Design inference Functionally Specified Complex Information & Organization ID Foundations Intelligent Design

“I’ve grown accustomed to your face . . . ” — headlining a comment by ayearningforpublius to pose the question of origin of a significant case of FSCO/I . . . functionally specific, complex organization and/or associated information

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New UD commenter ayearningforpublius has put up a comment on the implications of facial recognition, several times. I think it significant enough as a case of FSCO/I and the challenge of addressing its origin, to headline it. But first, let’s put up the vid clip he links:

embedded by Embedded Video

YouTube Direkt

Now, his remarks:


>> The following scenario is familiar to most of us, particularly as we grow older:

We walk into a crowded and noisy room full of mostly strangers and unfamiliar heads bobbing up and down. Then off to the side and slightly behind we hear and recognize a familiar voice … we turn our head searching for that old friend we know is there, and after a short search … there she is, head slightly turned away from our view, but recognizable none-the-less. We are surprised and pleased to meet our old friend once more after some number of years and begin renewing the friendship.

The recognition of the voice and face is instinctive and very quick; and we take it for granted with no thoughts of anything unusual other than the mere co-incidence of the meeting.

But behind the scenes in our ears, eyes, nerves and brains is a marvelous and miraculous process called pattern recognition. A pattern recognition that is able to pick out and recognize individual faces and voices out of the billions of faces and voices surrounding us in the world. So let’s take a brief tour of what’s involved in meeting up with our old friend.

The hearing system that most of us have is a partnership between our ears and brain along with the connecting nerves between the two. This stereo audio system is able to sift through the many amplitudes (volumes) presented – the multitudes of widely spread and finely differentiated frequencies – the various timbres presented by the many voices surrounding us in that room full of strangers. And we are able to pick out that distinctive and familiar voice among the multitudes. And by the way, that same set of ears, in the form of the semi-circular canals, is instrumental in our balance system which keeps us from stumbling around in that crowded room.

And the eyes … my gosh what a gift … a gift of obvious design which enables us to stand in awe at the many wonders of our everyday world.

The eyes, as with the ears, are continually involved in a massive process of pattern recognition that allow us to function smoothly within our very busy, active and dangerous world. Eyes that are quick to warn us of the dangers of that car moving too close to us on the freeway. Eyes that quickly recognize that old friend even in a crowded and busy room.

In our modern technological world we have analogies to that busy room. Our Navy ships scan the depths of the ocean with sonar. The pulses transmitted from the sonar antenna bounce off; the ocean floor, schools of fish and even the surface of the ocean, returning a bewildering stream of noise that the computers of the sonar must sift through, filter and cluster to present the operators and commanders an array of potential hazards and threats to the fleet. These sophisticated sonar system require sophisticated computational systems and large amounts of memory storage to accomplish the task in real-time. But most fundamentally they require intelligent designers to create the systems required.

Pattern recognition in the visual world is no less wondrous. When you take a picture of that group at a reunion with a modern state of the art camera, have you noticed the little boxes surrounding the faces? Somehow some very smart scientists and engineers have figured out how to program a computer in your camera to recognize that human faces are part of the picture and visually highlight them for you. And after you take them you can ‘tag’ the individual faces with names in programs like Facebook. Again, sophisticated computational power and large amounts of memory storage are required for the job. And, as in the case of sonar processing, intelligent designers are necessary to create the systems required.

Pattern recognition is not a trivial task in the engineering world. Take the time to read about the complexities and mathematics of pattern recognition, for example a Wikipedia article on “pattern recognition.”

So I ask you my friends who believe that Darwinian Evolution … a belief in unguided, unintelligent and strictly natural processes; is it reasonable and rational that such a process could guide you to that reunion in a crowded room? Can you really believe that? Can you set aside your dogmatic atheism and look at what nature presents to you?
You atheists at NCSE [–> this seems to be a remark he has shared at NCSE, we would like the link, it does not come up easily in web searches . . . ] need to apply real science to the multitudes of designs all around us and within us. Science that takes an honest researcher to wherever the evidence leads. Evidence like I have cited above, evidence that is obvious even to a sea-going corporal. Take the leap and cast off your irrational atheism and discover the secrets of the designs you so flippantly cast aside as illusions or false appearances. Many of you have PhDs, but have not the common sense that should go with it.

And to those of you who denigrate and insult those of us who believe such natural capabilities are the result of an Intelligent Design (ID), I would ask … which of us is the IDiot?

