Philosopher Thomas Nagel has been getting a lot of ink these days, pro and con, for trying to rescue serious traditional atheism from the materialist dump site (in which we all evolved so that we would not believe in materialism—which is really true anyhow—so, go figure … ).

So who is Thomas Nagel and why should we care? Nagel is best known for his famous essay, “What is it like to be a bat?”, in which he acknowledges the limits of human understanding of animal minds. What is less well known is that he named Steve Meyer’s ID-friendly Signature in the Cell (Harper One) a Book of the Year for 2009, for raising key issues. After questioning whether the human intellect is explicable on Darwinian principles, he went on to publish Mind & Cosmos: Why the Materialist Neo-Darwinian Conception of Nature is Almost Certainly False (Oxford University Press: 2013). He is one of the most significant defectors from Darwinism to date. Yet he says, “I don’t want there to be a God; I don’t want the universe to be like that.”*

Reviewer Terry Scambray thinks Nagel is on to something, but that no accommodation with materialism really works:

Nagel’s probes or “speculations,” the word he consistently uses, are characteristic of the style of much of the book which is sketchy when it isn’t down right contradictory.

For example, while he trashes Darwinian natural selection as a phony explanation for how minds were made, nonetheless, he continues to believe that natural selection has explanatory power. And though he correctly understands that a materialist explanation of mind destroys any notion of “values” while skewing even the baked-in imperatives of logic, nonetheless, he sees Darwinian evolution as the only credible support for materialistic solutions to all the big issues, including the mind problem.

And while he is grateful to individuals like Michael Behe and Stephen Meyer for showing the weaknesses in evolutionary explanations, Nagel notes that they both “are motivated at least in part by their religious beliefs.” And whereas David Berlinski is also given a pat on the head for dissecting Darwin’s theory without having ulterior “religious” motives, he is also commended for refraining from advocating design.

Apparently Dr. Nagel, wants to have his cake and eat it too. Read, for example, this sentence: “Those who have seriously criticized these arguments have certainly shown that there are ways to resist the design conclusion; but the general force of the negative part of the intelligent design position—skepticism about the likelihood of the orthodox reductive view, given the available evidence—does not appear to me to have been destroyed in these exchanges.”

Hard to track ? More.

Hard to track? Hard to say. Nagel’s biggest problem is probably to hold off Darwin’s thugs, which even the great Karl Popper was unable to do.
These days, only a person who just does not care what some government’s tagged herd is currently fed can afford to really genuinely doubt Darwin or any key materialist hero.

See also:

Movies: The History of the World in Two Hours and, oh, on two legs …

Where human uniqueness apparently does NOT lie …

Linguist: What we can and can’t learn about vanished languages, and how

Can we really identify words that have come down to us from 10,000 years ago?

* Thomas Nagel, The Last Word (Oxford University Press: 1997), pp. 130-131: http://tinyurl.com/4yh27e5

Steve Fuller explains here:

First, whether or not the ‘Darwinian paradigm’ is crumbling depends on what the next generation thinks and does. As long as the paradigm retains its current levels of control over who and what passes as ‘scientific’, I see little prospect for change. I doubt that any particular piece of evidence will change minds by itself. One should not underestimate the amount of bigotry against Christianity at work here, albeit in the relatively unself-conscious way that in the past had been associated with anti-Semitism. (I am especially struck by how self-regarding ‘liberals’ are quick to bring up how the supposed financial might of ID people distorts scientific discourse.) What is required for the sort of change that Meyer would like to see is a more systemic disillusionment with the scientific establishment in terms of its failure to live up to its own ideals. My guess is that this is more likely to help ID’s fortunes than any new research, which can always be spun in multiple ways.

More.

Note: A UD news writer (Denyse O’Leary)* remembers encountering an atheist professor in Toronto at the TVO station at Eglinton & Yonge some years ago. The prof swore that the ID-promoting Discovery Institute had scads of money. News writer, as it happened, had visited their office in 2007. The DI crowd were a great bunch, but their office was the usual not-for-profit dump in what was (or should be) a low rent neighbourhood. (They’ve since moved, but from what I hear, the new digs aren’t that much better.)

So their luxury yachts must be anchored off their private islands somewhere …

PS: UD News* operates at least one division from somewhere near a cell tower somewhere in Canada, which narrows things down a lot.  ;)

Original Big Bang theorist, priest

We’re not doing this just because it makes atheists mad. Honest. It’s instructive:

Atheists are just as likely as anyone to resist research findings that challenge their views. Here’s the romp in four short posts:

The “I hate the Big Bang” Cosmology Club

Cosmologist Christopher Isham:

Perhaps the best argument in favor of the thesis that the Big Bang supports theism is the obvious unease with which it is greeted by some atheist physicists.

Still under construction: A No Big Bang Universe

Stephen Hawking has been arguing against the Big Bang at recent public appearances, and has himself proposed various alternatives. (He has also made his atheist leanings quite clear in recent years.)

The Big Bang: Are the fireworks still on despite the downpour?

The Big Bang is not direct proof of God’s existence, but if God exists and did create the universe, we might expect something like that. And something like the ensuing reaction of world-famous atheists in science as well. They have put a great deal of effort into developing alternative models that would point away from God. The problem is that for sixty years and more, the evidence has favored the Big Bang.

Manufacturing doubts about the Big Bang

Here’s a sample from the news desk of Nature, which gives some idea of the available no-Big Bang fare in the light of recent results from particle physics: In “Higgs data could spell trouble for leading Big Bang theory,” we learn first that the most recent research, as of March of this year in fact, “was seen as in line, for the most part, with the standard theory of cosmology” (the Big Bang). That’s probably why we didn’t hear much about it.

But, we are also told, “a controversial analysis,” putting together different data streams, “paints the prevailing theory in a dim light.” That striking news deflates, a paragraph later, to the fact that a paper was posted the previous week by an astronomer who “is no novice when it comes to making controversial cosmic claims.”

In Illustra Media’s Darwin’s Dilemma, there is a clip on proteins as islands of function in amino acid sequence space:

[There is a video that cannot be displayed in this feed. Visit the blog entry to see the video.]

Food for thought.

