Patron saint of the long shot.

Natural Selection: Could It Be the Single Greatest Idea Ever Invented?
Denyse O'Leary 

Information, according to Darwin's idea (natural selection), can exist without intelligence. Nature produces intelligent designs, just because some life forms survive and others don't. That's it. That's all it takes. How odd that no one noticed.

A letter written by Darwin, the theory's originator, might fetch $90,000 at an upcoming auction. The Guardian explains:

The 19th-century naturalist and fervent letter writer had largely evaded this question since the publication of the book in 1859. The now classic text introduced his theory of natural selection, which demonstrated that species evolve through gene variation; it was a divisive proposition for Christian readers who believed that humans were made in God's image, distinct from other animals.

That distinction can prove relevant if one thinks civil liberties matter. Many of us live in countries where the invocation of a supreme being is a basis for civil liberties (though those liberties may not extend to mosquitoes).

Darwin's theory of evolution (natural selection acting on random mutations) is a cultural icon, like the Big Bang, or e=mc2. One needn't know anything specific about any of these ideas. Indeed, media professionals can be passionately devoted to Darwinism without knowing anything about it at all.

That makes sense. Professed loyalty to Darwin is an admission to good parties. And Darwinism's relationship to modern warfare and eugenics is drowned out by cultural support. True, hillbillies thump the Bible against it, to the groans of the better educated. But what if...?

First, what exactly is Darwin's theory anyway, other than an invite to the approved parties?

Here it is: Information can be created without intelligence. That is, natural selection acting on random mutation explains the order of life we see all around us. What can't survive won't, and that explains how very complex life forms and structures -- including the human mind -- get built up.

True: Things that can't survive don't. But why would that fact alone drive nature to produce anything as simple as a kitten, let alone a math genius?

We've looked earlier at documented ways evolution can really happen -- if all we really want to know is how life forms can change over time. That said, I spent the last fifteen years trying to understand the cultural part. Darwinism isn't just about evolution as such. It is also a way of looking at life. It tries to explain life without assuming that there is any actual mind at all, dispensing with traditional philosophies and religions.

Humans are assumed to do what they do because they are guided by their instincts, in the same way that nature haphazardly produces a kitten or a math genius.

Ideas have consequences. Think of that when, for example, an elaborately coiffed person on prime time TV announces that she believes in evolution (by which she means Darwinism) when she probably has no better idea what it means than the existence of space aliens (of which she is also perfectly certain, on the same level of evidence). Then decide.

See the rest of the series to date at "Talk to the Fossils: Let's See What They Say Back."

The unholy trinity.

Trinity And Pagan Influence

Trinity And Pagan Influence

1. "The trinity was a major preoccupation of Egyptian theologians .... Three gods are combined and treated as a single being, addressed in the singular. In this way the spiritual force of Egyptian religion shows a direct link with Christian theology." - Egyptian Religion.

2. "The Egyptians believed in a resurrection and future life, as well as in a state of rewards and punishments dependent on our conduct in this world. The judge of the dead was Osiris, who had been slain by Set, the representative of evil, and afterwards restored to life. His death was avenged by his son Horus, whom the Egyptians invoked as their "Redeemer." Osiris and Horus, along with Isis, formed a trinity, who were regarded as representing the sun-God under different forms." - Trinitarian scholar Dr. M.G. Easton; Easton's Bible Dictionary, Thomas Nelson Publ.

3. "This triad of Abydos [Horus, Isis, and Osiris] is apparently much older than even the earliest records .... These 3 main gods were skillfully incorporated into the Great Ennead or State religion of Egypt .... particularly during the first 5 [3110-2342 B.C.] or 6 dynasties when the worship of this triad was prominent." - The Ancient Myths, A Mentor Book, Goodrich, p. 25, 1960.

4. Alexandria, Egypt, had even developed a trinity doctrine of its very own long before Christian times. It appears to have been a blend (not surprisingly) of Egyptian, Hindu, and Greek philosophy/mystery religions.

"This fusing of one god with another is called theocrasia, and nowhere was it more vigorously going on than in Alexandria. Only two peoples resisted it in this period: The Jews, who already had their faith in the one God of heaven and earth, Jehovah, and the Persians, who had a monotheistic sun worship [Mithras]. It was Ptolemy I [who died in 283 B. C.] who set up not only the Museum in Alexandria, but the Serapeum, devoted to the worship of a trinity of gods which represented the result of a process of theocrasia applied more particularly to the gods of Greece and Egypt [with a distinct Hindu flavor].

"This trinity consisted of the god Serapis (= Osiris + Apis), the goddess Isis (= Hathor, the cow-moon goddess), and the child-god Horus. In one way or another almost every god was identified with one or other of these three aspects of the one god, even the sun god Mithras of the Persians. and they were each other; THEY WERE THREE, BUT THEY WERE ALSO ONE." - The Outline of History, Wells, vol. 1, p. 307, 1956 ed.

5. The book The Symbolism of Hindu Gods and Rituals admits, regarding the ancient Hindu trinity that was taught centuries before the first Christians:
"Siva is one of the gods of the Trinity. He is said to be the god of destruction. The other two gods are Brahma, the god of creation and Vishnu, the god of maintenance.... To indicate that these three processes are one and the same the three gods are combined in one form." - Published by A. Parthasarathy, Bombay. (As quoted in ti-E, p. 12.)

6. The Encyclopedia Americana tells of the fully developed "Hindu Trinity" existing "from about 300 B. C.," p. 197, v. 14, 1957. Brahmana writings, probably from 800 B. C. or before, frequently include the Vedic triad concept. - Encyclopedia Britannica, 14th ed., v. 3, pp. 1014-1016, and 34, also see The Portable World Bible, The Viking Press, pp. 23, 25.