I put this scenario up before the folks at NCSE recently, and it sparked quite an exchange between myself and NCSE friendly commenters. Interestingly, even though my post asks for Darwinian explanations and evidence for the scenario I presented (including evidence for the evolution of vision), no one stepped up to the challenge. If you read the responses you get the usual stuff about ID being religion etc.

So I continue to wonder about that “mountain of overwhelming evidence.” I don’t see it. What I do see is a relatively small set of bones and rocks with the supposed connecting dots of evolution.>>


Mapou’s remark in response was:

Nice piece, even if off topic. As someone who does research in AI, especially in visual and auditory pattern recognition, I know that there is no way this capability could have evolved by chance and natural selection. One of the hardest unsolved problems in computer science is the so-called cocktail party problem, the ability to recognize and focus on a single voice or sound in a noisy environment. The brain handles it with ease. During REM sleep, there is a mechanism that goes through the brain’s cortex and cleans up any bad synaptic connection that was acquired during the day. If that did not happen, we would lose our ability to see and hear within days and likely go mad. You cannot design a sophisticated pattern recognition system such as exists in the brain without knowing in advance that you will need a sleep-activated cleanup mechanism and why it is necessary.

So, how do we explain such on evolutionary materialist, chance and necessity terms, without begging questions through a priori impositions. END

16 Replies to ““I’ve grown accustomed to your face . . . ” — headlining a comment by ayearningforpublius to pose the question of origin of a significant case of FSCO/I . . . functionally specific, complex organization and/or associated information

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  2. 2
    johnp says:

    Facial memory obviously evolved as a child/parent survival advantage, so that the parent could recognize their progeny and visa-versa, enabling them to nourish and protect them…

    Oh wait. That would be putting the cart (the need for facial recognition) before the horse (blind and unguided evolution). Hmmmmm…

    Anyone? Anyone?

  3. 3
    fifthmonarchyman says:

    I am constantly amazed at the human capacity for pattern recognition. It’s what makes us who we are.

    Computers can handle tons of more data than we could ever hope to but somehow we are better able to filter through tons of garbage quickly and find the penny.

    ID is really about this ability. We have an innate idea of the sort of pattern we expect an intelligent agent to produce and when we see it we infer design.

    I’m skeptical that we will ever be able to completely reduce this ability to an algorithm.


  4. 4

    Yes indeed, I do have comments – several!

    First – I am flattered that you would headline my post and that you consider the scenario significant. By the way, I’m not familiar with the term FSCO/I.

    Second – Thanks to Mapou for his remarks, I’ve looked briefly at his web site and intend to revisit in the near future.

    Third – My use of the sonar analogy is from a very early experience in my software development career – a long time ago, but I still recall the basics:

    I was working at a Navy lab in San Diego on a project that was building a prototype for the Advanced Lightweight Torpedo. I was a very junior computer programmer carrying water for some really smart folks.
    These folks put acoustic pattern recognition, and more, into a very small torpedo sized package, and I was fortunate to witness mush of this amazing development.
    I’ll skip the part of generating the sonar pulse and go to the receive processing as much as I can recall.
    First of all, the returning signals from the pulse came from a variety of sources; – reverberation from the ocean bottom, the ocean surface, and from the volume of water containing the pulse; – discrete signal sources such as schools of fish, rocks and other underwater terrain features; and lastly the potential targets.
    I was not then, nor have I ever been, an acoustics engineer, but I can appreciate the knowledge that was behind the algorithms used in this processing.
    The surface, volume and bottom reverberation filtering I suspect was the easy part, maybe as simple as filtering out particular frequency bands as noise.
    The discrete object filtering however, I suspect took some very sophisticated algorithms in order to separate out fish, rocks etc. from the potential targets.
    Once the noise was for the most part filtered out, what was left was a set of discrete, and potential targets.
    The next step, as I recall, was called ‘clustering’ where returns in close proximity to one another were combined into single discrete items.
    I don’t recall, these many years later what was next, but there was probably a ‘tactical’ set of algorithms that analyzed such attributes as motion, size, dispersions over time etc. in order to pick the most likely target.

    Mind you, this was all done in the confines of a torpedo shell using 1970s vintage computer technology. And, the returned sonar data was recorded and the engineers and scientists were able to replay, analyze and tweak the algorithms.

