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Author Topic:   Another IDology challenge -- complete with complaints of harsh treatments ...
Posts: 5067
Joined: 05-02-2006
Member Rating: 2.8

Message 7 of 63 (861610)
08-23-2019 4:10 PM
Reply to: Message 3 by RAZD
08-23-2019 11:39 AM

Re: IDotic arguments
I'm not going to waste an entire hour listening to ID BS, especially if it's as brain-dead stiupid as you describe it.

I don't care how "learned" Gelernter's name claims him to be (German: lernen, lernte, gelernt), as a computer scientist he should know better than others the old dictum, GIGO ("Garbage In, Garbage Out") *. The output of your program can only be as good as the program and the data inputs: if your program is fouled up or you input crap data, then the results will be fouled up and crap. Or to a mathematician modeling something in the real world, your calculations depend on your model, so if you build a slap-dash fouled up model, then your results will reflect that.

Building crap models and using them to throw a lot of big numbers at the audience is one of the oldest "creation science" tricks to confuse and deceive its audience, one which IDologists use fully -- it's easy to refute most YEC claims, but ID claims are more difficult because of all the obtuse pseudo-mathematics you have to wade through and counter (not to mention that your countering would also go over most people's heads).

I should give Gelernter a listen before addressing his claims, but it's not worth sitting through an hour of that crap (I've had to sit through Hovind videos to find a specific claim and I have no desire to undergo such torture again). Do you have the timemark for when he makes his claims so that I can respond to what he's actually saying? Barring that, I have to go with your descriptions.

For example, what does he mean by "to assemble a protein molecule by molecule"? Are we talking about DNA base pairs, triplets of which form codons which translate for amino acids? Or are we talking about amino acids which chain to form proteins? Are we talking about the original proteins or modern proteins, or does he not realize that there's any distinction?

Also, is he talking about only one single attempt to form a (¿modern?) protein in such a single-step selection manner (see Chapter 3 of The Blind Watchmaker)? Or is he allowing for a large number of parallel attempts such that the attempt would succeed if even just one individual attempt succeeds, meaning that the overall attempt would fail only if each and every individual attempt fails.

Refer to my page, MONKEY PROBABILITIES (MPROBS), where I analyzed the probabilities in MONKEY, my implementation of Dawkins' WEASEL program (again from Blind Watchmaker):

  1. First, there is a huge difference between single-step selection and cumulative selection:
    1. Single-step selection is where you make your attempt and, when you fail (which is most probable), then you start all over from scratch, over and over and over again. In my MONKEY, the task is to randomly generate the alphabet in alphabetical order; in Dawkins' WEASEL, the target is a specific line of Shakespeare. Single-step selection could be described as "all or nothing at all."

      The probability of single-step selection succeeding is abysmally small. For MONKEY's task to succeed with a super-computer capable of one million attempts per second (modern PCs can only do about 2000 per second) would take about 195 trillion years to earn a one-in-a-million chance of success, more than 10,000 times longer than the universe's estimated age.

      All creationist probability arguments that I have encountered all single-step selection. I'm sure that Gelernter's contribution does the same. His second "hopeful monster" argument confirms my suspicion.

    2. Cumulative selection is a step-wise approach which accepts a small change in each step and uses the outcome of the previous step as the new starting point. Basically, you have a population of attempts and you select the one (as in MONKEY or WEASEL) or few (as in life) that come closest to the target and that/those serves as the starting point for the next generation. This does describe and model life far better than single-step selection.

      Completely different from the abysmal failure of single-step selection, cumulative selection succeeds readily and quickly. When I read about WEASEL in The Blind Watchmaker, I couldn't believe it so I wrote my own, MONKEY, using Dawkin's description as the specification. WEASEL was written in BASIC, an interpreted language, so it ran so slowly that it took much of their lunch break to succeed. My MONKEY was written in Turbo Pascal, a compiled language, so it ran much faster (even on an XT clone with a Norton Factor of 2) and succeeded in much less than a minute (depending on population size, it normally took about 20 seconds -- on more recent PCs, it's almost instantaneous, which at first made me think that the program hadn't run).