7. "Vishnu, Brahma, and Siva together form the trinity of the Hindu Religion. At one time these were distinct Hindu deities. Their rival claims for recognition were finally met by making them three forms of the one supreme god. This was, however, a creation of the priests and ecclesiastical students." - Encyclopedia Americana, 1957 ed., v. 28, p. 134.
  
8. "There is a tendency in [pagan] religious history for the gods to be grouped in threes .... Even in Christianity, the Trinity of the Father, Son, and Holy Ghost reflects the underlying tendency. In India, the great Triad included Brahma, the Creator, Vishnu, the Preserver, and Shiva, the Destroyer. These represent the cycle of existence, just as the Babylonian triad of Anu, Enlil and Ea represent the materials of existence: air, water, earth." - An Encyclopedia of Religion, Ferm, p. 794, 1945.

9. Not only did the ancient Babylonians have the major trinity of Anu, Enlil, and Ea, but they worshiped more than one trinity of gods. - Babylonian Life and History, Sir E. A. Wallis Budge, 1925 ed., pp. 146, 147.

10. "On the basis of  Pythagorean and gnostic theories, each number [in the Medieval Number Method] was assigned a root meaning and diversified representations.  Some root meanings were: 1 = UNITY OF GOD, ... 3 = TRINITY, extension of Godhead, ... 10 = extension of Unity, Perfect Completeness." - An Encyclopedia of Religion, Ferm, 1945, p. 755.

11. "... the doctrine of the Trinity was of gradual and comparatively late formation; that it had its origin in a source entirely foreign from that of the Jewish and Christian scriptures; that it grew up, and was ingrafted on Christianity, through the hands of the Platonizing Fathers."– p. 34, The Church of the First Three Centuries, Alvan Lamson, D.D. (see WT 15 Oct. 1978, p. 32.)

"All things are three, and thrice is all:  and let us use this number in the worship of the gods. For as the Pythagoreans say, everything and all things are bound by threes, for the end, the middle, and the beginning have this number in everything, and these compose the number of the trinity." - Aristotle, as quoted in Paganism in our Christianity, Arthur Weigall, p. 198, Putnam, NY.  (Weigall is quoting from On the Heavens, Bk I, ch. i., by Aristotle who died  322 B.C.)

So it appears that this "holy" number three used to "worship the gods" in unity came down from the extremely influential Pythagoras to the ancient Greek philosophy/mystery religions and even to Plato himself.

"NEO-PYTHAGOREANISM...appeared during the first century B. C. [the faithful Jews were still clinging to their faith in a single one-person God, Jehovah the Father] in Rome, whence it traveled to Alexandria (the sect's chief center) where it flourished until Neo-Platonism absorbed it in the 3rd century A. D."  - Encyclopedia Americana, p. 98, v. 20, 1982 ed.

12. Weigall relates many instances of the trinity concept in pre-Christian pagan religions and then states: "The early Christians, however, did not at first think of applying the idea to their own faith." And, "Jesus Christ never mentioned such a phenomenon, and nowhere in the New Testament does the word `trinity' appear. The idea was only adopted by the Church three hundred years after the death of our Lord; and the origin of the conception is entirely pagan." - The Paganism in our Christianity, pp. 197,198, Arthur Weigall.

13. "If Paganism was conquered by Christianity, it is equally true that Christianity was corrupted by paganism. The pure Deism of the first Christians (who differed from their fellow Jews only in the belief that Jesus was the promised Messiah) was changed by the Church at Rome, into the incomprehensible dogma of the trinity. Many of the pagan tenets, invented by the Egyptians and idealized by Plato, were retained as being worthy of belief." - The History of Christianity, (Preface by Eckler).

14. "Christianity did not destroy Paganism; it adopted it .... From Egypt came the ideas of a divine trinity, …. the adoration of the Mother and Child…." – p. 595, The Story of Civilization: vol. 3, Simon & Schuster Inc., by noted author and historian Will Durant.

15. The Trinity "is a corruption borrowed from the heathen religions, and ingrafted on the Christian faith." - A Dictionary of Religious Knowledge

16. "When Newton was made a fellow of the College, along with an agreement to embrace the Anglican faith, the Trinity fellowship also required ordination within 8 years. During his studies Newton had come to believe that the central doctrine of the church, the Holy and Undivided Trinity was a pagan corruption imposed on Christianity in the fourth century by Athanasius." -Sir Isaac Newton And The Ocean of Truth; "Theology and the word of God"

Posted by Elijah Daniels

Mammalian hearing v. Darwin.

Mammals Compute Sound Timing in the Microsecond Range
Evolution News | @DiscoveryCSC

At a basic level, we all know that two ears give us the ability to detect the direction of a sound. Cover one ear, and it’s hard to tell. Uncover; we hear in stereo. But when you look into the physics of sound localization, the requirements are stringent.

Sound waves coming from the left hit your left eardrum only microseconds (millionths of a second) before they hit the right eardrum. Your ears must not only be able to capture that tiny difference in arrival time, but preserve the information through noisy channels on the way to the brain. And they must be able to do that continuously. Consider an ambulance siren moving left to right; the inter-aural time difference (ITD) is constantly changing. Your ears need to keep up with the microsecond-by-microsecond changes as they occur, without the prior information getting swamped by the new information.

Now consider being in an auditorium, listening to an orchestra with your eyes closed. You can tell where each instrument is located, even when they are playing together, just by the ITDs from each player. How amazing is that?

