Speaker 1 00:00:05 ID the future. A podcast about evolution and intelligent design.
Speaker 2 00:00:12 Is Darwinian evolution really the mechanism that is causing adaptations in different types of organisms? I'm Casey Luskin with ID The Future, and today we have on the show with us Dr. Brian Miller, research coordinator at Discovery Institute Center for Science and Culture. Brian has a PhD in physics from Duke University, but he's quite an expert related to the new models that are emerging with engineering and the life sciences, helping us to understand how engineering can better explain biology. Then I'm guided to our winning mechanism. So Brian, thank you so much for coming on the show with us today.
Speaker 3 00:00:44 It's a pleasure to be here.
Speaker 2 00:00:46 So Brian, back in June of 2021, you and I both attended the conference on engineering, the Life Sciences or Cells back in Dallas, Texas, and it was really quite an event. There were about 60 or so biologists and engineers interested in questions about intelligent design and certainly friendly towards n Id viewpoint exploring the questions of whether or not engineering is a better way to understand biology than unguided Darwinian evolution. And Brian, you were very instrumental in putting that conference together. Uh, far more instrumental than me and I really enjoyed the conference. So thanks for all your work that you did on that conference.
Speaker 3 00:01:20 Yeah, it was a real pleasure. I, I think the people that attended really were inspired by what they were talking about.
Speaker 2 00:01:26 So I know that we've already discussed that conference in both Id the Future podcast and also on evolution news. But I wanna talk to you about some of the new paradigms that are emerging from the research that was presented at that conference, which you've also been writing about on Evolution News over the last couple months. So the sales meeting, it, it addressed various engineering based models for adaptation. Could you summarize those models for us and contrast them with what we might call standard evolutionary models?
Speaker 3 00:01:52 Well, certainly, in fact, there were two particularly wonderful lectures. And one of the lectures was by, uh, a person with, with some background in the engineering world. And he talked about what was, what he described as the operational gravity well model for adaptation and appreciate it. I need to contrast it with more of the standard Darwinian Neo Darwinian model of adaptation because the standard eche model is that you have kind of what's called a fitness landscape. And this would be like a plot of all the variation that you see in some population for some species or some group of species. And you could either plot it by the genes or by the, the, the nucleotides or the amino acids or simply by the different traits. And the idea is that a higher place on this landscape means an organism is more likely to survive, it's more likely to reproduce.
Speaker 3 00:02:44 And what happens is the population can move along this very complex landscape where there's hills and valleys and and peaks. And the idea is that over time you have natural selection and selective pressures, which can cause an organism to basically dramatically over long periods of time. Now, that is in stark contrast with an engineering model. The operational gravity Well model where the idea is that an organism is based on an engineering blueprint or a design plan that is based on a coherent logic founded on engineering principles. And this design logic has many features that really don't change. They're always gonna be set, yet there are certain parameters that will vary over time. Now, example would be like a finch. You have a finch bird and there's aspects of the finch bird that are always the same. It's gonna have a b, it'll have wings with a certain bone structure, a certain anatomy and physiology, but there are parameters that are adjustable.
Speaker 3 00:03:42 So for instance, the bee can be, uh, longer or shorter or sharper or thicker. And that variation you can see in the finch is reflected by the design logic. So the design logic determines what can vary and by how much. So you can depict it not as a landscape that can go on indefinitely, but more like a well where the bottom of the well would be your typical environmental conditions. And that's where that, that finch beak is gonna work very nicely. But as the environment changes, but certain details of the variation can change. So the big, the beak can get thicker or thinner, but it's always very constrained. It's always within type bounce. The overarching design logic is always the same. The parameters can vary, but that's not determined by the environment. How much the parameters can vary is based on the design logic, but where in that gravity, well the, uh, or the population best fits is determined by the environment.
Speaker 3 00:04:37 So that's one model which was very significant and generated a lot of conversation. And a second model done by a second lecture is more of a tracking model of adaptation because again, as I mentioned, the standard evolutionary model is that you've got these environmental pressures and then natural selection will drive transformations in an organism. But the tracking model is very different. It's the idea that the ability of an organism to adapt to its environment is based on internal mechanisms. So the organism is constantly scanning the environment and then when certain environmental conditions are met, the organism can change itself either in the next generation or let's say a young organism can grow into an older organism with different features. And that has really been confirmed by a lot of research because people like Jim Shapiro have talked about what's called natural genetic engineering. And that's the idea that the genetic changes aren't random, but there's mechanisms that direct certain genetic changes in certain parts of the D N a and also by what's called phenotypic plasticity. Phenotypic plasticity is essentially exactly what I talked about, that an organism will be monitoring the environment. And let's say you have a fish in water with greater sali tear or lower salinity, it has a logic based, an analysis system where it measures a solidity determines when it gets to a certain set point and then it can derive changes to its anatomy. It can make its body longer or shorter and different things like that. So those are the two models that were talked about at the conference.