As a stimulus to such, let us next note how the bloggist Wintery Knight has given an interesting summary of the challenges involved if a chance-dominated process is invoked for a hypothetical 100-AA polypeptide:

Let’s calculate the odds of building a protein composed of a functional chain of 100 amino acids, by chance. (Think of a meaningful English sentence built with 100 scrabble letters, held together with glue)

Sub-problems:

• BONDING: You need 99 peptide bonds between the 100 amino acids. The odds of getting a peptide bond is 50%. The probability of building a chain of one hundred amino acids in which all linkages involve peptide bonds is roughly (1/2)^99 or 1 chance in 10^30.
• CHIRALITY: You need 100 left-handed amino acids. The odds of getting a left-handed amino acid is 50%. The probability of attaining at random only L–amino acids in a hypothetical peptide chain one hundred amino acids long is (1/2)^100 or again roughly 1 chance in 10^30.
• SEQUENCE: You need to choose the correct amino acid for each of the 100 links. The odds of getting the right one are 1 in 20. Even if you allow for some variation, the odds of getting a functional sequence is (1/20)^100 or 1 in 10^65.

The final probability of getting a functional protein composed of 100 amino acids is 1 in 10^125. Even if you fill the universe with pre-biotic soup, and react amino acids at Planck time (very fast!) for 14 billion years, you are probably not going to get even 1 such protein. And you need at least 100 of them for minimal life functions, plus DNA and RNA.

But, some will object, it’s not just chance involved!

That is, they are appealing to self-organisation and/or mechanical necessity, or incremental complexification — a sort of pre-life evolution.

Especially, with RNA acting as a catalyst and potential information store.

Mechanical necessity, a forced sequence of bonds, is both counter to what we know of the chemistry of both AA and D/RNA chaining, and would undermine the flexibility of sequence required. Templating, in which a clay bed or the like would force the sequence only displaces the informational specificity one step back.

And while pebbles on Chesil Beach are sorted by size along the beach and while similar self-ordering phenomena for instance explain hurricanes and the hexagonal polar cloud ring on one of our gas giant planets, that is not even comparable to the functional and aperiodic, non sorted sequence chaining we need for the information-rich polymers of life.

Functional sequence specificity simply is not explained by forces of order or of randomness, once we have to deal with relevantly complex sequences and organised clusters of hundreds or thousands of molecules required to achieve cellular function.

They don’t even plot to the same zones on a graph of random, ordered and functional sequence complexity, as Trevors and Abel remind us from 2005:

No wonder, the making of proteins in the cell is such a meticulous, organised step by step process:

The step-by-step process of protein synthesis, controlled by the digital (= discrete state) information stored in DNA

Zooming in on the ribosome:

Step by step protein synthesis in action, in the ribosome, based on the sequence of codes in the mRNA control tape (Courtesy, Wikipedia and LadyofHats)

Let us remind ourselves: cells are gated, encapsulated, metabolic automata with self maintenance, responsiveness to environment and a code based self replication. As Mignea summed up in the context of requisites for a minimally functional, self-replicating cell:

Fig. A: Mignea’s schematic of the requisites of kinematic self-replication, showing duplication and arrangement then separation into daughter automata. This requires stored algorithmic procedures, descriptions sufficient to construct components, means to execute instructions, materials handling, controlled energy flows, wastes disposal and more. (Source: Mignea, 2012, slide show; fair use.

That means, there is a stiff irreducible complexity threshold involved, which locks out incrementalist solutions, as we confront Menuge’s criteria C1 – 5 to get incrementally additive cobbling together (NB: Menuge set these in the context of the flagellum, but the challenge is much broader in relevance as anyone struggling to get a rare car part can tell us):

For a working [bacterial] flagellum to be built by exaptation, the five following conditions would all have to be met:

C1: Availability. Among the parts available for recruitment to form the flagellum, there would need to be ones capable of performing the highly specialized tasks of paddle, rotor, and motor, even though all of these items serve some other function or no function.

C2: Synchronization. The availability of these parts would have to be synchronized so that at some point, either individually or in combination, they are all available at the same time.

C3: Localization. The selected parts must all be made available at the same ‘construction site,’ perhaps not simultaneously but certainly at the time they are needed.

C4: Coordination. The parts must be coordinated in just the right way: even if all of the parts of a flagellum are available at the right time, it is clear that the majority of ways of assembling them will be non-functional or irrelevant.

C5: Interface compatibility. The parts must be mutually compatible, that is, ‘well-matched’ and capable of properly ‘interacting’: even if a paddle, rotor, and motor are put together in the right order, they also need to interface correctly.

( Agents Under Fire: Materialism and the Rationality of Science, pgs. 104-105 (Rowman & Littlefield, 2004). HT: ENV.)

No wonder, then, that a few years back, Berlinsky commented:

At the conclusion of a long essay, it is customary to summarize what has been learned. In the present case, I suspect it would be more prudent to recall how much has been assumed:

First, that the pre-biotic atmosphere was chemically reductive; second, that nature found a way to synthesize cytosine; third, that nature also found a way to synthesize ribose; fourth, that nature found the means to assemble nucleotides into polynucleotides; fifth, that nature discovered a self-replicating molecule; and sixth, that having done all that, nature promoted a self-replicating molecule into a full system of coded chemistry.

These assumptions are not only vexing but progressively so, ending in a serious impediment to thought. That, indeed, may be why a number of biologists have lately reported a weakening of their commitment to the RNA world altogether, and a desire to look elsewhere for an explanation of the emergence of life on earth. “It’s part of a quiet paradigm revolution going on in biology,” the biophysicist Harold Morowitz put it in an interview in New Scientist, “in which the radical randomness of Darwinism is being replaced by a much more scientific law-regulated emergence of life.”

Morowitz is not a man inclined to wait for the details to accumulate before reorganizing the vista of modern biology. In a series of articles, he has argued for a global vision based on the biochemistry of living systems rather than on their molecular biology or on Darwinian adaptations. His vision treats the living system as more fundamental than its particular species, claiming to represent the “universal and deterministic features of any system of chemical interactions based on a water-covered but rocky planet such as ours.”

This view of things – metabolism first, as it is often called – is not only intriguing in itself but is enhanced by a firm commitment to chemistry and to “the model for what science should be.” It has been argued with great vigor by Morowitz and others. It represents an alternative to the RNA world. It is a work in progress, and it may well be right. Nonetheless, it suffers from one outstanding defect. There is as yet no evidence that it is true . . .

Origin of life is the root of the tree of life, and so that is the decisive issue:

The Smithsonian’s tree of life model, note the root in OOL

No roots, no tree.

And, on blind watchmaker mechanisms, there is no good reason to expect a root to form.

Where also, there is one reliably known adequate causal source for functionally specific complex organisation and/or associated information (FSCO/I).

Design.

Which is in the main being disregarded on a priori ideological grounds such as Lewontin so tellingly documented:

. . . It is not that the methods and institutions of science somehow compel us to accept a material explanation of the phenomenal world, but, on the contrary, that we are forced by our a priori adherence to material causes to create an apparatus of investigation and a set of concepts that produce material explanations, no matter how counter-intuitive, no matter how mystifying to the uninitiated . . . [["Billions and billions of demons," NYRB, Jan 1997. (If you imagine this is quote-mining, as a common how dare you cite that talking point alleges, cf. the fuller cite and notes here.)]