This can only work if the auditory system maintains the information all the way to the brain. The brain receives the timing differences after a delay: first, the eardrum converts pressure waves to membrane vibrations, which trigger mechanical movements of the middle ear bones (ossicles), which convert the mechanical motions into fluid waves in the cochlea, which converts the fluid waves to electrical impulses in the neurons. These things take time, but we’re still not there.

Each axon of each neuron has to cross synapses where the electrical information is converted to chemical information and back again in the next neuron. This is getting very complicated! There’s bound to be some noise in the transmission pathway. How can the ITD at the outer ear be maintained all the way to the brain through these multiple energy conversions?

Two neurobiologists from the Ludwig-Maximilian University of Munich, appreciating the problem of maintaining sound localization information, decided to run experiments on mice and gerbils. Think how much closer together those ears are than human ears! The smaller inter-aural distance compounds the problem, tightening the requirements even more. Under the news headline  “Auditory perception: where microseconds matter,” Drs. Grothe and Pecka announce what they found.

Gerbils (who depend on sound localization more than mice) use multiple mechanisms to maintain accurate ITD information in their sound transmission apparatus. The researchers explain the challenge:

In the mammalian auditory system, sound waves impinging on the tympanic membrane of the ear are transduced into electrical signals by sensory hair cells and transmitted via the auditory nerve to the brainstem. The spatial localization of sound sources, especially low-frequency sounds, presents the neuronal processing system with a daunting challenge, for it depends on resolving the difference between the arrival times of the acoustic stimulus at the two ears. The ear that is closer to the source receives the signal before the contralateral ear. But since this interval – referred to as the interaural timing difference (ITD) — is on the order of a few microseconds, its neuronal processing requires exceptional temporal precision. [Emphasis added.]

Grothe and Pecka, along with seven other colleagues, published the results of their research in an open-access paper in the Proceedings of the National Academy of Sciences  (PNAS). They report “a specific combination of mechanisms, which plays a crucial role in ensuring that auditory neurons can measure ITDs with the required accuracy.”

Back in 2015, the team observed structural modifications of the myelin sheaths wrapping the auditory nerves. The axons of these neurons, they also noted, were particularly thick. Discontinuities in the sheaths, coupled with the axon thickness, seemed to turbo-charge the neurons “to enable rapid signal transmission.” That’s necessary for sound localization, but it’s not enough. If the synapses introduce additional varying delays, you’ll just get faulty information transmitted faster. There must be something else going on. Here’s what they found this time:

Before cells in the auditory brainstem can determine the ITD, the signals from both ears must first be transmitted to them via chemical synapses that connect them with the sensory neurons. Depending on the signal intensity, synapses themselves can introduce varying degrees of delay in signal transmission. The LMU team, however, has identified a pathway in which the synapses involved respond with a minimal and constant delay. “Indeed, the duration of the delay remains constant even when rates of activation are altered, and that is vital for the precise processing of interaural timing differences,” Benedikt Grothe explains.

Specifically, the team discovered “stable synaptic delays” in the transmission neurons by a unique mechanism previously unknown in other neural circuits. Without a unique “inhibitory pathway” described in the paper, synapse transmission times would vary under continuous excitation, wiping out the ITD information. (This can happen, for instance, as a result of changes in vesicle abundance needed to carry the neurotransmitter molecules across a synapse.)

Functionally, stable synaptic delays seem to represent a specific adaptation for faithful ITD processing, because it would prevent fluctuations in the relative timing of direct excitation and indirect inhibition for responses to onsets vs. ongoing sounds in the range of tens to hundreds of microseconds. Such fluctuations may be negligible for most neuronal computations, but not for microsecond ITD processing of low-frequency sounds.

We now know the challenge; something needs to keep these synapses in a consistent readiness state, so that the crossing time delays are constant. One method might be buffering, so that enough vesicles are always at the ready. That’s one mechanism they observed, but not the only one. The solution also involves computation. There are two bodies at the receiving end, named the LSO and the MSO, that share information. The LSO deals with sound levels, and is less stringent about timing. The MSO, however, requires precise time information to calculate ITDs. By comparing one another’s inputs, the LSO and MSO can “detect coincidences between inputs from the two ears.” The authors note another “striking shared structural feature is the contralateral inhibitory pathway that is specialized for speed and reliability.”

That’s still not all. Two other structures upstream from the MSO are involved, but they cannot inhibit too much, or they, too, will introduce noise. So they, too, are finely tuned:

Recently we showed that the inhibitory pathway conquers this challenge via a two- to threefold thicker axon diameter of GBCs [globular bushy cells] compared with the spherical bushy cells, which comprise the excitatory input. Moreover, we revealed the presence of a dramatic decrease of internode length toward the terminal region in both fiber classes.

The details of these specializations need not concern us here. Suffice it to say that multiple mechanisms ensure that ITD information is preserved from eardrum to brain: structural properties of axon diameter and sheathing patterns, buffering of vesicles, and computation of differences between inputs received at the auditory cortex. No other part of the body requires this level of timing precision, and no other circuit achieves it.

For a real-world application of this need for precision, consider the echolocating bat. This creature darts about in the air, making sudden turns every second, listening to echoes from its high-frequency chirps. Research at Johns Hopkins finds that bats respond to a noisy environment by turning up the volume. We humans do that, too, but bats do it in 30 milliseconds: 10 times faster than the blink of an eye! That means that these little flying mammals, with ears much closer together than ours, are able to respond to the sound location information calculated from their ITDs extremely fast, while simultaneously operating their wings in a constantly changing auditory environment.

