Introducing Geremy (and Behe)

Hi this is my first post here. I agree that Behe often relies heavily on lab experiments, but I think that he is doing that because he is asking a very different sort of question than most evolutionary biologists are. They are asking how evolutionary mechanisms evolved biological functions, while Behe is asking are evolutionary mechanisms alone capable of creating all biological functions. So I think that he wants to use examples where evolution is demonstrably the cause of a given biological change, as opposed to inferring it as the cause of an unobserved event.

I always thought that the mathematical evidence is more interesting, because, I think that either evolutionary theory is demonstrating something fundamental about algorithms, or it isn’t actually a realistic approximation of reality. Since you are a data scientist you might like this paper below which reviews the performance of evolutionary algorithms:

The limitations in the ability evolutionary algorithms of evolutionary algorithms, is precisely what an ID theorist such as Dempski would expect it to be, and precisely contradicts the expectations of the theorists who originally designed the evolutionary algorithms in the first place, so the question is why? If ID is actually a pseudo science as is often claimed then why does it accurately describe why evolutionary algorithms, are self limiting? Might better computer models of cells developed in the future similarly demonstrate mathematical limits to biological evolution consistent with ID someday as well? Perhaps ID is just a young science, with many imperfect personalities who are making many mistakes, but it’s fundamental premise is closer to how the world actually works than the one presented by evolutionary theory. That’s how I see it anyway.


Welcome @Geremy. Tell us about yourself.

I’m just an inventor, with an allied health background as a respiratory therapist who likes to think outside the box. I only have one patented device at present, but I’m designing two simple devices at present so that will probably have to change soon.


That computer programmers are not yet able to produce a program that works as well as natural evolution is a problem for computer science, not for evolutionary biology.

When computer programmers were struggling to create a program that could play chess at a Grand Master level, did anyone suggest that this was because chess doesn’t actually exist?


This is a big problem, and it’s the result of a misunderstanding of science. Everything in science is inference from observation, whether the relevant event happened in the lab or elsewhere, recently or long ago. Interpreting that paper to suggest that evolution doesn’t work is to deny the mass of data. It would be similar to the apocryphal proof that bumblebees can’t fly. We see that species are related. We see that the differences among them are exactly the sort expected from known mutational processes, sometimes filtered by selection. If intelligence is necessary somewhere in all that, it’s hiding itself from view very assiduously.


The mathematics seems to hold up just fine. The number of mutations that separate the chimp and human genomes are consistent with 5-8 million years of divergence, as one example. It would be interesting to hear Behe explain how nearly all of our human adaptations are due to mutations that broke genes.

The success of algorithms like AlphaGo seem to argue just the opposite. AlphaGo evolved through competition, and it plays Go better than any human. Genetic algorithms have also designed physical components, such as the evolution of a radio:

Of course, computers and circuits are analogous to life, not homologous. The differences between genetic and computer code are large, so any inability to exactly model biology in computer software is due to the differences between the systems.


I wonder if it is truly possible to know without observing natural evolution in thousands of experiments for millions of generations, as has been done using evolutionary algorithms, that naturally occurring unguided evolution works better than evolutionary algorithms. I don’t think one can argue that without strong mathematical evidence.

Perhaps you are correct, in trying to to explain the results the author suggested that maybe these algorithms don’t accurately reflect evolution, but they rejected that thought saying:

Some[55] have suggested that EAs do not accurately capture the theory of evolution, but of course that would imply that the theory itself is not specified in sufficient detail to make falsifiable predictions. If, however, such more detailed specifications are available to GP believers, it is up to them to implement them as computer simulations for testing purposes, but no successful examples of such work are known and the known ones have not been successful in evolving software.

I don’t think that the computer scientists running these algorithms don’t understand evolution as explained by evolutionary biologists, I think it’s just that applied evolutionary mechanisms simply don’t have the computational power theorists expected it to.

Computers have a difficult time modeling protein folding, much less predicting function, binding partners, and impacts on gene regulation. There is currently no way to accurately model this type of biological evolution in a computer.

I think they fail to see the difference between silicon and biology.


Nice article by the way, ( I am curious to know how one could amplify existing radio waves with such a simple system). It is sort of a simple optimization program, with 10 just components and was guided by rewarding any progress toward the goal, no penalties for missing it. Which makes it a lot like these other toy projects:

So it’s a cool project, but analogous to the evolutionary process of a virus. Like the oscillator a virus is rewarded for every mutation that allows it to more effectively be transmitted from host to host, and it doesn’t have have other complicated functions like a living cell does that could be damaged by if they had the viruses high mutation rate.

This is a version of the creationist “were you there?” trope. But one can infer much about the past based on the present, and the evidence of the present tells us that known evolutionary processes were operating in the distant past. If those processes were not responsible for turning an ancestral mammal into elephants and anteaters, bison and bats, whales and wolverines, etc., then what do you suppose the evidence suggests as an alternative? Is it possible that computer code differs from DNA and from organisms in some important ways that might affect results?


A living cell doesn’t have to worry about evolving those systems either since it already has them. We don’t have to wonder about the origin of life if we are talking about the evolution of vertebrates or humans.


We can learn a whole lot about the creative power of unguided evolution versus, guided evolution by comparing the two processes results in experiments, even when the guidance initially appears subtle:

First guided evolution:

Now I have my own ideas, but please look at Figure 2. Why do you think that the evolutionary fitness improved so much in the populations of yeast that were placed in the centrifuge?