No wonder ID thinker Philip Johnson replied:

For scientific materialists the materialism comes first; the science comes thereafter. [[Emphasis original] We might more accurately term them “materialists employing science.” And if materialism is true, then some materialistic theory of evolution has to be true simply as a matter of logical deduction, regardless of the evidence. That theory will necessarily be at least roughly like neo-Darwinism, in that it will have to involve some combination of random changes and law-like processes capable of producing complicated organisms that (in Dawkins’ words) “give the appearance of having been designed for a purpose.”

. . . .   The debate about creation and evolution is not deadlocked . . . Biblical literalism is not the issue. The issue is whether materialism and rationality are the same thing. Darwinism is based on an a priori commitment to materialism, not on a philosophically neutral assessment of the evidence. Separate the philosophy from the science, and the proud tower collapses. [[Emphasis added.] [[The Unraveling of Scientific Materialism, First Things, 77 (Nov. 1997), pp. 22 – 25.]

There is no good reason why design is not sitting at the table as a serious explanatory candidate for the FSCO/I in first cell based life, and therefore also, in explaining the origin of major body plans. Motive mongering games and dismissive remarks notwithstanding.

In short, it is time for a serious re-think on the science of origins. END

There are two versions of the metric for Bill Dembski’s CSI. One version can be traced to his book No Free Lunch published in 2002. Let us call that “CSI v1.0″.

Then in 2005 Bill published Specification the Pattern that Signifies Intelligence where he includes the identifier “v1.22″, but perhaps it would be better to call the concepts in that paper CSI v2.0 since, like windows 8, it has some radical differences from its predecessor and will come up with different results. Some end users of the concept of CSI prefer CSI v1.0 over v2.0.

It was very easy to estimate CSI numbers in version 1.0 and then argue later whether the subjective patterns used to deduce CSI were independent and not postdictive. Trying to calculate the CSI in v2.0 is cumbersome, and I don’t even try anymore. And as a matter of practicality, when discussing origin-of-life or biological evolution, ID-sympathetic arguments are framed in terms of improbability not CSI v2.0. In contrast, calculating CSI v1.0 is a very transparent transformation going from improbability to taking the negative logarithm of probability.

I = -log2(P)

In that respect, I think MathGrrl (who’s real identity he revealed here) has scored a point with respect to questioning the ability to calculate CSI v2.0, especially when it would have been a piece of cake in CSI v1.0.

For example, take 500 coins, and suppose they are all heads. The CSI v1.0 score is 500 bits. The calculation is transparent and easy, and accords with how we calculate improbability. Try doing that with CSI v2.0 and justifying the calculation.

Similarly, with pre-specifications (specifications already known to humans like the Champernowne Sequences), if we found 500 coins in sequence that matched a Champernowne Sequence, we could argue the CSI score is 500 bits as well. But try doing that calculation in CSI v2.0. For more complex situations, one might get different answers depending on who you are talking to because CSI v2.0 depends on the UPB and things like the number possible primitive subjective concepts in a person’s mind.

The motivation for CSI v2.0 was to try account for the possibility of slapping on a pattern after the fact and calling something “designed”. v2.0 was crafted to try to account for the possibility that someone might see a sequence of physical objects (like coins) and argue that the patterns in evidence were designed because he sees some pattern in the coins somewhat familiar to him but no one else. The problem is everyone has different life experiences and they will project their own subjective view of what constitutes a pattern. v2.0 tried to use some mathematics to create at threshold whereby one could infer, even if the recognized pattern was subjective and unique to the observer of a design, that chance would not be a likely explanation for this coincidence.

For example, if we saw a stream of bits which some claims is generated by coin flips, but the bit stream corresponds to the Chapernowne sequence, some will recognize the stream as designed and others will not. How then, given the subjective perceptions that each observer has, can the problem be resolved? There are methods suggested in v2.0, which in and of themselves would not be inherently objectionable, but then v2.0 tries to quantify how likely the subjective perception can arise out of chance and then it convolves this calculation with the probability of the objects emerging by chance. Hence we mix the probability of an observer concocting a pattern in his head by chance and then mixing it with the probability an event or object happens by chance, and after some gyrations out pops a CSI v2.0 score. v1.0 does not involve such heavy calculations regarding the random chance an observer formulates a pattern in his head, and thus is more tractable. So why the move from v1.0 to v2.0? The v1.0 approach has limitations witch v2.0 does not. However, I recommend, that when v1.0 is available to use, use v1.0!

The question of post diction is an important one, but if I may offer an opinion — many designs in biology don’t require exhaustive rigor as attempted in v2.0 to try to determine if our design inferences are postdictive (the result of our imagination) or whether the designed artifacts themselves are inherently evidence against a chance hypothesis. This can be done using simpler mathematical arguments.

For example, consider if we saw 500 fair coins all heads, do we actually have to consider human subjectivity when looking at the pattern and concluding it is designed? No. Why? We can make an alternative mathematical argument that says if coins are all heads they are sufficiently inconsistent with the Binomial Distribution for randomly tossed coins, hence we can reject the chance hypothesis. Since the physics of fair coins rules out physics as being the cause of the configuration, we can then infer design. There is no need in this case to delve into the question of subjective human specification to make the design inference in that case. CSI v2.0 is not needed to make the design inference, and CSI v1.0, which says we have 500 bits of CSI, is sufficient in this case.

Where this method (v1.0 plus pure statistics) fails is in questions of recognizing design in a sequence of coin flips that follow something like the Champernowne sequence. Here the question of how likely it is for humans to make the Champernowne sequence special in their minds becomes a serious question, and it is difficult to calculate that probability. I suppose that is what motivated Jason Rosenhouse to argue that the sort of specifications used by ID proponents aren’t useful for biology. But that is not completely true if the specifications used by ID proponents can be formulated without subjectivity (as I did in the example with the coins)

The downside of the alternative approach (using CSI v1.0 and pure statistics) is that it does not include the use of otherwise legitimate human subjective constructs (like the notion of motor) in making design arguments. Some, like Michael Shermer or my friend Allen MacNeill, might argue that we are merely projecting our notions of design by saying something looks like a motor or a communication system or a computer, but the perception of design is owing more to our projection than to an inherent design. But the alternative approach I suggest is immune from this objection, even though it is far more limited in scope.