Our brief look into the complexity of auditory localization in mammals provides a good example of not only Behe’s irreducible complexity, but also what Douglas Axe calls functional coherence, “the hierarchical arrangement of parts needed for anything to produce high-level function — each part contributing in a coordinated way to the whole” (Undeniable, p. 144). None of these parts (MSO, myelin, synapses) perform sound localization individually, but collectively, they do.

We could explore the hierarchy further by looking more closely at how molecular machines within the neuron cells participate in the “functional whole” of sound localization. Taking the wide-angle view, we see how all the lower levels in the hierarchy contribute to the bat’s amazing ability to catch food on the wing. Functional coherence is not just beyond the reach of chance (Axe, p. 160), it provides positive evidence for intelligent design. In all our uniform human experience, only minds are capable of engineering complex, hierarchical systems exhibiting functional coherence. The complexity of this one circuit — sound localization — makes that loud and clear.

Good luck with that.

Falsify Intelligent Design? Try Simulating the Cambrian Explosion Digitally
David Klinghoffer | @d_klinghoffer

Want to falsify the theory of intelligent design? Here’s one way.

Show with a convincing computer simulation – no cheating allowed — that the infusion of biological information in the Cambrian explosion could occur absent the intervention of a guiding intelligence: artificial life in a variety as we see in the Cambrian event, but without design.

Researchers have tried, in multiple cases, as Introduction to Evolutionary Informatics author Winston Ewert tells biologist Ray Bohlin on a new episode of ID the Future. But each time, the simulations hit a “complexity barrier,” as the scientists themselves concede, and fail. It’s a fascinating conversation. Listen to it here, or download it here.

Ewert calls it “the mystery of the missing digital Cambrian explosion,” observing that “something is missing from all of the different artificial life simulations.” There’s a secret ingredient, and guess what that is? Intelligent design.

On the publish or perish syndrome.

Peer-Review and the Corruption of Science
Jonathan M. September 13, 2011 6:00 AM


The Guardian features an interesting opinion column by the renowned British pharmacologist David Colquhoun. The article bears the intriguing headline, "Publish-or-perish: Peer review and the corruption of science." The author laments that "Pressure on scientists to publish has led to a situation where any paper, however bad, can now be printed in a journal that claims to be peer-reviewed."

Colquhoun explains,

The blame for this sad situation lies with the people who have imposed a publish-or-perish culture, namely research funders and senior people in universities. To have "written" 800 papers is regarded as something to boast about rather than being rather shameful. University PR departments encourage exaggerated claims, and hard-pressed authors go along with them.
The author proceeds to list a few examples of the failure of the peer-review system to ensure robust and accurate journal content. He argues that part of the reason for the lapse in academic publication standards is the pressure on academics to publish many papers. If a scientist publishes frequently, that should actually call into question, rather than enhance, his credibility as a diligent and focused researcher.
Those of us who follow the professional literature (or even the blogosphere) may recall the Nowak et al. (2010) paper that appeared in Nature back in May of last year. It was regarded by many evolutionary biologists (most notably University of Chicago's Jerry Coyne) as a "misguided attack on kin selection."

Coyne noted,

If the Nowak et al. paper is so bad, why was it published? That's obvious, and is an object lesson in the sociology of science. If Joe Schmo et al. from Buggerall State University had submitted such a misguided paper to Nature, it would have been rejected within an hour (yes, Nature sometimes does that with online submissions!). The only reason this paper was published is because it has two big-name authors, Nowak and Wilson, hailing from Mother Harvard. That, and the fact that such a contrarian paper, flying in the face of accepted evolutionary theory, was bound to cause controversy.
I have often read papers, published in reputable journals, that I thought should not have passed through peer-review. Consider, for example, this paper, published in PLoS Biology in May of last year. Indeed, the esteemed atheist blogger PZ Myers wrote about it in a blog post headlined "Junk DNA is still junk" (to which I responded briefly here). The paper erroneously concluded "Overall, ...we find that most of the genome is not appreciably transcribed. [emphasis added]"
There is actually a pretty good response to this article here. The methodology of the PLoS Biology article is fatally flawed, for they use a program called "RepeatMasker", which screens out all the repetitive DNA. But given that about 50% of our genome is comprised of repetitive DNA, the conclusions drawn by the authors seems to be a little disingenuous to say the least! In fact, the official description of RepeatMasker itself states that "On average, almost 50% of a human genomic DNA sequence currently will be masked by the program."

As if that weren't bad enough, the researchers then base their results "primarily on analysis of PolyA+ enriched RNA." But we've known since 2005 that, in humans, PolyA- sequences are twice as abundant as PolyA+ transcripts. So the authors not only exclude half the genome from their research, but also completely ignore two thirds of the RNA in what remains!

By citing that paper PZ Myers didn't do his own credibility any favors. The point being made by Myers is a false one anyway because it is known that even DNA that is not transcribed can play important roles.

Then there was, of course, that recent paper in PNAS telling us that "There's plenty of time for evolution" (also paraded by Myers). The substance of the argument presented in this paper was terrible (for some of the reasons why, see here and here). Reading that paper when it came out, I was frankly astonished that it was able to pass through peer-review.