      Since I still couldn't believe what I was seeing even with my own program, I started analyzing the probabilities involved, doing the math, which resulted in my paper, MPROBS. Basically, each individual attempt would result in one of three outcomes: advancing (success), slipping back (failure), or no change (also counts as a failure). The probability of advancing is always low and it gets ever lower the closer the systems approaches the target. It turns out that the reason for MONKEY's success is that, while an individual's own success is unlikely, it becomes increasingly unlikely for every single individual in the entire population to all fail in each and every generation. Yes, we see the system backslide often, especially as we get to within a few steps of the target, but the probability of that continuing to happen becomes very small so MONKEY always succeeds in the end.

      Creationists (including IDists) are ignurunt of cumulative selection and, even when they hear of it, cannot understand it nor its great power. I have no doubt that the "learned" Gelernter is no different.

  2. Second, any mathematical models for evolution and evolutionary processes must use the correct selection model, which is cumulative selection. The moment that IDists start to use single-step selection, they have destroyed the validity of their model and their argument.

    The reasons for this have already been presented above.

Another treatment of this is on my page, THE "RANDOM" PROTEINS ARGUMENT, in which I responded to a typical creationist probability claim about the chances of a modern protein just falling together randomly -- my impression is that this is what Gelernter is also trying to argue. Several problems with that:
  1. That is simply not how it works. That is not how proteins form, so just what are they talking about?

  2. There is no actual abiogenesis scenario, in which we expect any modern proteins to have formed at that time, but rather ancient barely functional proteinoids which later evolved into their modern forms. It's only creationists who think that's how it must work.

  3. The argument demands one-and-only-one highly specific amino acid sequence for that protein. It doesn't work that way! First, the very existence of differences in amino acid sequences for the same protein in different species (included in some creationist arguments, so they do know about that and acknowledge it) kills that assumption immediately.

    Second, it is a well-known fact that only some loci in a protein are specified for one specific protein. I review this on my page, which is a reprint of an email with a creationist (to which he did not reply, as I recall) plus some of my posts on CompuServe.

    In the class notes for their classic two-model class at SDSU (closed down by strident protests from campus Christian clubs), Thwaites and Awbrey take the example of an active site on a protein and show the variety of amino acids that could occupy each locus:

    Rather than brandying about a hypothetical protein, let's look at a specific case. In the class notes of Frank Awbrey & William Thwaites' creation/evolution class at UCSD (the Institute for Creation Research conducted half the lectures and Awbrey & Thwaites the other half), they give the example of a calcium binding site with 29 amino acid positions: only 2 positions (7%) require specific amino acids, 8 positions (28%) can be filled by any of 5 hydrophobic amino acids, 3 positions (10%) can be filled by any one of 4 other amino acids, 2 positions (7%) can be filled with two different amino acids, and 14 of the positions (48%) can be filled by virtually any of the 20 amino acids.

    The sequence of the 15 specified positions is:
    L* L*L* L*D D* D*G* I*D* EL* L*L* L*

    L* = hydrophobic - Leu, Val, Ilu, Phe, or Met
    Prob = (5/20)^8

    D* = (a) Asp, Glu, Ser, or Asn
    Prob = (4/20)^3
    OR (b) theoretically also Gls or Thr
    Prob = (6/20)^3

    D = Asp
    Prob = (1/20)

    E = Glu
    Prob = (1/20)

    G* = Gly or Asp
    Prob = (2/20)

    I* = Ilu or Val
    Prob = (2/20)

    Remaining positions = any of 20
    Prob = (20/20)^14 = 1^14 = 1

    Total Prob = Prob(L*) * Prob(D*) * Prob(D) * Prob(E) * Prob(G*) * Prob(I*)
    = (a) 3.05 x 10^(-12)
    OR (b) 10.2 x 10^(-12)

    Your own calculation of the probability of a functional order coming up (ie, the standard creation science method) would be: (1/20)^29 = 1.86 x 10^(-38).

    Comparing the lower probability to yours shows it to be 1.64 x 10^26 times greater.

    This invalidates your colored-box-car analogy as it stands (to correct it, you would need to allow for a variety of different combinations) and it invalidates your probability calculations.

    In addition to such active sites, the rest of the protein is primarily structural, which to me means that any of the 20 protein-building amino acids would do. Of course, that would by far further kill creationist ideas of amino-acid specificity in proteins.

Did I misunderstand Gelernter's arguments? If so, then please give us the timemarks so I can get the straight skinny.