Of course I believe something is designed if it looks like a motor (flagellum), a telescope (the eye), a microphone (the ear), a speaker (some species of bird can imitate an incredible range of sounds), a sonar system (bat and whale sonar), a electric field sensor (sharks), a magnetic field navigation system (monarch butterflies), etc. The alternative method I suggest will not directly detect design in these objects quite so easily, since the pure statistics are hard pressed to describe the improbability of such features in biology even though it is so apparent these features of biology are designed. CSI v2.0 was an ambitious attempt to cover these cases, but it came with substantial computational challenges to arrive at information estimates. I leave it to others to calculate CSI v2.0 for these cases.

Here is an example of using v1.0 in biology regarding homochirality. Amino acids can be left or right handed. Physics and chemistry dictate that left-handed and right-handed amino acids arise mostly (not always) in equal amounts unless there is a specialized process (like living cells) that creates them. Stanley Miller’s amino acid soup experiments created mixtures of left and right handed amino acids, a mixture we would call racemic (a mix of right and left-handed amino acids) versus the homochiral variety (only left-handed) we find in biology.

Worse for the proponents of mindless oirgins of life, even homochiral amino acids will racemize spontaneously over time (some half lives are on the order of hundreds of years), and they will deanimate. Further, when Sidney tried to polymerize homochiral amino acids into protoproteins, they racemized due to the extreme heat and created many non-chains, and the chains he did create had few if any alpha peptide bonds. And then in the unlikely event the amino acids polymerize, in a soup, the amino acids can undergo hydrolysis. These considerations are consistent with the familiar observation that when something is dead, it tends to remain dead and moves farther away from any chance of resuscitation over time.

I could go on and on, but the point being is we can provisionally say the binomial distribution I used for coins also applies to the homochirality in living creatures, and hence we can make the design inference and assert a biopolymer has at least 2^N bits of CSI v1.0 based on N stereoisomer residues. One might try to calculate CSI v2.0 for this case, but me being lazy will stick to the CSI v1.0 calculation. Easier is sometimes better.

So how can the alternative approach (CSI v1.0 and pure statistics) detect design of something like the flagellum or DNA encoding and decoding system? It cannot do so as comprehensively as CSI v2.0, but v1.0 can argue for design in the components. As I argued qualitatively in the article Coordinated Complexity – the key to refuting postdiction and single target objections one can formulate observer independent specification (such as I did with the 500 coins being all heads) by appeal to pure statistics. I gave the example of how the FBI convicted cheaters of using false shuffles even though no formal specifications for design were asserted. They merely had to use common sense (which can be described mathematically as cross or auto correlation) to detect the cheating.

Here is what I wrote:

The opponents of ID argue something along the lines: “take a deck of cards, randomly shuffle it, the probability of any given sequence occurring is 1 out of 52 factorial or about 8×10^67 — Improbable things happen all the time, it doesn’t imply intelligent design.”

In fact, I found one such Darwinist screed here:

Creationists and “Intelligent Design” theorists claim that the odds of life having evolved as it has on earth is so great that it could not possibly be random. Yes, the odds are astronomical, but only if you were trying to PREDICT IN ADVANCE how life would evolve.

http://answers.yahoo.com/question/index?qid=20071207060800AAqO3j2

Ah, but what if cards dealt from one random shuffle are repeated by another shuffle, would you suspect Intelligent Design? A case involving this is reported in the FBI website: House of Cards

In this case, a team of cheaters bribed a casino dealer to deal cards and then reshuffle them in same order that they were previously dealt out (no easy shuffling feat!). They would arrive at the casino, play cards which the dealer dealt and secretly record the sequence of cards dealt out. Thus when the dealer re-shuffled the cards and dealt out the cards in the exact same sequence as the previous shuffle, the team of cheaters would be able to play knowing what cards they would be dealt, thus giving them substantial advantage. Not an easy scam to pull off, but they got away with it for a long time.

The evidence of cheating was confirmed by videotape surveillance because the first random shuffle provided a specification to detect intelligent design of the next shuffle. The next shuffle was intelligently designed to preserve the order of the prior shuffle.

Biology is rich with self-specifying systems like the auto correlatable sequence of cards in the example above. The simplest example is life’s ability to make copies of itself through a process akin to Quine Computing. Physics and chemistry makes Quine systems possible, but simultaneously improbable. Computers, as a matter of principle, cannot exist if they have no degrees of freedom which permit high improbability in some of its constituent systems (like computer memory banks).

We can see the correlation between a parent organism and its offspring not being the result of chance, and thus we can reject the chance hypothesis for that correlation. One might argue that though the offspring (copy) is not the product of chance, the process of copying is the product of a mindless copy machine. True, but we can further then estimate the probability of randomly implementing particular Quine computing algorithms (that makes it possible for life to act like computerized copy machines). The act of a system making copies is not in-and-of-itself spectacular (salt crystals do that), but the act of making improbable copies via an improbable copying machine? That is what is spectacular.

I further pointed out that biology is rich with systems that can be likened to login/password or lock-and-key systems. That is, the architecture of the system is such that the components are constrained to obey a certain pattern or else the system will fail. In that sense, the targets for individual components can be shown to be specified without having to calculate the chances the observer is randomly formulating subjective patterns onto the presumably designed object.

That is to say, even though there are infinite ways to make lock-and-key combinations, that does not imply that emergence of a lock-and-key system is probable! Unfortunately, Darwinists will implicitly say, “there are infinite number of ways to make life, therefore we can’t use probability arguments”, but they fail to see the errors in their reasoning as demonstrated with the lock-and-key analogy.

This simplified methodology using v1.0, though not capable of saying “the flagellum is a motor and therefore is designed”, is capable of asserting “individual components (like the flagellum assembly instructions) are improbable hence the flagellum is designed.”

But I will admit, the step of invoking the login/password or lock-and-key metaphor is a step outside of pure statistics, and making the argument for design in the case of login/password and lock-and-key metaphors more rigorous is a project of future study.

Acknowledgments:
Mathgrrl, though we’re opponents in this debate, he strikes me a decent guy

NOTES:
The fact that life makes copies motivated Nobel Laureate Eugene Wigner to hypothesize a biotonic law in physics. That was ultimately refuted. Life does copy via a biotonic law but through computation (and the emergence of computation is not attributable to physical law in principle just like software cannot be explained by hardware alone).