Back in June of 2009, a paper appeared in PNAS by Ghosh et al. purporting to demonstrate the production of endospores in the genus Mycobacterium (which includes many pathogens such as M. tuberculosis and M. leprae). Traag et al. (2010) document the problems with the paper:

Here, we report that the genomes of Mycobacterium species and those of other high G+C Gram-positive bacteria lack orthologs of many, if not all, highly conserved genes diagnostic of endospore formation in the genomes of low G+C Gram-positive bacteria. We also failed to detect the presence of endospores by light microscopy or by testing for heat-resistant colony-forming units in aged cultures of M. marinum. Finally, we failed to recover heat-resistant colony-forming units from frogs chronically infected with M. marinum. We conclude that it is unlikely that Mycobacterium is capable of endospore formation.
As ID proponents know only too well, the peer-review system has not only become corrupted in allowing substandard content into the academic market. It has also been turned into a gate-keeping system for imposing ideological conformity. Recently, an editor resigned over the publication of a seminal article by Roy Spencer and William Braswell. The paper's purpose was to demonstrate that one of the feedbacks that the Intergovernmental Panel on Climate Change has been treating as a positive feedback is really a negative feedback. You can read Roy Spencer's defense of his paper here.
In a similar incident in 2004, Smithsonian Institute evolutionary biologist Richard Sternberg was punished and pressured to resign following the publication of a pro-ID article by Stephen C. Meyer in a journal of which Sternberg was the editor.

In still another incident, a recent pro-ID paper authored by mathematician Granville Sewell was retracted from publication (after it had been subjected to peer-review and approved) as the result of a complaint from a blogger writing to the journal's editor. The journal, Applied Mathematics Letters has since apologized and paid $10,000 in compensation to Dr. Sewell.

What's to be done? Colquhoun makes the following recommendation:

There is an alternative: publish your paper yourself on the web and open the comments. This sort of post-publication review would reduce costs enormously, and the results would be open for anyone to read without paying. It would also destroy the hegemony of half a dozen high-status journals.
And, indeed, this is exactly how the Biologic Institute-associated journal Bio-Complexity operates. This peer-reviewed journal, dedicated to discussions surrounding the respective scientific merits of neo-Darwinian evolution and intelligent design, is published freely on the web and is open for comments and published responses, hence allowing -- even encouraging -- post-publication review.
Colquhoun further suggests,

...it would be essential to allow anonymous comments. Most reviewers are anonymous at present, so why not online? Second, the vast flood of papers that make the present system impossible should be stemmed. I'd suggest scientists should limit themselves to an average of two original papers a year. They should also be limited to holding one research grant at a time. Anyone who thought their work necessitated more than this would have to be scrutinized very carefully. It's well known that small research groups give better value than big ones, so that should be the rule.
The benefit of such a system, as Colquhoun notes, is that "With far fewer papers being published, reviewers, grant committees and promotion committees might be able to read the papers, not just count them."

Colquhoun is to be commended. The goal of the peer-review system ought to be the ensuring of factual accuracy and the highlighting of necessary revisions and corrections. Its goal should not be the enforcement of ideological and paradigmatic conformity, nor should it be the upholding of "consensus science." Post-publication review ought to be encouraged, and moves should be made to make journal content more frequently open-access.

File under "well said" L

Only a virtuous people are capable of freedom. As nations become corrupt and vicious, they have more need of masters.

BENJAMIN FRANKLIN,

Still yet more on Maths v. Darwin.

Top Ten Questions and Objections to Introduction to Evolutionary Informatics
Robert J. Marks II

Five years ago, Gregory Chaitin, a co-founder of the fascinating and mind-bending field of algorithmic information theory, offered a challenge:1

The honor of mathematics requires us to come up with a mathematical theory of evolution and either prove that Darwin was wrong or right!

In  Introduction to Evolutionary Informatics2, co-authored by William A. Dembski, Winston Ewert, and myself, we answer Chaitin’s challenge in the negative: There exists no model successfully describing undirected Darwinian evolution. Period. By “model,” we mean definitive simulations or foundational mathematics required of a hard science.

We show that no meaningful information can arise from an evolutionary process unless that process is guided. Even when guided, the degree of evolution’s accomplishment is limited by the expertise of the guiding information source — a limit we call Basener’s ceiling. An evolutionary program whose goal is to master chess will never evolve further and offer investment advice.

Here I answer ten frequently posed questions about and objections to Introduction to Evolutionary Informatics.

1. Why yet another book dissing Darwinian evolution?

Solomon was right. “Of making many books there is no end, and much study wearies the body.”3 There are gobs of books written about evolution, pro and con. Many are excellent. So what’s so important about Introduction to Evolutionary Informatics? On the topic of evolution, the conclusion is in: There exists no model successfully describing undirected Darwinian evolution. Hard sciences are built on foundations of mathematics or definitive simulations. Examples include electromagnetics, Newtonian mechanics, geophysics, relativity, thermodynamics, quantum mechanics, optics, and many areas in biology. Those hoping to establish Darwinian evolution as a hard science with a model have either failed or inadvertently cheated. These models contain guidance mechanisms to land the airplane squarely on the target runway despite stochastic wind gusts. Not only can the guiding assistance be specifically identified in each proposed evolution model, its contribution to the success can be measured, in bits, as active information.

And, as covered in Introduction to Evolutionary Informatics, we suspect no model will ever exist to substantiate the claims of undirected Darwinian evolution.

2. But Darwinian evolution is so complicated, it can’t be modeled!

If this objection is true, we have reached the same conclusion by different paths: There exists no model successfully describing undirected Darwinian evolution.

3. You model evolution as a search. Evolution isn’t a search.

We echo Billy Joel: “We didn’t start the fire!” Models of Darwinian evolution, Avida and EV included, are searches with a fixed goal. For EV, the goal is finding specified nucleotide binding sites. Avida’s goal is to generate an EQU logic function. Other evolution models that we examine in Introduction to Evolutionary Informatics likewise seek a prespecified goal.