    I tell this sonar story because it shows to some extent, the knowledge, design and implementation (manufacturing) necessary to solve a problem similar to the ‘cocktail party problem’ and my ‘reunion in a busy room’ scenario. And it shows the extreme unlikelihood that such capabilities can happen as a result of purely naturalistic causes – and yet each of us has that same capability.

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    scordova says:

    Excellent post!

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    kairosfocus says:


    I thought the issue is significant, for much the same reasons. Let’s just say that underwater acoustics is a big part of the history of digital signal processing, and that the cetaceans got to acoustic signal processing and “imaging” first (though it seems their processing is essentially analogue . . . and the USN’s Ford Instrument Co built Fire Control computers for surface ships give us an idea of how complicated that was).

    And yes, this is part of how do you design a successful whale or dolphin, step by blind incremental step where 6 – 7 co-ordinated gene changes is pretty much an upper limit for step size. Multiply by reasonable generation times, population sizes and mutation rates, and see where that gets us in the time said to be available. I bet you are going to be well up in the hundreds of millions of years real fast, especially once we start to look at what it takes to turn a cow or a wolf or a bear or the like into a whale.


    PS: FSCO/I is short for functionally specific complex organisation and/or associated information. Algorithmic code is like that, and so are blueprints and their digital form, etc. So is text in a language like this post. Beyond a threshold of 500 – 1,000 bits of complexity the atomic resources of our solar system or our observed cosmos are not plausible as sources. To see why, at the low end convert the 10^57 atoms of the sol system into observers of states for strings of 500 coins, and make afresh observation every 10^-14 s for 10^17 s, and see the fraction of the config space of possibilities for 500 coins, 3.27*10^150, can be scanned. The answer is comparable to making a sample of one straw size from a cubical haystack 1,000 light years across, as thick as the central bulge of our galaxy. 10^17 s is a reasonable estimate of time available for the sol system. The only empirically warranted entity to generate FSCO/I is design.

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    kairosfocus says:

    PPS: and that 100’s of MY educated guess is ASSUMING there is a smooth incremental path from a plausible source animal to a fully loaded dolphin etc.

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    Querius says:

    Sounds like the “fully loaded dolphin” and many others of her kind shopped at the same Convergent EvoMart. 😉


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    kairosfocus says:

    Q, like her friend the micro-bat who went for the very same genetic complement:

    two new studies in the January 26th issue of Current Biology, a Cell Press publication, show that bats’ and whales’ remarkable [[sonar echolocation] ability and the high-frequency hearing it depends on are shared at a much deeper level than anyone would have anticipated — all the way down to the molecular level.

    “The natural world is full of examples of species that have evolved similar characteristics independently, such as the tusks of elephants and walruses,” said Stephen Rossiter of the University of London, an author on one of the studies. “However, it is generally assumed that most of these so-called convergent traits have arisen by different genes or different mutations. Our study shows that a complex trait — echolocation — has in fact evolved by identical genetic changes in bats and dolphins.”

    A hearing gene known as prestin in both bats and dolphins (a toothed whale) has picked up many of the same mutations over time, the studies show. As a result, if you draw a phylogenetic tree of bats, whales, and a few other mammals based on similarities in the prestin sequence alone, the echolocating bats and whales come out together rather than with their rightful evolutionary cousins.

    Both research teams also have evidence showing that those changes to prestin were selected for, suggesting that they must be critical for the animals’ echolocation for reasons the researchers don’t yet fully understand.

    Miracles of “natural selection.”


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    Thanks for your reply and the amplification. And thanks for the link to the fire control computers – had you read my article – My Very First Computer at ?

    Also, yesterday I challenged the 5000+ members of NCSE to Google or Bing the term “cocktail party problem” and look for evolutionary explanations and evidence and then report back those results along with the sources.

    Well it looks as if you have beaten them to the punch with the article in Current Biology. I’ve read the article, and remain quite skeptical even though I am not a biologist – but I have learned over the years to look for key phrases in such reports such as: “suggests that …” “might be … ” “it is generally assumed …” “for reasons the researchers don’t yet fully understand … ” “The results imply that … ” “our findings suggest … ” etc.

    Also, the article seems light on the systems aspect of such a trait as echo-location … systems aspects such as the ‘stereo’ effect of two ears, the synergy of the brain and probable multiple areas of the brain, and also the interconnecting nervous system which ties the various pieces together as a fully functional system.

    In other words, the report seems to rely to heavily on individual common parts rather that the system as a whole.