It is intuitively obvious that insect wings, such as these shown from the desert locust, did not evolve from random chance events as evolutionists insist they did, and new research is helping to elucidate the underlying reasons. One glance at the insect wings pictured here reveals something special, but what is it? There is a definite pattern revealed by the crisscrossing veins and the new research demonstrates that the cells formed by the intersecting veins are optimized to minimize the weight of the wing while maximizing the wing’s resistance to cracks. Specifically, the cell’s are sized according to the so-called “critical crack length” which is the length at which a crack becomes a structural threat—a property of the wing material. Cracks shorter than this length tend not to grow and so need not be stopped. So the mechanical properties of the wing material (cuticle), and the structural design of the veins, work together to form an optimized wing. As the research concluded:  Read more

The scientific enterprise entails:

1. observation
2. hypothesis
3. testing

Consider this passage from the class text of an introductory cosmology class I took once upon a time:

galaxies farther than 4300 megaparsecs from us are currently moving away from us at speeds greater than that of light. Cosmological innocents sometimes exclaim, “Gosh! Doesn’t this violate the law that massive objects can’t travel faster than the speed of light?” Actually, it doesn’t. The speed limit that states that massive objects must travel with v < c relative to each other is one of the results of special relativity, and refers to the relative motion of objects within a static space. In the context of general relativity, there is no objection to having two points moving away from each other at superluminal speed due to the expansion of space.

page 39
Introduction to Cosmology
by Barbara ryden

Let’s say for the sake or argument this is true, an agnostic science loving friend of mind expressed the following unease with this claim:

1. we can never observe these galaxies
2. thus we can therefore never test that they are moving faster than the speed of light from us
3. repeatability of the observation? Not even testable in principle
4. things moving faster than the speed of light? We can’t test that directly either!
5. if you add space between two attracting bodies, doesn’t that mean you increase potential energy out of nowhere?

I responded to point 5 by saying, “General Relativity might not implicitly assert the conservation of energy law”, but that didn’t seem to be reassuring to him. I then read this passage in the same book on page 17:

During the 1950s and 1960s, the Big Bang and Steady State models battled for supremacy. Critics of Steady State model pointed out that the continuous creation of matter violates mass-energy conservation. Supporters of the Steady State model pointed out that the continuous creation of matter is no more absurd than the instantaneous creation of the entire universe in a single “Big Bang”.

My agnostic friend just about fell out his chair laughing. We both laughed.

The scenario of faster-than-speed-of light motion can be fit into the Friedmann-Robertson-Walker-LeMaitre solution to Einstein’s feild equations of General Relativity, but does that make it true?

Consider Newton’s 2nd law. Suppose we are dealing with a force of 5 Newtons, what are the some of the mathematical (not necessarily physical) solutions to an equation constrained by the assumption that the force is 5 Newtons?

F = ma where F = 5 Newtons
Solution 1:
mass = 5 kg
acceleration = 1 meter/ sec^2

Solution 2
mass = -5 kg
acceleration = -1 meter/sec^2

etc.

Astute readers will notice solution 2, though mathematically consistent with the equation F=ma, is not physically real (in classical or most physics anyway) since it invokes negative mass.

I recall when studying General Relativity the professor assigning us an exercise to analyze geodesic trajectories through a particular solution to the Einstein field equations. This solution yielded incredible possibilities, and I thought to myself, “wow, where can I find such a place in the universe to observe this?”

And then reviewing the solution in class, the professor said something to the effect, “I didn’t tell you, but the solution I gave you describes a wormhole, but I’m not sure wormholes are possible since you need negative mass! This was more an exercise in math.” I and my fellow students had a small laugh, especially after having endured this mathematical exercise. The point being however, just because something is a mathematical solution to an equation of physics doesn’t mean it’s for real.

So with respect to those galaxies which we can’t see, which we will never see, that move faster than the speed of light, we can only postulate their existence as fact via inference. We can’t do it by observation, not by repeatable measurement or direct testing. So is the claim of these unseen entities a scientific claim? It does not accord with 2 of the 3 elements listed above that describe the scientific enterprise. The positivists among us will assert, “well if we can’t see it, we won’t believe it.”

So I would respond, “Ok, so do you believe the unseen galaxies predicted by the Big Bang. You can’t see them, you won’t see them, you can’t verify them, but supposedly they exist, they have properties as galaxies, and to top it off they move faster than the speed of light even though in the lab or anywhere we have access to, we haven’t clocked anything moving faster than the speed of light?”

So is the claim of unseen, unobservable, untestable, unverifiable galaxies a scientific claim? Eh, I leave that to the philosophers of science to decide, but it seems to me if one will admit as scientific the unseen, untestable, unknowable, unobservable, unverifiable entities as existing and having certain properties via inference and without direct evidence, then — well uh — couldn’t we hypothesize all sorts of unseen, untestable, unobservable, unknowable, unverifiable entities as being real via inference, and hence call that hypothesis science? I provided one example of such an entity in the thread: Quantum Enigma of Consciousness and the Identity of the Designer where Richard Conn Henry (a professor at no minor school) argued that Quantum Mechanics suggests God exists. Richard Conn Henry argued God is a permissible construct within accepted physics, and so is consciousness. Whether God is ultimately real is a separate question, but science doesn’t preclude His existence.

Getting back to cosmology, I learned of Alan Guth who speculated the universe expanded briefly at around 1000 times the speed of light in a process called inflation. In fact Andrei Linde speculated Guth understated the inflation speed by a factor of 10^1,000,000. If Guth claims the universe was inflationary, Linde claims it was hyperinflationary. Yikes!

What wasn’t presented in our cosmology class was Guth’s other speculation, which I learned of in a taboo book by William C. Mitchell

Guth is reported to have said, “in fact, our own universe might have been started in somebody’s basement.” Overbye has reported that, Guth and another MIT professor, Ed Fahri, found that, “If you could compress 25 pounds of matter into 10^-24 centimeters, making a mass 10^75 times the density of water…a bubble of false vacuum, or what Guth called a ‘child universe’ would be formed. From outside it would look like a black hole. From the inside it would look like an inflating universe.”

page 229
Bye Bye Big Bang, Hello Reality
by William C. Mitchell

Mitchell further commented of Guth, “can you believe such garbage?” I withhold making such a judgment since Guth is a smart guy, but it seems to me if we admit the possiblity of the universe being created by some tinkerer in a basement, we can surely admit intelligent design of the universe.

On a marginally more serious note, there are a minority of dissenting voices that share some of the reservations about modern cosmology that I’ve hinted of in this thread. One of them is a respected cosmologist by the name of Michael Disney. He argues we have too little data to really form a cosmological model.

Here is an excerpt from Modern Cosmology Science or Folktale

Where Do We Stand Today?