The evolution software Avida is of particular importance because Robert Pennock, one of the co-authors of the first paper describing Avida,4 gave testimony at the Darwin-affirming Kitzmiller et al. v. Dover Area School District bench trial. Pennock’s testimony contributed to Judge Jones’s ruling that teaching about intelligent design violates the establishment clause of the United States Constitution. Pennock testified, “In the [Avida computer program] system, we’re not simulating evolution. Evolution is actually happening.” If true, Avida and thus evolution are a guided search with a specified target bubbling over with active information supplied by the programmers.

The most celebrated attempt of an evolution model without a goal of which we’re aware is TIERRA. In an attempt to recreate something like the Cambrian explosion on a computer, the programmer created what was thought to be an information-rich environment where digital organisms would flourish and evolve. According to TIERRA’s ingenious creator, Thomas Ray, the project failed and was abandoned. There has to date been no success in open-ended evolution in the field of artificial life.5

Therefore, there exists no model successfully describing undirected Darwinian evolution.

4. You are not biologists. Why should anyone listen to you about evolution?

Leave aside that this question reeks of the genetic fallacy used in debate to steer conversation away from the topic at hand and down a rabbit trail of credential defense. The question is sincere, though, and deserves an answer. Besides, it lets me talk about myself.

The truth is that computer scientists and engineers know a lot about evolution and evolution models.

As we outline in Introduction to Evolutionary Informatics, proponents of Darwinian evolution became giddy about computers in the 1960s and 70s. Evolution was too slow to demonstrate in a wet lab, but thousands and more generations of evolution can be put in the bank when Darwinian evolution is simulated on a computer. Computer scientists and engineers soon realized that evolutionary search might assist in making computer-aided designs. In Introduction to Evolutionary Informatics, we describe how NASA engineers used guided evolutionary programs to design antennas resembling bent paper clips that today are floating and functioning in outer space.

Here’s my personal background. I first became interested in evolutionary computation late last century when I served as editor-in-chief of the IEEE6 Transactions on Neural Networks.7 I invited top researchers in the field, David Fogel and his father Larry Fogel, to be the guest editors of a special issue of my journal dedicated to evolutionary computing.8 The issue was published in January 1994 and led to David founding the IEEE Transactions on Evolutionary Computing9 which today is the top engineering/computer science journal dedicated to the topic.

My first conference paper using evolutionary computing was published a year later10 and my first journal publication on evolutionary computation was in 1999.11 That was then. More recently my work, funded by the Office of Naval Research, involves simulated evolution of swarm dynamics motivated by the remarkable self-organizing behavior of social insects. Some of the results were excitingly unexpected12 including individual member suicidal sacrifice to extend the overall lifetime of the swarm.13 Evolving digital swarms is intriguing and we have a whole web site devoted to the topic.14

So I have been playing in the evolutionary sandbox for a long time and have dirt under my fingernails to prove it.

But is it biology? In reviewing our book for the American Scientific Affiliation (ASA), my friend Randy Isaac, former executive director of the ASA, said of our book, “Those seeking insight into biological or chemical evolution are advised to look elsewhere.”15 We agree! But if you are looking for insights into the models and mathematics thus far proposed by supporters of Darwinian evolution that purport to describe the theory, Introduction to Evolutionary Informatics is spot on. And we show there exists no model successfully describing undirected Darwinian evolution.

5. You use probability inappropriately. Probability theory cannot be applied to events that have already happened.

In the movie Dumb and Dumber, Jim Carey’s character, Lloyd Christmas, is brushed off by beautiful Mary “Samsonite” Swanson when told his chances with her are one in a million. After a pause for introspective reflection, Lloyd’s emergent toothy grin shows off his happy chipped tooth. He enthusiastically blurts out, “So you’re telling me there’s a chance!” Similar exclamations are heard from Darwinian evolutionist advocates. “Darwinian evolution. So you’re telling me there’s a chance!” So again, we didn’t start the probability fire. Evolutionary models thrive on randomness described by probabilities.

The probability-of-the -gaps championed by supporters of Darwinian evolution is addressed in detail in Introduction to Evolutionary Informatics. We show that the probability resources of the universe and even string theory’s hypothetical multiverse are insufficient to explain the specified complexity surrounding us.

Besides, a posteriori probability is used all the time. The size of your last tweet can be measured in bits. Claude Shannon, who coined the term bits in his classic 1948 paper,16 based the definition of the bit on probability. Yet there sits your transmitted tweet with all of its a posteriori bits fully exposed. Another example is a posteriori Bayesian probability commonly used, for example, in email spam filters. What is the probability that your latest email from a Nigerian prince, already received and written on your server, is spam? Bayesian probabilities are also a posteriori probabilities.

So a hand-waving dismissal of a posteriori probabilities is ill-tutored. The application of probability in Introduction to Evolutionary Informatics is righteous and the analysis leads to the conclusion that there exists no model successfully describing undirected Darwinian evolution.

6. What about a biological anthropic principle? We’re here, so evolution must work.

Stephen Hawking has a simple explanation of the anthropic principle: “If the conditions in the universe were not suitable for life, we would not be asking why they are as they are.” Gabor Csanyi, who quotes from Hawking’s talk, says, “Hawking claims, the dimensionality of space and amount of matter in the universe is [a fortuitous] accident, which needs no further explanation.”17

“So you’re telling me there’s a chance!”

The question ignored by anthropic principle enthusiasts is whether or not an environment for even guided evolution could occur by chance. If a successful search requires equaling or exceeding some degree of active information, what is the chance of finding any search with as good or better performance? We call this a search-for-the-search. In Introduction to Evolutionary Informatics, we show that the search-for-the-search is exponentially more difficult that the search itself! So if you kick the can down the road, the can gets bigger.