    Mind you, I am speaking entirely from the point of view of a layman in the field – the son of an immigrant TV repairman from Butte Montana, but sometimes I think such a vantage point might be useful in the discussion.

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    kairosfocus says:


    Way back, we briefly studied analogue computers as part of systems engineering, with emphasis on electronic analogue computers. Where of course anything capable of being rendered as differential equations can then be fed in principle into a suitably patched up set of integrators with pots, diode function generators etc, to solve.

    Your babies were electromechanical. The ball summer pressed against a rotating disk and all that. Then feed off to some summing shaft and onwards.

    Synchros then mimic positions and do the pointing, in a servosystem. A pioneering one.

    My stuff was also in the context of control systems.

    I defy anyone to give us a blind mechanism incrementalist account, with suitable empirical backup, that solves the whale’s noisy environment, 3-d imaging sonar problem!


    PS: Nice article. I thought it was a stable vertical that gyroscope was? Did terminology change? (And what about the gyro-based predicting director for the light 40 mm AA batteries?)

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    kairosfocus says:

    PPS: If the fire direction controller machine was liable to need regular field maintenance, you bet there would have been a specialist class for that. I suspect it was a case of periodic factory tech recalibration and maintenance, with over-built components.

    PPPS: Ever looked up the Dreyer Table remote ancestor?

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    All this was way back in 1965-66 and I’m amazed I remember anything at all. The computer was the Mk-1A, and the director was a Mk-37.
    “Dreyer Table remote ancestor” No, but I sure will look it up now.

    You know kariosfocus, my Navy experience is way – way back there, but in recent years I’ve been rekindling an interest in those days. If you are interested, click on ‘Navy’ under ‘Categories’ on my web site. Also, I am working on a book about the life and times of living on a destroyer (tin can) will let you know when it’s done.

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    kairosfocus says:


    First, Dreyer. (The Capt of that name was Jellicoe’s Captain on HMS Iron Duke at Jutland, and would later become an Admiral in his own right.)

    These fire control systems are examples of what is required to do something exacting and functionally specific. In the case of the Ford computer, you are talking about an electromechanical integrator that in effect executed a set of differential equations, solving them through successive, coordinated integration. This, to solve a 2 – 3 dimensional ballistics problem, by your time with I think ability to direct guns to 400 mph targets moving at high tangential rates in 3-D requiring serious solutions on deflection.

    The point is, here is how we found out a lot about analogue computing, which is probably fairly closely linked to the sort of targetting problems Whales have to solve.

    I know they make mistakes — I once saw a Dolphin (one that starred as Flipper) fall on his trainer while trying to leap over her. Serious hit from a 300 lb animal.

    But at the same time, it could distinguish and pick up and return a small bit of coral tossed in a fetch exercise, and return it to the trainer, making the problem look easy.

    The sound processing involved is awesome, and it is clear that they are able to tell what they are “looking at” and pick it out from the background. Their ability to catch fish etc is legendary.

    Now, how do we go about building a whale, one small step at a time, incrementally improving all the way [so selected], within reasonable timelines per what is claimed, as a signal processing ballistic computer embedded in a submarine that is at the same time a mammal living 100% of the time in the salty ocean (with some exceptions). With realistic pop sizes, breeding rates, mutation rates etc.

    And, obviously, there are going to be thousands of intermediates.

    Where are the step by step incremental traces, as these intermediates should dominate the picture. And what are the reasonable steps, backed by empirical evidence of the capacity of blind chance and mechanical necessity acting through chance variation and loss of inferior varieties to do the job — without imposing question begging a priori materialism that begs the question, on assertions about natural vs supernatural.

    In short, show cause per empirical evidence that FSCO/I manifest in new body plans can and does arise incrementally by the Darwinist type processes.

    And the case of whales is just one of many cases.


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    (And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … And then a miracle happens … ) raised to the umpteenth power.

    That is how it happened!! You just don’t understand biology!

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    Mapou says:

    And then a miracle happens …

    Yeah. So-called “convergent genes” fully falsify the Darwinian theory of evolution. It is a merciless and mortal blow to Darwinism. Darwinists are trying their best to keep their little religion alive but it’s hopeless.

    By contrast, lateral gene sharing (multiple inheritance in software parlance) in distant species is precisely what one would expect from intelligent design.

    In my opinion, the Darwinian theory of evolution is the most stupid scientific theory since the flat earth hypothesis. Heck, the flat earth hypothesis was a brilliant idea in comparison.

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