Speaker 2 00:06:11 So Brian, what I'm seeing here really stands in stark contrast to a typical Darwinian model. Darwinian evolution of course, says that variation is random. It's not just random because mutations are totally random. It's random with respect to the needs of the organism. There's no reason to think that the variation that exists in a population is there because the organisms need it. It's also typically viewed as sort of unconstrained or almost, you know, infinitely plastic that organisms can evolve as much as they want, but it's never targeted to what the organism needs. But what you're talking about with these sort of engineering ID models is that the variation is not random, it's predetermined to give the organism the type of variation that it's probably going to need. It responds to the environment and that it's actually, as you said, the organism is scanning the environment and then it's able to produce the traits it needs. And it's probably, I, I would imagine also not infinitely plastic, but constrained within certain bounds. There's, you don't need infinite variation, you need certain variation because these organisms are, have been designed to be able to obtain the variation they need to survive and adapt to certain situations. So I guess it's always helpful when we have different testable predictions or different testable observations that we can predict from these different models. So what observations do these models predict and how are those observations maybe different from what we would expect from a Darwinian model of adaptation?
Speaker 3 00:07:31 Yeah, those are fantastic questions. So first of all,
Speaker 2 00:07:34 Well you wrote them, Brian, so I hope so. Oh yes, <laugh>,
Speaker 3 00:07:37 Yes. So well, good for me. Well, so what happens is there's several very clear predictions. One prediction is that when you have some new design logic that appears, that's like a radically different type of organism, it'll appear suddenly in the fossil record and then it won't change significantly. That's one prediction. Another prediction is if you look at the variation in any, any, uh, organisms that you can clearly trace back to a common ancestor, and that would be like the finch is on the Galapagos Islands. That would be like CLI fish and Lake Victoria. What you'd expect is as you examine the the variation, what you'll find is no variation for the basic architecture of the organism. Um, a finch will always be a finch. It'll have certain finch characteristics, but you will see variation in the features that can be adjusted to fine tune the design logic to a particular environment.
Speaker 3 00:08:31 In fact, engineers can predict in advance where will that variation will be. So if, if an engineer looked at a finch, they could predict that you'd probably see variation in the beak size and the sharpness and so forth. And, and that's exactly what you see. And there's been a flood of research over the last 20 years. A lot of it is very recent. It's been like the last five years that's confirming all of these predictions. So if you look at the classic model organisms that people look like, like fruit flies or dogs or bacteria or yeast or fish, that's what you see when you look at dogs. What you find is the variation in dogs that you have, all the amazing breeds is not from just random mutations, but there's what's called mutational hotspots. But there's specific regions in the d n A of dogs where you see mutation events much, much more frequently than in other examples. In fact, the classic example would be these, these tandem repeats in dogs which allow for just the right variation to help the dogs in different contexts. If you look at yeast, the same thing when when a yeast is stressed, what you find is there's certain mutational hotspots that are triggered. So you get the variation that you need to help the yeast. And now there's many other examples that I could be happy to talk about.
Speaker 2 00:09:42 So Brian, maybe you've kind of started to address this, but there have been many studies on the variation in different species that have been conducted over the past few decades. Have the predictions of these engineering based sort of ID models matched what this research has been finding?
Speaker 3 00:09:58 Oh, absolutely. In fact, let me give you a really nice example, and this is from a paper on fruit flies, the the Genus Drosophila, and it's by Alba etal. It's a 2021 paper evolution news article that you can download the paper and, and look at all the references that I mentioned and, and it's really an amazing paper. In fact, I'm gonna read a quote from the paper and then I'm gonna flesh out the quote. So any listeners that might be kind of panicked by the technical language, I'll explain it in the quote. Remarkably, the phenotypic variants can be described by a single integrated mode that corresponds to a non-intuitive combination of structural variations across the wing. This work demonstrates the presence of constraints that funnel environmental inputs and genetic variation to phenotypes stretch along a single ax axis and morphology space. Now let me translate that.