Professor Sydney R. Coleman said after the Hawking’s MIT talk, “Anything else is better [than the ‘Anthropic Principle’ to explain something].”18 We agree. For example, check out our search-for-the-search analysis in Introduction to Evolutionary Informatics.

7. What about the claim that “All information is physical”?

This is a question we have heard from physicists.

In physics, Landauer’s principle pertains to the lower theoretical limit of energy consumption of computation and leads to his statement “all information is physical.”

Saying “All computers are mass and energy” offers a similar nearly useless description of computers. Like Landauer’s principle, it suffers from the same overgeneralized vagueness and is at best incomplete.

Claude Shannon counters Landauer’s claim:

It seems to me that we all define “information” as we choose; and, depending upon what field we are working in, we will choose different definitions. My own model of information theory…was framed precisely to work with the problem of communication.19

Landauer is probably correct within the narrow confines of his physics foxhole. Outside the foxhole is Shannon information which is built on unknown a priori probability of events which have not yet happened and are therefore not yet physical.

We spend an entire chapter in Introduction to Evolutionary Informatics defining information so there is no confusion when the concept is applied. And we conclude there exists no model successfully describing undirected Darwinian evolution.

8. Information theory cannot measure meaning.

Poppycock.

A hammer, like information theory, is a tool. A hammer can be used to do more than pound nails. And information theory can do more than assign a generic bit count to an object.

The most visible information theory models are Shannon information theory and KCS information.20 The consequence of Shannon’s theory on communication theory is resident in your cell phone where codes predicted by Shannon today allow maximally efficient use of available bandwidth. KCS stands for Kolmogorov-Chaitin-Solomonoff information theory named after the three men who independently founded the field. KCS information theory deals with the information content of structures. (Gregory Chaitin, by the way, gives a nice nod-of-the-head to Introduction to Evolutionary Informatics.21)

The manner in which information theory can be used to measure meaning is addressed in Introduction to Evolutionary Informatics. We explain, for example, why a picture of Mount Rushmore containing images of four United States presidents has more meaning to you than a picture of Mount Fuji even though both pictures might require the same number of bits when stored on your hard drive. The degree of meaning can be measured using a metric called algorithmic specified complexity.

Rather than summarize algorithmic specified complexity derived and applied in Introduction to Evolutionary Informatics, we refer instead to a quote from a paper from one of the world’s leading experts in algorithmic information theory, Paul Vitányi. The quote is from a paper he wrote over 15 years ago, titled “Meaningful Information.”22

One can divide…[KCS] information into two parts: the information accounting for the useful regularity [meaningful information] present in the object and the information accounting for the remaining accidental [meaningless] information.23

In Introduction to Evolutionary Informatics, we use information theory to measure meaningful information and show there exists no model successfully describing undirected Darwinian evolution.

9. To achieve specified complexity in nature, the fitness landscape in evolution keeps changing. So, contrary to your claim, Basener’s ceiling doesn’t apply in Darwinian evolution.

In search, complexity can’t be achieved beyond the expertise of the guiding oracle. As noted, we refer to this limit as Basener’s ceiling.24 However, if the fitness continues to change, it is argued, the evolved entity can achieve greater and greater specified complexity and ultimately perform arbitrarily great acts like writing insightful scholarly books disproving Darwinian evolution.

We analyze exactly this case in Introduction to Evolutionary Informatics and dub the overall search structure stair step active information. Not only is guidance required on each stair, but the next step must be carefully chosen to guide the process to the higher fitness landscape and therefore ever increasing complexity. Most of the next possible choices are deleterious and lead to search deterioration and even extinction. This also applies in the limit when the stairs become teeny and the stair case is better described as a ramp. As Aristotle said, “It is possible to fail in many ways…while to succeed is possible only in one way.”

Here’s an anecdotal illustration of the careful design needed in the stair step model. If a meteor hits the Yucatan Peninsula and wipes out all the dinosaurs and allows mammals to start domination of the earth, then the meteor’s explosion must be a Goldilocks event. If too strong all life on earth would be zapped. If too weak, velociraptors would still be munching on stegosaurus eggs.

Such fine tuning is the case of any fortuitous shift in fitness landscapes and increases, not decreases, the difficulty of evolution of ever-increasing specified complexity. It supports the case there exists no model successfully describing undirected Darwinian evolution.

10. Your research is guided by your ideology and can’t be trusted.

There’s that old derailing genetic fallacy again.

But yes! Of course, our research is impacted by our ideology! We are proud to be counted among Christians such as the Reverend Thomas Bayes, Isaac Newton, George Washington Carver, Michael Faraday, and the greatest of all mathematicians, Leonard Euler.25 The truth of their contributions stand apart from their ideology. But so does the work of atheist Pierre-Simon Laplace. Truth trumps ideology. And allowing the possibility of intelligent design, embraced by enlightened theists and agnostics alike, broadens one’s investigative horizons.

Alan Turing, the brilliant father of computer science and breaker of the Nazi’s enigma code, offers a great example of the ultimate failure of ideology trumping truth. As a young man, Turing lost a close friend to bovine tuberculosis. Devastated by the death, Turing turned from God and became an atheist. He was partially motivated in his development of computer science to prove man was a machine and consequently that there was no need for a god. But Turing’s landmark work has allowed researchers, most notably Roger Penrose,26 to make the case that certain of man’s attributes including creativity and understanding are beyond the capability of the computer. Turing’s ideological motivation was thus ultimately trashed by truth.