Big Bang cosmology is not a single theory; rather, it is five separate theories constructed on top of one another. The ground floor is a theory, historically but not fundamentally rooted in general relativity, to explain the redshifts—this is Expansion, which happily also accounts for the cosmic background radiation. The second floor is Inflation—needed to solve the horizon and “flatness” problems of the Big Bang. The third floor is the Dark Matter hypothesis required to explain the existence of contemporary visible structures, such as galaxies and clusters, which otherwise would never condense within the expanding fireball. The fourth floor is some kind of description for the “seeds” from which such structure is to grow. And the fifth and topmost floor is the mysterious Dark Energy, needed to allow for the recent acceleration of cosmic expansion indicated by the supernova observations. Thus Dark Energy could crumble, leaving the rest of the building intact. But if the Expansion floor collapsed, the entire edifice above it would come crashing down. Expansion is a moderately well-supported hypothesis, consistent with the cosmic background radiation, with the helium abundance and with the ages inferred for the oldest stars and star clusters in our neighborhood. However, finding more direct evidence for Expansion must be of paramount importance.

In the 1930s, Richard Tolman proposed such a test, really good data for which are only now becoming available. Tolman calculated that the surface brightness (the apparent brightness per unit area) of receding galaxies should fall off in a particularly dramatic way with redshift—indeed, so dramatically that those of us building the first cameras for the Hubble Space Telescope in the 1980s were told by cosmologists not to worry about distant galaxies, because we simply wouldn’t see them. Imagine our surprise therefore when every deep Hubble image turned out to have hundreds of apparently distant galaxies scattered all over it (as seen in the first image in this piece). Contemporary cosmologists mutter about “galaxy evolution,” but the omens do not necessarily look good for the Tolman test of Expansion at high redshift.

In its original form, an expanding Einstein model had an attractive, economic elegance. Alas, it has since run into serious difficulties, which have been cured only by sticking on some ugly bandages: inflation to cover horizon and flatness problems; overwhelming amounts of dark matter to provide internal structure; and dark energy, whatever that might be, to explain the seemingly recent acceleration. A skeptic is entitled to feel that a negative significance, after so much time, effort and trimming, is nothing more than one would expect of a folktale constantly re-edited to fit inconvenient new observations.

Ah, the wonderful world of Disney. Disney wrote a more technical article in The Case Against Cosmology published in the Journal General Relativity and Gravitation..

It should be noted, there is a forgotten article in the Discovery Institute archives by David Berlinski:
Was There a Big Bang

Is the big bang model correct? The answer to that question is above my pay grade. One of my professors, James Trefil, gave his estimate that its about half way confirmed, but he has still some skepticism as he articulated in his book The Dark Side of the Universe.

The answer to the question of the Big Bang is way above my pay grade, but I posted this thread mostly to point out that if we pass off certain unverifiable, unseen, unknowable, unobservable claims as science, by what standard is ID disqualified? After all, according to Richard Conn Henry, quantum mechanics suggests God exists, and if so (though he won’t go so far as I would), imho, ID can then be admitted into to the realms of scientific hypotheses since now we have a theoretical entity with a sufficient skill set to design life.

And finally, with respect to the question of ID being science, in light of considerations above, this passage by Bill Dembski comes to mind:

Thus, a scientist may view design and its appeal to a designer as simply a fruitful device for understanding the world, not attaching any significance to questions such as whether a theory of design is in some ultimate sense true or whether the designer actually exists. Philosophers of science would call this a constructive empiricist approach to design. Scientists in the business of manufacturing theoretical entities like quarks, strings, and cold dark matter could therefore view the designer as just one more theoretical entity to be added to the list. I follow here Ludwig Wittgenstein, who wrote, “What a Copernicus or a Darwin really achieved was not the discovery of a true theory but of a fertile new point of view.”

Just now VJT picked up a TSZ attempt to challenge CSI.

I suggested wood grain as a possibility, leading to complex but not relevantly specified. Phineas did a Google Image search and came up, ash on ice.

I did a similar search:

This led me to seek to superpose and fit on a colourised version of the suggested original:

This seems to be indeed the source.

In neither case are we dealing with the joint complexity and specificity pattern that leads to inferring CSI thence design.

It is worth repeating the design inference filter as a reference:

The per aspect explanatory filter that shows how design may be inferred on empirically tested, reliable sign

Comments may be made in VJT’s discussion thread. END

Over at The Skeptical Zone, Dr. Elizabeth Liddle has put up a post for Uncommon Descent readers, entitled, A CSI Challenge (15 May 2013). She writes:

Here is a pattern:

It’s a gray-scale image, so it is just one 2D matrix. Here is a text file containing the matrix:

MysteryPhoto

I would like to know whether it has CSI or not.

The term complex specified information (or CSI) is defined by Intelligent Design advocates William Dembski and Jonathan Wells in their book, The Design of Life: Discovering Signs of Intelligence in Biological Systems (The Foundation for Thought and Ethics, Dallas, 2008), as being equivalent to specified complexity (p. 311), which is then defined as follows:

An event or object exhibits specified complexity provided that (1) the pattern to which it conforms is a highly improbable event (i.e. has high PROBABILISTIC COMPLEXITY) and (2) the pattern itself is easily described (i.e. has low DESCRIPTIVE COMPLEXITY). (2008, p. 320)

In some comments on her latest post, Dr. Liddle tells readers more about her mysterious pattern:

There are 658 x 795 pixels in the image, i.e 523,110. Each one can take one of 256 values (0:255). Not all values are represented with equal probability, though. It’s a negatively skewed distribution, with higher values more prevalent than lower…

I want CSI not FSC or any of the other alphabet soup stuff…

Feel free to guess what it is. I shan’t say for a while ☺ …

Well, if I’m understanding Dembski correctly, his claim is that we can look at any pattern, and if it is one of a small number of specified patterns out of a large total possible number of patterns with the same amount of Shannon Information, then if that proportion is smaller than the probability of getting it at least once in the history of the universe, then we can infer design…

Clearly it’s going to take a billion monkeys with pixel writers a heck of a long time before they come up with something as nice as my photo. But I’d like to compute just how long, to see if my pattern is designed…

tbh [To be honest - VJT], I think there are loads of ways of doing this, and some will give you a positive Design signal and some will not.

It all depends on p(T|H) [the probability of a specified pattern T occurring by chance, according to some chance hypothesis H - VJT] which is the thing that nobody every tells us how to calculate.

It would be interesting if someone at UD would have a go, though.

Looking at the image, I thought it bore some resemblance to contours (Chesil beach, perhaps?), but I’m probably hopelessly wrong in my guess. At any rate, I’d like to make a few short remarks.

