

At the end of each round, each player computes the product of their runs-of-heads.  The person with the highest product wins.

In addition, there is a House jackpot.  Any person whose product exceeds 1060 wins the House jackpot.

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Dembski’s CSI

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(5th April, 2013: stickying this, for a bit, as it has come up.  Mung might like to comment).

Time to look at this in detail, I think 🙂

His definitive paper to date on CSI, is Specification: The Pattern That
Signifies Intelligence. It is very clearly written, not very mathy, but, by the same token, a paper in which it is easy (IMO) to see where he goes wrong.

Here is the abstract:

ABSTRACT: Specification denotes the type of pattern that highly improbable events must exhibit before one is entitled to attribute them to intelligence. This paper analyzes the concept of specification and shows how it applies to design detection (i.e., the detection of intelligence on the basis of circumstantial evidence). Always in the background throughout this discussion is the fundamental question of Intelligent Design (ID): Can objects, even if nothing is known about how they arose, exhibit features that reliably signal the action of an intelligent cause? This paper reviews, clarifies, and extends previous work on specification in my books The Design Inference and No Free Lunch.

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“Tiktaalik”, Why it is a failed Prediction

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Tiktaalik is still being used as a successful prediction of something. I know it was supposed to be a successful prediction of universal common descent because it is A) Allegedly a transitional form between fish and tetrapods and B) It was found in the “correct” strata because allegedly no evidence of tetrapods before 385 million years ago- plenty of fish though and plenty of evidence for tetrapods around 365 million years ago- Tiktaalik was allegedly found in strata about 375 million years old- Shubin said that is the strata he looked in because of the 365-385 range already bracketed by existing data.

The thinking was tetrapods existed 365 mya and fish existed 385 mya, so the transition happened sometime in that 20 million years.

Sounds very reasonable. And when they looked they found Tiktaalik and all was good.

Then along comes another find that put the earliest tetrapods back to over 390 million years ago.

Now had this find preceded Tiktaalik then Shubin et al. would not have been looking for the transitional after the transition had occurred- that doesn’t make any sense. And that is why it is a failed prediction- the transition occurred some 25 million years before, Shubin et al., were looking in the wrong strata.

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Functional information and the emergence of biocomplexity

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Journal club time again 🙂

I like this paper: Functional information and the emergence of biocomplexity by Hazen et al, 2007 in PNAS, and which I hadn’t been aware of.

I’ve only had time to skim it so far, but as it seems to be an interesting treatment of the concepts variously referred to by ID proponents as CSI, dFCSI, etc, I thought it might be useful.  It is also written with reference to AVIDA.  Here is the abstract:

Complex emergent systems of many interacting components, including complex biological systems, have the potential to perform quantifiable functions. Accordingly, we define “functional information,” I(Ex ), as a measure of system complexity. For a given system and function, x (e.g., a folded RNA sequence that binds to GTP), and degree of function, Ex (e.g., the RNA–GTP binding energy), I(Ex ) = −log2[F(E x)], where F(Ex ) is the fraction of all possible configurations of the system that possess a degree of function ≥ Ex . Functional information, which we illustrate with letter sequences, artificial life, and biopolymers, thus represents the probability that an arbitrary configuration of a system will achieve a specific function to a specified degree. In each case we observe evidence for several distinct solutions with different maximum degrees of function, features that lead to steps in plots of information versus degree of function.

I thought it would be interesting to look at following the thread on Abel’s paper.  I’d certainly be interested in hearing what our ID contributors make of it 🙂

 

Intelligent Design is NOT Anti-Evolution

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Thank you Elizabeth for this opportunity-

Good day- Over the past many, many years, IDists have been telling people that intelligent design is not anti-evolution. Most people understand and accept that, while others just refuse to, no matter what.

With that said, in this post I will provide the evidence (again) that firmly demonstrates that ID is not anti-evolution. I will be presenting several authoritative definitions of “evolution” followed by what the ID leadership has to say about evolution. So without any further adieu, I give you-

Intelligent Design is NOT Anti-Evolution

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Why Methodological Naturalism is a Questionable Philosophy of Science

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Elizabeth started another thread (http://theskepticalzone.fr/?p=256) stating that methodological naturalism (MN) “underlies the methodology that we call science.” Later she spoke of “methodological naturalism, as in the working assumption that scientists make about the world in order to predict things.” Then she quoted Wikipedia, which states: “all scientific endeavors—all hypotheses and events—are to be explained and tested by reference to natural causes and events,” adding that this is “more or less the definition I have been assuming.” In other words, science studies ‘nature-only’ because it is naturalistic – it sees nothing other than nature that *could* be studied. Elizabeth sticks with this definition when she says “Science occupies the domain of natural explanations.”

Still later, Elizabeth admitted she is ‘not wild about’ MN (or what I suggested as more accurate of her statements: science applies ‘methodological probabilism’) and also that “‘methodological naturalism’ is a poor term.” Thus, her concession: “now that I realise that the term [MN] appears to denote different things to different people, I will avoid it.” So, the main argument in the OP was deserted.

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Why I find ID fallacious

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Note that I do not say “wrong”.  I don’t think ID is wrong.  I do think that it is not falsifiable.

That is not in itself a problem.  I’d argue that most theories are unfalsiable.  What are falsifiable are the predictive hypotheses we derive from our theories.

So I’ll go out on a limb and say that neither evolutionary theory nor ID are, in themselves, falsifiable.  However, evolutionary theory generates lots of testable hypotheses.  Many of these have proved confirmatory; some have delivered surprises, and as a result, the theory has had to change.  This is a good thing.

In contrast, I would argue, that ID generates very few hypotheses, one exception being “front-loading”, and this remains rudimentary, and, AFAIK, untested.

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Good arguments and straw men

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We seem to have quite a number of posters here who are happy to defend  ID, as well as a number (myself included) who are happy to defend evolutionary theory.

I’m posting this as a kind of straw poll for people to state what they think the major claim of their own position is, and why they find it persuasive; and also what they think the major claim of the opposite position is, and why (if they do) they find it flawed.

It might be interesting to count the straw men standing by the end 🙂  More to the point, it might stop us talking past each other quite so much, and perhaps understand the other side’s position a little more.

Full disclosure: I don’t think myself that the two positions are symmetrical.  But I am constantly brought upn short by the realisation that ID proponents also perceive an assymmetry, but see it as the mirror image of mine.  So I wait enlightenment 🙂

Coyne vs Shapiro

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Interesting exchange between Jerry Coyne and James Shapiro at Coyne’s blog, Why Evolution is true: A colleague wrongfully disses modern evolutionary theory.

(Hat tip to news at Uncommon Descent)

I’ve only skimmed Coyne’s piece and Shapiro’s response so far, but it seems to me that they are talking past each other to some extent.  And Coyne says something silly about cats and dogs.

Have at it.  Gotta run.