Speaker 3 00:10:45 What these authors found is when they look at the, uh, genetic variation and the structural variation fruit flies is it was highly, highly constrained. The basic design logic was always intact, but there were minor differences like where the wing veins would cross differences in size. But what they found is you see the same variation over and over again. Uh, and it was always constrained. And what's really remarkable is if you look at the phenotypic plasticity, and, and again as I mentioned, phenotypic plasticity means that when, let's say a fly encounters a different environmental condition, when it's young, it'll grow into a fly with slightly different traits. The wing sides might be larger or smaller, or the wing dimensions might be larger. And then if you look at the variation based on that phenotypic plasticity, it's the same variation that results from the genetic variation. These authors talk about how these, these very tight design constraints that ensure a fly will end up being basically a fly with the way the same wing structure. And if there's perturbations from mutations or from environmental situations, the developmental program forces the outcome to stay the same. But again, there is some flexibility in these very specific traits that allow the fly to fine tune as designed to the particular environment. So that perfectly matches both the tracking model and the model for the gravitational operational. Well
Speaker 2 00:12:15 Brian, for me, the fact that you're saying that the same variation keeps appearing over and over again, that's really the smoking gun, that this model seems to be onto something because it predicts that there's targeted variation. Organisms are designed to evolve the same kinds of adaptations because it's known what the needs are gonna be that was built into the organisms when they were designed. They keep evolving the same variation in response to certain external stimuli. So that sounds like a very positive confirmation of the article. You talked about this looking at variation in fruit flies, drosophila. How does that evidence support or not support this engineering model you're talking about?
Speaker 3 00:12:52 Yeah, and, and it, it just, it it it supports it absolutely to a t It's exactly what you see. What you see is that the design logic never changes. You see that there's these very specific variables that can change and the way it changes allows the fruit fly to fine tune itself to the environmental conditions. So it it, it fits it to a team, but it's not just fruit flies. That's just one example. There's numerous examples. Two of the examples I think are particularly significant are the cli fish and the stickleback fish. These particular groups of fish are very important because they're typically seen as kind of the best example that evolutionists have of the ability of evolutionary processes to create change. This would be like the poster children for the evolutionary model. And the idea was that you have all these random mutations and that's allowed cylis to change dramatically over time.
Speaker 3 00:13:48 So the idea is maybe a pair of CYC lids go into a lake and then they get stuck there for several million years and then they can diversify into multiple different species that look quite different. But as it turns out, studies have shown that that variation is not from random mutations. What you find is, again, phenotypic plasticity in the cyclic fish. So again, as you mentioned, the fish are designed to adapt to different conditions in very specific and helpful ways. And there's some beautiful papers like Parsons Etal has a 2016 study, and what they did is they actually fed these cyclins in their, in very young CLIs different types of food. And what happened is the jaws in the, in the skulls would form in different ways. And what they found is the differences in those offspring in in the different fish matched the different species that you would see in these different lakes.
Speaker 3 00:14:42 So again, what people used to think was mutations that accumulated over millions of years could happened in a single generation. And there's countless other examples. So for instance, another experiment, they raised the s in different salinity levels of water, so different amounts of salt. Some of the fish had shallower bodies, they had longer jaws because of these differences. And again, you even see things like different numbers of spikes on the fins. So they're very dramatic differences. Same thing with stickleback. There's been similar experiments with stickleback where they would raise these fish in different conditions. The differences in the traits as the adults would match the different species that you would see in the wild. It's not just phenotypic plasticity. What you would also see is evidence of natural genetic engineering. So for like the cyclics, what would happen is when they examined the genetic variation, they found that the genes that were associated with vision had what were called transposable elements that moved into those regions that affected the operation of those genes.
Speaker 3 00:15:44 The regulation of those genes, and again, transp disposable elements are those elements of genes that can move that are often associated with natural genetic engineering. Now lemme just throw in the caveat that this is very, very, very recent research and there's lots of, um, discoveries being made. So naturally people are trying to interpret all this through an evolutionary grid. So they say, oh, well these transpos elements, maybe they're just ancient viruses. But what you're seeing in the latest literature is these transp disposable elements often will move in response to environmental conditions stimuli, and often they're targeted to specific regions in the genome. What we're seeing is more and more evidence that this variation the genes is not random, but it's engineered.