Unguided evolution:

Not only is the result much less striking but it is also harmful as explained in another paper which explains:

In our experiments, populations were evolved in illuminated incubators with ample nutrients obviating the need for photo- or chemotaxis. This process therefore allows multicellular colonies to settle and survive without selection for motility. Thus, while our evolved multicells thrive in a laboratory environment, their immobility would likely place them at a strong fitness disadvantage in nature…
By examining the motility phenotype of newly evolved multicellular Chlamydomonas we have uncovered a trade-off that arises from their novel morphology. However, because flagellar structure and function are unchanged, and unicellular propagules remain phototactic, barriers to the subsequent evolution of externalized flagella and coordinated movement in multicells may not be too high to overcome in the laboratory. Multiple, and possibly sequential, selective pressures are likely required to experimentally evolve naturally viable multicellular algal clusters.

So why were the results so different? I would like to hear what you think first then I will be happy to tell you what I think.

Before getting into the weeds, the first question I ask concerning all such lofty algorithmic objections to evolution, as they pop up from time to time, is just what in biology is precluded by the supposed finding?

For instance, a single base pair substitution is able to shift the spectrum sensitivity of opsin proteins, allowing the development of enhanced chromaticity in vision. Is there something in the algorithm that says “HALT, that violates computer science, so you are not allowed to do that!” Covid variants have arisen which are of concern for increased morbidity, contagion, and escape. Does the algorithm apply to that scenario; why or why not? Are the established mathematics of population genetics superseded or encompassed? If none of these real world types of applications can be addressed, that is an reasonable indication that the author’s idea is fundamentally flawed.


Because it was subjected to an environment in which multicellularity was favored. That isn’t guided evolution; it’s natural selection. We appear to disagree on the definitions of basic terms, so there isn’t much we can sensibly discuss.

We also appear to have a basic disagreement not just about what “guided” means but about what “harmful” means.

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Are you sure? Selection was used along with unnatural mechanical pressures, to engineer a new phenotype: Here’s what I see.

First, the researchers selected all of the yeast cells that were attached to other yeasts cells, by sorting them according to size (gravitational selection).

Second they selected out all of the cells that were attached to each other in flocs by using the centrifuge. The physical strength of the attachment between mother daughter cells is greater than what occurs in flocs.

Third, the greater the size of the cluster the more mechanical pressure existed at the center of the cluster, at 100 X g the 1.5 grams of pressure placed on each cluster’s central region caused the elongation of some of the cells, this change as well as the phenotype of the whole cluster were driven by physics and the existing sorting which created the novel phenotype.

So there was nothing natural about the selection used in this experiment, or the constraints of the environment. There’s no such thing as gravitational selection and there’s no natural process that will tug on the cell clusters in all directions for ten seconds and only select the clusters that don’t come apart. This is an example of guided evolution.

To his credit the author didn’t appear to understand how essential mechanical pressure was at the time he first wrote the first paper (he probably thought only about selection like you just did) but he later coauthored a paper about the essential role of mechanical pressure creating the new phenotype in this paper below:

So briefly the real reason this experiment worked and the other one didn’t, is because one mirrored the development of the multicellular fungi while the other didn’t mirror the development of multicellular algae. of the organism. The development of the hyphae is governed by mechanical pressure, so pressure testing hyphae and selecting those that perform the best is a good way to get multicellular fungi. In contrast the development of multicellular algae requires gastrulation which is hard to mimic, so simple genetic evolution is not sufficient to evolve multicellularity. I learned this concept by reading what developmental biologists have to say about the what’s needed to form a multicellular organism, and I have never found them to be wrong about this. Here’s an example:

As a side note the routinely algae form the same structures for the same reason in nature, but if it becomes permanent they can’t survive in a natural environment. I could give you another paper if you would like, but I’ve already given you four today so only if you want to see it.

I suggest you familiarize yourself with the Third Law of Creationism:

  1. The Law of Reproducible Results : Anything found in nature was Designed, unless it can be reproduced in the lab. Corollary: Anything intentionally done in a lab is not natural; it’s a purposeful result. Therefore, all lab results are evidence of Intelligent Design.

That’s interesting Faisal, but you can’t intend to apply that to what I wrote because both experiments I described occurred in in a lab :slight_smile:

The selection pressure in the algae experiment was predation, a naturally occurring selection pressure. However I’m unaware of a naturally occurring environmental pressure that selects only the yeast clusters the fall the fastest and don’t break apart when subjected to 100 X g.

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Yes. As I said before, we seem to have quite different definitions of crucial terms, and no discussion is therefore possible. “Guided evolution”, “natural selection”, “harmful”: all three are problematic understandings.


Why are whales so big but land animals are not? Why are your bones, the bones of birds, and the bones of elephants the size they are?

We can agree that persistent centrifugal selection of the type used in that experiment probably does not occur anywhere on Earth, but it is not correct to say that the force of gravity plays no role in natural selection.

Of course, researchers might some time use a physically unrealistic selection protocol to answer a more fundamental question, such as whether extant obligately single-celled organisms can even be selected in any way to exhibit multicellular phenotypes. Turns out they can.


That’s fine I alway’s try to understand what evolutionary biologist claim is possible in the light of developmental biology, this is probably causing the difference in how we see the evidence. So I wonder if you think that it is possible for a human to guide the morphogenesis of another creature by creating unnatural selection pressures, that involve mechanical pressures, or specific chemical gradients? Or is direct genetic intervention the only possible route? From what I’ve read one can use unnatural mechanical pressures and artificial chemical gradients to control tissue phenotype in ways that are often unexpectedly effective, since that since that is how phenotypes are formed during development, as explained in some developmental biology papers case in point:

Would you disagree?

As far as the algae is concerned, if the researchers placed immotile algae back in their natural environment where motility is essential to their survival, would that not be harmful? What criteria would you use for a harmful mutation? You don’t have to discuss any of this if you don’t want to, but it might leave someone with the impression that I’m correct, especially someone who has read the papers that I attached. All the best.