We DSes (US Navy Data Systems Technicians, disestablished in the 1998) saw GIGO, "Garbage In, Garbage Out", as being depicted in our rating symbol:

The helium atom is used in the rating symbols for all electronics ratings (not technically correct, but far easier to embroider than a copper, silicon, or germanium atom). The three arrows pointing in represent inputs and the arrow pointing out represents output. This image is of a metal pin. When embroidered on a rate badge, the input arrows are solid and the output is just an outline (empty). We would interpret that to mean that the input arrows were the unprocessed "garbage in" and the output arrow was the processed "garbage out."

The rating symbol for Electrician's mate is a globe of the earth. Here is why that is.

The creation of rating symbols happened around 1921. The Navy team went to each rating community and asked about equipment or tools or anything else that would symbolize what that rating did. At that time, many light bulbs were spherical and were called "globes" (as opposed to our current talk of an oniony shape, "bulb", or the German "Glühbirne", "glowing pear"). So when the team spoke with the Electrician's Mate the response was "a globe", which the team misinterpreted. By the time the mistake was discovered, it was too late to correct it.

This message is a reply to:
 Message 3 by RAZD, posted 08-23-2019 11:39 AM RAZD has seen this message

Posts: 5067
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Message 9 of 63 (861619)
08-23-2019 8:16 PM
Reply to: Message 8 by WookieeB
08-23-2019 6:23 PM

Re: IDotic arguments
So then show us! Point us to your sources. Quote from them.

I am not going to sit through an hour-long video filled with BS. I explicitly asked for a timemark so that I could hear Gelernter's argument itself.

If you have something to show us, then show us.

This message is a reply to:
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Message 21 of 63 (861705)
08-25-2019 3:41 PM
Reply to: Message 20 by AZPaul3
08-25-2019 11:46 AM

Re: more filling in the blanks.
I know we love to say this but I don’t think evolution has a rate.

I've pointed this out before, but nobody will believe me:

Evolution never stops. The same evolutionary processes are constantly at work, just with differing results. The processes that cause changes in the population in a new or changing environment are the same processes that keep a population from changing in an unchanging environment.

So even when there's no change, that's still evolution at work.

For those with a background in engineering or as a technician, it basically acts like a negative-feedback control loop. The further you are from the set-point (eg, a specified voltage, the optimal phenotype for that environment) the harder it will drive you back to that set-point. When you are at the set-point, then the exact same mechanism keeps you at that set-point.

If a power supply's voltage output remains constant, that does not mean that it's not performing voltage regulation.

This message is a reply to:
 Message 20 by AZPaul3, posted 08-25-2019 11:46 AM AZPaul3 has replied

Replies to this message:
 Message 22 by RAZD, posted 08-25-2019 4:47 PM dwise1 has replied
 Message 24 by AZPaul3, posted 08-25-2019 5:38 PM dwise1 has replied

Posts: 5067
Joined: 05-02-2006
Member Rating: 2.8

Message 23 of 63 (861718)
08-25-2019 5:34 PM
Reply to: Message 22 by RAZD
08-25-2019 4:47 PM

Re: more filling in the blanks.
When the ecology is stable, in equilibrium, then selection is to maintain that median position because it is successful.

Indeed. Selection is still selection and selection still happens. All it takes to be able to see that is some basic knowledge of evolution and thinking through how it works.

The backlash I would get would mainly be from creationists who are so wrapped up in definitions and, since the word "change" appears in their definition of evolution, they think that if there's no change then evolution isn't still happening.

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 Message 22 by RAZD, posted 08-25-2019 4:47 PM RAZD has seen this message

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Message 25 of 63 (861731)
08-25-2019 8:39 PM
Reply to: Message 24 by AZPaul3
08-25-2019 5:38 PM

Re: more filling in the blanks.
I like the analogy. I'm going to steal it. Thanx.

You're welcome to it. I'll even give you some of the background to its development in case that gives you more to work with.

I read an article from Nature or a similar science journal from around 1980 which reported on a paleontology conference centering around punctuated equilibria and similar topics. One pattern presented would be of a large population ranging over a broad environment such that it didn't change much but it lasted a long time because it had enough diversity to weather through changes in their environment; compared to that are smaller populations changing a lot to become highly specialized to their particular niches, but short-lived because they could not survive changes in their environment.