Speaker 2 00:16:29 So Brian, you're talking about fish evolution. And I remember when I was an undergraduate, I took an evolutionary biology course and I had to write a paper on CLINs. And there were all these huge lakes like Lake Victoria, lake Tanika in Africa, where these lakes have been invaded by cyclins. And there's tremendous diversity of different types of cyla species in these lakes. But what I remember reading is that these CICD species often have very, uh, they're very similar. I mean, they're barely different. They have like the same as you were saying, the same repeating traits over and over again. You might have one type of cyc lid that looks almost like another species of cyclo except it feeds at a slightly different depth in the lake. And because of that doesn't interact, interact with that other fish. And because of that, they would call it a separate species.
Speaker 2 00:17:15 But otherwise, these fish were, were very similar to one another. And so it seems to match what you're saying that we're seeing the same kind of variation and similarities repeating over and over again. But I wanna ask you a question. I know this is going off script a little bit, but you know, when an evolutionist hears about the opportunities for rapid adaptations, things that should normally take millions of years to evolve, and now we're able to evolve them in just a couple of years, sometimes they're gonna immediately say, well this, this proves our model that you can evolve things rapidly. Evolution doesn't take millions of years to produce these complex traits. What would you say in response to an objection like that, that to the kinds of evidence you're raising for people who wanna support a Darwinian model of, of rapid evolutionary change?
Speaker 3 00:17:55 Well, it's, it's very problematic because again, if you look at the traditional predictions of the evolutionary model are that you have the slow accumulation of of mutations, you have slow adaptation. It's, it could be in very different directions. It's not always predictable. But again, when you see very rapid adaptation, you see the same adaptation over and over again. It's just the opposite of what people have predicted. And the reason it's so rapid is because it's engineered. You've got mechanisms in the fish or in the drosophila that caused the body to change in very predetermined ways based on engineered mechanisms. So again, they're sensing the environment. They have logic, a logic system that determines when when conditions are met. And they have very directed responses to that. And again, here's the biggest problem is that when you look at the CYC lids or the sticklebacks or, or you look at any particular species, you see the same variation both genetically, often and phenotypically in the structures that appear over and over and over again. So it's not limitless, it's very predictable and it's very, very constrained. It is always constrained within particular limits. And the overarching design logic never changes. And that's really fits with a design-based model much more than a Darwinian model.
Speaker 2 00:19:13 Yeah, again, that really is the smoking gun that you're not dealing with a Darwinian pattern of adaptation here. Brian, we're running outta time. So I wanna ask one last question, but you mentioned that a design expectation is that life should contain design patterns based upon engineering logic. So do we see any such patterns which resemble human engineering designs even such patterns appearing over and over again in the same kinds of organisms?
Speaker 3 00:19:38 We do. And that's really I think one of the most exciting things about this engineering model. What you see is the same engineering logic in human engineering that you see in life. And again, that has really deep profound philosophical implications because it looks like our universe was designed in such a way that certain engineering motifs work. And that's why the same motifs are seen in life as in human engineering. And one of my favorite examples is from lab fish. There's a really very talented researcher named West Nut and he wrote a paper in 2005 where they looked at these different, uh, labyrinths and do you see what's called a four bar linkage? That's a classic engineering design that humans use. What you have essentially is like four bars in the case of the fish it's bones and it's almost like a, like you can imagine a, um, a parallelogram or a rectangle where you have the four bars, which would be like the four bones, and then you have hinges that connect them all together.
Speaker 3 00:20:37 This four bar linkage allows you to have extremely tight control over your force. So it's like a jaw can can bite down with a lot, lot of force in a very, very precise way. And what wes not found that you see different versions of these linkages. So you may have had the classic four bar linkage, but you might have, let's say a linkage with extra bars or extra bones in, in extra hinges. They have the same basic motif, but they're very different in their own way and they're highly specialized for the fish's food or its environment. You see these design logics appear independently throughout the, the fossil record and you'll see 'em appear independently and they always appear suddenly and they never change. And that was really just a remarkable fine that's very consistent with the models I talk about.
Speaker 2 00:21:27 Well, this is really fascinating, Brian, and it's, it's, it's exciting to see intelligent design serving as a paradigm which can help make predictions and guide research and help us understand crucial evolutionary questions. Like how do organisms undergo small scale changes to adapt to their environment? So this is really exactly where we wanna see intelligence design going as a paradigm and we appreciate you helping to explain this to us and I'm sure that, uh, we're gonna have more about this topic in the future.
Speaker 3 00:21:55 Uh, thank you. It's been a pleasure.
Speaker 2 00:21:57 Well, I'm Casey Luskin with ID The Future. Thanks for listening.
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