The relationship between human and computer capabilities is discussed in more depth in Introduction to Evolutionary Informatics.

Take Aways

In Introduction to Evolutionary Informatics, Chaitin’s challenge has been met in the negative and there exists no model successfully describing undirected Darwinian evolution. According to our current understanding, there never will be. But science should never say never. As Stephen Hawking notes, nothing in science is ever actually proved. We simply accumulate evidence.27

So if anyone generates a model demonstrating Darwinian evolution without guidance that ends in an object with significant specified complexity, let us know. No guiding, hand waving, extrapolation of adaptations, appealing to speculative physics, or anecdotal proofs allowed.

Until then, I guess you can call us free-thinking skeptics.

Thanks for listening.

Robert J. Marks II PhD is Distinguished Professor of Electrical and Computer Engineering at Baylor University.

Notes:

(1) Chaitin, Gregory. Proving Darwin: Making Biology Mathematical. Vintage, 2012.

(2) Marks II, Robert J., William A. Dembski, and Winston Ewert. Introduction to Evolutionary Informatics. World Scientific, 2017.

(3) Ecclesiastes 12:12b.

(4) Lenski, R.E., Ofria, C., Pennock, R.T. and Adami, C., 2003. “The evolutionary origin of complex features.” Nature, 423(6936), pp. 139-144.

(5) ID the Future podcast with Winston Ewert. “Why Digital Cambrian Explosions Fizzle…Or Fake It,” June 7, 2017.

(6) IEEE, the Institute of Electrical and Electrical Engineers, is the largest professional society in the world, with over 400,000 members.

(7) R.J. Marks II, “The Joumal Citation Report: Testifying for Neural Networks,” IEEE Transactions on Neural Networks, vol. 7, no. 4, July 1996, p. 801.

(8) Fogel, David B., and Lawrence J. Fogel. “Guest editorial on evolutionary computation,” IEEE Transactions on Neural Networks 5, no. 1 (1994): 1-14.

(9) R.J. Marks II, “Old Neural Network Editors Don’t Die, They Just Prune Their Hidden Nodes,” IEEE Transactions on Neural Networks, vol. 8, no. 6 (November, 1997), p. 1221.

(10) Russell D. Reed and Robert J. Marks II, “An Evolutionary Algorithm for Function Inversion and Boundary Marking,” Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 794-797, November 26-30, 1995.

(11) C.A. Jensen, M.A. El-Sharkawi and R.J. Marks II, “Power Security Boundary Enhancement Using Evolutionary-Based Query Learning,” Engineering Intelligent Systems, vol. 7, no. 9, pp. 215-218 (December 1999).

(12) Jon Roach, Winston Ewert, Robert J. Marks II and Benjamin B. Thompson, “Unexpected Emergent Behaviors from Elementary Swarms,” Proceedings of the 2013 IEEE 45th Southeastern Symposium on Systems Theory (SSST), Baylor University, March 11, 2013, pp. 41-50.

(13) Winston Ewert, Robert J. Marks II, Benjamin B. Thompson, Albert Yu, “Evolutionary Inversion of Swarm Emergence Using Disjunctive Combs Control,” IEEE Transactions on Systems, Man and Cybernetics: Systems, v. 43, #5, September 2013, pp. 1063-1076.

Albert R. Yu, Benjamin B. Thompson, and Robert J. Marks II, “Swarm Behavioral Inversion for Undirected Underwater Search,” International Journal of Swarm Intelligence and Evolutionary Computation, vol. 2 (2013). Albert R. Yu, Benjamin B. Thompson, and Robert J. Marks II, “Competitive Evolution of Tactical Multiswarm Dynamics,” IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 43, no. 3, pp. 563- 569 (May 2013).

Winston Ewert, Robert J. Marks II, Benjamin B. Thompson, Albert Yu, “Evolutionary Inversion of Swarm Emergence Using Disjunctive Combs Control,” IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 43, no. 5, September 2013, pp. 1063-1076.

(14) NeoSwarm.com.

(15) Review of Introduction to Evolutionary Informatics, Perspectives on Science and Christian Faith, vol. 69 no. 2, June 2017, pp. 104-108.

(16) Claude E. Shannon, “A mathematical theory of communication,” Bell System Technical Journal 27: 379-423 and 623–656.

(17) Gabor Csanyi “Stephen Hawking Lectures on Controversial Theory,” The Tech, vol. 119, issue 48, Friday, October 8, 1999.

(18) The bracketed insertion in the quote is Csanyi’s, not ours.

(19) Quoted in P. Mirowski, Machine Dreams: Economics Becomes a Cyborg Science (New York: Cambridge University Press, 2002), 170.

(20) Cover, Thomas M., and Joy A. Thomas. Elements of Information Theory. John Wiley & Sons, 2012.

(21) Review for Introduction to Evolutionary Informatics.

(22) Paul Vitányi, “Meaningful Information,” in International Symposium on Algorithms and Computation: 13th International Symposium, ISAAC 2002, Vancouver, BC, Canada, November 21-23, 2002.

(23) Unlike our approach, Vitányi’s use of the so-called Kolmogorov sufficient statistic here does not take context into account.

(24) Basener, W.F., 2013. “Limits of Chaos and Progress in Evolutionary Dynamics.” Biological Information — New Perspectives. World Scientific, Singapore, pp. 87-104.

(25) Christian Calculus.

(26) See, e.g., Penrose, Roger. Shadows of the Mind. Oxford University Press, 1994.

(27) Hawking, Stephen. A Brief History of Time (1988). AppLife, 2014.