A graphic that formed the imagery in my mind was one which showed that the "sudden" change in geological time was still gradual in generational. The portion of the graphic showing generational time was a series of bell curves each representing a generation and showing the center of the curve (representing the optimal organism) moving as the environment changed. That would translate into our use of the term "set-point" here and of your point that that set-point does move so the population needs to track that movement.

Another contribution was made by a PBS popularization of evolution from the early to mid-80's hosted by Christopher Reeve. Towards the end was my first exposure to Evolutionstechnik, using evolutionary processes in engineering (eg, genetic algorithms, it was a few years later that I first heard of GAs). The mind-bender for me was when he presented a model of a 3-D "evolutionary landscape" in which the environmental optimum was the top of a hill (a local optimum) and he described evolutionary change as being faster when the population is farther away from that optimal point and would slow down as it got closer.

That idea took me by surprise, so I worked through some Gedankenexperimenten (I'm kind of good at visualizing things). This is what I ended up with (which would work better with good visuals, so my apologies):

  1. Start with a bell curve to represent the initial population. Establish an optimal point to the right of that curve.
  2. The population reproduces and creates the next generation. This causes the bell curve to grow in amplitude and also to spread out to the left and to the right. This could or could not involve the removal of the previous generation; removal would make the new bell curve represent only the next generation.
  3. Selection happens. The individuals closer to the optimal point would have a better chance of surviving (ie, have an easier "saving roll" to make if you're familiar with RPGs like D&D) and those further away would have a worse change (ie, a harder "saving roll" to make). This would result in a lopsided curve whose center would have shifted closer to the optimal point.
  4. Goto Step 2 and rinse and repeat observing what happens to the population's distribution curve over the generations.

In my mind, I saw that population work its way to that optimal point and then center around it. And over subsequent generations as the population's curve might try to spread out, selection would eliminate the more extremely different individuals and thus keep the population centered at that point.

A further application would be to start with an optimally adapted population and then start moving the optimal point and observe the population's response to that. Again, we should observe the population shifting its own center to track its optimal point.

I think that you could set up an experiment involving two optimal points, one that the population starts off tracking and the other a near-by one. I would visualize part of the parent population splitting off and starting to track the new optimal point.

I've also thought of adapting this visual model to a simulation program for study.

Let us know what you're able to do with this, if anything.

Share and enjoy!

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 Message 24 by AZPaul3, posted 08-25-2019 5:38 PM AZPaul3 has seen this message

Posts: 5067
Joined: 05-02-2006
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Message 34 of 63 (861867)
08-28-2019 12:26 PM
Reply to: Message 32 by RAZD
08-28-2019 8:09 AM

Re: Another input -- Faith-0-lution ....
Faith writes:

That's what selection does. It will eventually blend tog3ether whatever proportions of traits are in the new set of individuals, their new collection of gene/allele frequencies, and eliminate others from the population.

Again this is not how evolution works. It doesn't blend characteristics. It selects those that are more fit for survival or more attractive for reproduction.

It appears to me that Faith is making the same mistake as Charles Darwin when he couldn't figure out how new traits could establish themselves in a population.

He pictured heredity as being like mixing paint, but that would inevitably result in new traits disappearing as all traits just blended together. But of course, that's not how it works as scientists came to realize through Mendelian genetics (ironically, Darwin had a copy of Mendel's monograph in his library, but apparently never got around to reading it).

We now mainly only know about Darwinian evolution (the natural selection acting upon variation part), but we forget about Darwin's pangenetic theory which tried (and failed) to explain heredity. We have reams of creationist quotes of "scientists declaring Darwinan evolution to be false" which are taken primarily from the first part of the 20th century. During that time, research into genetics and mutations did indeed disprove Darwin's pangenetic ideas (which were demonstrably wrong), so you can find many statements of "Mendel proves Darwin wrong!", but that applied only to pangenesis and had nothing to do with the natural selection part. By the 1940's, it was discovered that Mendel actually provided answers to the questions that Darwin couldn't answer himself. What resulted was the Modern Synthesis (AKA "Grand Synthesis"), the combining of genetics with Darwinian evolution which produced neo-Darwinism.

So all that Faith has succeeded in doing is in reproducing Darwin's biggest mistake.

This message is a reply to:
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