(1) There is a vital distinction that needs to be kept in mind between a specified pattern’s being improbable as a configuration, and its being improbable as an outcome. The former does not necessarily imply the latter. If a pattern is composed of elements, then if we look at all possible arrangements or configurations of those constituent elements, it may be that only a very tiny proportion of these will contain the pattern in question. That makes it configurationally improbable. But that does not mean that the pattern is unlikely to ever arise: in other words, it would be unwarranted to infer that the appearance of the pattern in question is historically improbable, from its rarity as a possible configuration of its constituent elements.

(2) If, however, the various processes that are capable of generating the pattern in question contain no built-in biases in favor of this specified pattern arising – or more generally, no built-in biases in favor of any specified pattern arising – then we can legitimately infer that if a pattern is configurationally improbable, then its emergence over the course of time is correspondingly unlikely.

Unfortunately, the following remark by Elizabeth Liddle in her A CSI Challenge post seems to blur the distinction between configurational improbability and what Professor William Dembski and Dr. Jonathan Wells refers to in their book, The Design of Life (Foundation for Thought and Ethics, Dallas, 2008), as originational improbability (or what I prefer to call historical improbability):

Well, if I’m understanding Dembski correctly, his claim is that we can look at any pattern, and if it is one of a small number of specified patterns out of a large total possible number of patterns with the same amount of Shannon Information, then if that proportion is smaller than the probability of getting it at least once in the history of the universe, then we can infer design.

By itself, the configurational improbability of a pattern cannot tell us whether the pattern was designed. In order to assess the probability of obtaining that pattern at least once in the history of the universe, we need to look at the natural processes which are capable of generating that pattern.

(3) The “chance hypothesis” H that Professor Dembski discussed in his 2005 paper, Specification: The Pattern That Signifies Intelligence (version 1.22, 15 August 2005), was not a “pure randomness” hypothesis. In his paper, he referred to it as “the chance hypothesis most naturally associated with this probabilistic set-up” (p. 7) and later declared, “H, here, is the relevant chance hypothesis that takes into account Darwinian and other material mechanisms” (p. 18).

In a comment on Dr. Elizabeth Liddle’s post, A CSI Challenge, ID critic Professor Joe Felsenstein writes:

The interpretation that many of us made of CSI was that it was an independent assessment of whether natural processes could have produced the adaptation. And that Dembski was claiming a conservation law to show that natural processes could not produce CSI.

Even most pro-ID commenters at UD interpreted Dembski’s CSI that way. They were always claiming that CSI was something that could be independently evaluated without yet knowing what processes produced the pattern.

But now Dembski has clarified that CSI is not (and maybe never was) something you could assess independently of knowing the processes that produced the pattern. Which makes it mostly an afterthought, and not of great interest.

Professor Felsenstein is quite correct in claiming that “CSI is not … something you could assess independently of knowing the processes that produced the pattern.” However, this is old news: Professor Dembski acknowledged as much back in 2005, in his paper, Specification: The Pattern That Signifies Intelligence (version 1.22, 15 August 2005). Now, it is true that in his paper, Professor Dembski repeatedly referred to H as the chance hypothesis. But in view of his remark on page 18, that “H, here, is the relevant chance hypothesis that takes into account Darwinian and other material mechanisms,” I think it is reasonable to conclude that he was employing the word “chance” in its broad sense of “undirected,” rather than “purely random,” since Darwinian mechanisms are by definition non-random. (Note: when I say “undirected” in this post, I do not mean “lacking a telos, or built-in goal”; rather, I mean “lacking foresight, and hence not directed at any long-term goal.”)

I shall argue below that even if CSI cannot be assessed independently of knowing the processes that might have produced the pattern, it is still a useful and genuinely informative quantity, in many situations.

(4) We will definitely be unable to infer that a pattern was produced by Intelligent Design if:

(a) there is a very large(possibly infinite) number of undirected processes that might have produced the pattern;

(b) the chance of any one of these processes producing the pattern is astronomically low; and

(c) all of these processes are (roughly) equally probable.

What we then obtain is a discrete uniform distribution, which looks like this:

In the graph above, there are only five points, corresponding to five rival “chance hypotheses,” but what if we had 5,000 or 5,000,000 to consider, and they were all equally meritorious? In that case, our probability distribution would look more and more like this continuous uniform distribution:

The problem here is that taken singly, each “chance hypothesis” appears to be incapable of generating the pattern within a reasonable period of time: we’d have to wait for eons before we saw it arise. At the same time, taken together, the entire collection of “chance hypotheses” may well be perfectly capable of generating the pattern in question.

The moral of the story is that it is not enough to rule out this or that “chance hypothesis”; we have to rule out the entire ensemble of “chance hypotheses” before we can legitimately infer that a pattern is the result of Intelligent Design.

But how can we rule out all possible “chance hypotheses” for generating a pattern, when we haven’t had time to test them all? The answer is that if some “chance hypotheses” are much more probable than others, so that a few tower above all the rest, and the probabilities of the remaining chance hypotheses tend towards zero, then we may be able to estimate the probability of the entire ensemble of chance processes generating that pattern. And if this probability is so low that we would not expect to see the event realized even once in the entire history of the observable universe, then we could legitimately infer that the pattern was the product of Intelligent Design.

(5) In particular, if we suppose that the “chance hypotheses” which purport to explain how a pattern might have arisen in the absence of Intelligent Design follow a power law distribution, it is possible to rule out the entire ensemble of “chance” hypotheses as an inadequate explanation of that pattern. In the case of a power law distribution, we need only focus on the top few contenders, for reasons that will soon be readily apparent. Here’s what a discrete power law distribution looks like:

The graph above depicts various Zipfian distributions, which are discrete power law probability distributions. The frequency of words in the English language follows this kind of distribution; little words like “the,” “of” and “and” dominate.

And here’s what a continuous power law distribution looks like:

An example of a power-law graph, being used to demonstrate ranking of popularity (e.g. of actors). To the right is the long tail of insignificant individuals (e.g. millions of largely unknown aspiring actors), and to the left are the few individuals that dominate (e.g. the top 100 Hollywood movie stars).

This phenomenon whereby a few individuals dominate the rest is also known as the 80–20 rule, or the Pareto principle. It is commonly expressed in the adage: “80% of your sales come from 20% of your clients.” Applying this principle to “chance hypotheses” for explaining a pattern in the natural sciences, we see that there’s no need to evaluate each and every chance hypothesis that might explain the pattern; we need only look at the leading contenders, and if we notice the probabilities tapering off in a way that conforms to the 80-20 rule, we can calculate the overall probability that the entire set of hypotheses is capable of explaining the pattern in question.

Is the situation I have described a rare or anomalous one? Not at all. Very often, when scientists discover some unusual pattern in Nature, and try to evaluate the likelihood of various mechanisms for generating that pattern, they find that a handful of mechanisms tend to dominate the rest.

The Chaos Computer Club used a model of the monolith in Arthur C. Clarke’s novel 2001, at the Hackers at Large camp site. Image courtesy of Wikipedia.

(6) We can now see how the astronauts were immediately able to infer that the Monolith on the moon in the movie 2001 (based on Arthur C. Clarke’s novel) must have been designed. The monolith in the story was a black, extremely flat, non-reflective rectangular solid whose dimensions were in the precise ratio of 1 : 4 : 9 (the squares of the first three integers). The only plausible non-intelligent causes of a black monolith being on the Moon can be classified into two broad categories: exogenous (it arrived there as a result of some outside event – i.e. something falling out of the sky, such as a meteorite or asteroid) and endogenous (some process occurring on or beneath the moon’s surface generated it – e.g. lunar volcanism, or perhaps the action of wind and water in a bygone age when the moon may have had a thin atmosphere).

It doesn’t take much mental computing to see that neither process could plausibly generate a monument of such precise dimensions, in the ratio of 1 : 4 : 9. To see what Nature can generate by comparison, have a look at these red basaltic prisms from the Giant’s Causeway in Northern Ireland:

In short: in situations where scientists can ascertain that there are only a few promising hypotheses for explaining a pattern in Nature, legitimate design inferences can be made.

The underwater formation or ruin called “The Turtle” at Yonaguni, Ryukyu islands. Photo courtesy of Masahiro Kaji and Wikipedia.

(7) We can now see why the Yonaguni Monument continues to attract such spirited controversy, with some experts, such as Masaaki Kimura of the University of the Ryukyus, who claims: “The largest structure looks like a complicated, monolithic, stepped pyramid that rises from a depth of 25 meters.” Certain features of the Monument, such as a 5 meter-wide ledge that encircles the base of the formation on three sides,
a stone column about 7 meters tall, a straight wall 10 meters long, and a triangular depression with two large holes at its edge, are often cited as unmistakable evidence of human origin. There have even been claims of mysterious writing found at the underwater site. Other experts, such as Robert Schoch, a professor of science and mathematics at Boston University, insist that the straight edges in the underwater structure are geological features. “The first time I dived there, I knew it was not artificial,” Schoch said in an interview with National Geographic. “It’s not as regular as many people claim, and the right angles and symmetry don’t add up in many places.” There is an excellent article about the Monument by Brain Dunning at Skeptoid here.

The real problem here, as I see it, is that the dimensions of the relevant features of the Yonaguni Monument haven’t yet been measured and described in a rigorously mathematical fashion. For that reason, we don’t know whether it falls closer to the “Giant’s Causeway” end of the “design spectrum,” or the “Moon Monolith” end. In the absence of a large number of man-made monuments and natural monoliths that we can compare it to, our naive and untutored reaction to the Yonaguni Monument is one of perplexity: we don’t know what to think – although I’d be inclined to bet against it’s having been designed. What we need is more information.

(8) Turning now to Dr. Elizabeth Liddle’s picture, there are three good reasons why we cannot determine how much CSI it contains.

First, Dr. Liddle is declining to tell us what the specified pattern is, for the time being. Until she does, we have no way of knowing for sure whether there is a pattern or not, short of spotting it – which might take a very long time. (Some patterns, like the Champerdowne sequence in Professor Dembski’s 2005 essay, are hard to discern. Others, like the first 100 primes, are relatively easy.)

Second, we have no idea what kind of processes were actually used by Dr. Liddle to generate the picture. We don’t even know what medium it naturally occurs in (I’m assuming here that it exists somewhere out there in the real world). Is it sand? hilly land? tree bark? We don’t know. Hence we are unable to compute P(T|H), or the probability of the pattern arising according to some chance hypothesis, as we can’t even formulate a “chance hypothesis” H in the first place.

Finally, we don’t know what other kinds of natural processes could have been used to generate the pattern (if there is one), as we don’t know what the pattern is in the first place, and we don’t know where in Nature it can be found. Hence, we are unable to formulate a set of rival “chance hypotheses,” and as a result, we have no idea what the probability distribution of the ensemble of “chance hypotheses” looks like.

In short: there are too many unknowns to calculate the CSI in Dr. Liddle’s example. A few more hints might be in order.

(9) In the case of proteins, on the other hand, the pattern is not mathematical (e.g. a sequence of numbers) but functional: proteins are long strings of amino acids that actually manage to fold up, and that perform some useful biological role inside the cell. Given this knowledge, scientists can formulate hypotheses regarding the most likely processes on the early Earth for assembling amino acid strings. If a few of these hypotheses stand out, scientists can safely ignore the rest. Thus the CSI in a protein should be straightforwardly computable.

I have cited the recent work of Dr. Kozulic and Dr. Douglas Axe in recent posts of mine (see here, here and here). Suffice to say that the authors’ conclusions that the proteins we find in Nature are the product of Intelligent Design is not an “Argument from Incredulity” but an argument based on solid mathematics, applied to the most plausible “chance hypotheses” for generating a protein. And to those who object that proteins might have come from some smaller replicator, I say: that’s not a mathematical “might” but a mere epistemic one (as in “There might, for all we know, be fairies”). Meanwhile, the onus is on Darwinists to find such a replicator.

(10) Finally, Professor Felsenstein’s claim in a recent post that “Dembski and Marks have not provided any new argument that shows that a Designer intervenes after the population starts to evolve” with their recent paper on the law of conservation of information, is a specious one, as it rests on a misunderstanding of Intelligent Design. I’ll say more about that in a forthcoming post.

Recommended Reading

Specification: The Pattern That Signifies Intelligence by William A. Dembski (version 1.22, 15 August 2005).

The Conservation of Information: Measuring the Cost of Successful Search by William A. Dembski (version 1.1, 6 May 2006). Also published in IEEE Transactions on Systems, Man and Cybernetics A, Systems & Humans, 5(5) (September 2009): 1051-1061.

Conservation of Information Made Simple (28 August 2012) by William A. Dembski.

Before They’ve Even Seen Stephen Meyer’s New Book, Darwinists Waste No Time in Criticizing Darwin’s Doubt (4 April 2013) by William A. Dembski.

Does CSI enable us to detect Design? A reply to William Dembski (7 April 2013) by Joe Felsenstein at Panda’s Thumb.

NEWS FLASH: Dembski’s CSI caught in the act (14 April 2011) by kairosfocus at Uncommon Descent

Is Darwinism a better explanation of life than Intelligent Design? (14 May 2013) by Elizabeth Liddle at The Skeptical Zone.

A CSI Challenge (15 May 2013) by Elizabeth Liddle at The Skeptical Zone.