Speaker 1 00:00:05 ID the future, a podcast about evolution and intelligent design.
Speaker 2 00:00:12 Hello, I'm Casey Luskin and welcome to ID the Future. We're broadcasting today from Denton, Texas at our second conference on engineering and living systems. I have with me a person whose voice is very familiar to ID the future listeners, Eric Anderson, who is co-organizer of the conference, and also co-organizer of the engineering research group, which helped to put on this conference. So, Eric, it's great to have you on the show as a guest and not as a host this time. Yeah, thank
Speaker 3 00:00:39 You Casey. It's an honor to be here. Really great to be on the other side of the microphone today.
Speaker 2 00:00:42 Well, you more than deserve it. You guys did a fantastic job organizing this conference. We had what, 60 attendees or how many attendees? And
Speaker 3 00:00:50 Close to 80.
Speaker 2 00:00:51 80, okay. I'm way under, including biologists and engineers who together are trying to understand how we can study biology through an engineering lens. We had lots of fascinating talks about, you know, how we can from, from biologists about the complexity of biology, from engineers, about how we can use engineering to understand biological systems, signaling, uh, genetic switches, circuits, just all kinds of fascinating topics. And it's been a great last few days. So Eric, you also were one of the presenters. In fact, on the first day you talked about an engineering based model of bounded adaptation. So can you explain for us what do you mean by that concept?
Speaker 3 00:01:33 I'll, I'll start it this way. A few years ago, I gave a presentation to a group about evolution. It was actually, in my view, very positive. I probably wouldn't have been even been that positive today if I were to give it again. But I had a friend who came up to me afterwards and was very upset about this presentation, said, how can you, how can you question the truth of evolution? Because we see adaptation happening. And this is really a key point because that's one of the main things that people look to when they believe in evolution, is we see some small change, whether it be you knowed or the finch beaks or the e coli, uh, those kinds of classic examples that stick out to people. And so, one of the things that I think is really important as we're building a theory of biological design as we're moving forward with the design perspective, is to understand that if we have a theory of design that's really gonna be comprehensive and useful, it helps to help us understand the small changes as well.
Speaker 3 00:02:29 And I wanna, um, you know, maybe challenge my own colleagues a little bit in this regard because we often hear people say things like, well, Darwin didn't get the big stuff right, but boy, you sure nailed it with the small changes. Or, you know, the famous phrase, uh, what is it? Darwin, uh, explained the survival of the fist, but not the arrival of the fittest or Darwin, you know, didn't explain all these big things, but way Sure, nailed it with natural selection and the small stuff. And I would say, no, no, and no. If you look at what's actually happening with organisms as they operate in the real world, in real time, you see that the evidence just doesn't support this approach. And so they're able to temporarily adapt to their environments. They're able to do things proactively, and it's just upside down and backwards.
Speaker 3 00:03:16 And so I would say no, Darwin didn't get those things right. Yes, he observed that organisms were changing. But you have to understand, Casey, what was his claim to fame? It wasn't observing that organisms adapted. Lots of people had observed that what Darwin claimed was that he had in those small changes that we were witnessing right before our eyes, organisms turning into entirely different kinds of organisms. And he said, well, it takes really long. That's why you don't see that happen. But that's the general framework of evolutionary theory, is that when we see these small scale changes, we are actually witnessing organisms turning from what they used to be into what they are now, into what they will be in in the future. So one of the things that I wanted to get across to the group at the conference here is if we think that organisms are really designed, then they should say something about how they operate in the here and now.
Speaker 3 00:04:08 If we think a system is actually designed, it should have something to say about its day-to-day operation and the way that, that it's moving forward on a regular basis. And so that's kinda a big shift in mindset that we need to have, rather than saying, well, when I see some things in biology, I'm gonna look over here for a design explanation. When I see other things in biology, I'm gonna look over here for a Darwinian explanation. We're kind of like the, you know, the bobblehead dog, where we're kinda looking around, bouncing around, trying to find an explanation. I think there's a better way to just look at even these small changes from a standpoint of design.
Speaker 2 00:04:43 Say, Eric, what you're saying right now really hits me where I'm at. Cause I took all these undergraduate graduate level courses at uc, San Diego, other places in evolution. And so I do think that, I mean, I've always thought that, yeah, a Darwinian mechanism can explain many small scale changes in organisms. Of course, I'm an ID proponent. I think that there are limits to how, how far that can go. But I've always approached it in exactly this way. So, so how does this, what you're saying, how does it relate to the popular understanding of organismal change and, and, and how we need to change our thinking?
Speaker 3 00:05:16 Sure. And, and lemme add just one more kinda theoretical point on that, because this is something that I think a lot of us don't appreciate, which is if we sort of divide and bifurcate biology between the large scale, you know, the macro revolution and the micro revolution, which you often hear, what does that mean practically? Nobody's ever seen DNA the first time it was created. Nobody's ever seen the gellan the first time it was, you know, came into existence or ATPase or wings or eyes. Okay, we haven't witnessed that. But we tend to focus on those in the ID community and say, well, we can infer design because, you know, it's too complicated. Or the probabilistic resources are insufficient for revolution and so on and so forth. It's got, you know, it's irreducibly complex. But then what we do is we turn around and say, well, you know, the peppered moss and the finch pigs and the, you know, the bacteria and the antibiotics and the fruit flies, Darin can have those, but that's what we actually observe. And so what ends up happening from a theoretical level is we end up turning over all of the things that we actually observe, all the small scale things and saying, well, dharma can have that. We'll take all the stuff that you can't observe. That's not a great approach in terms of moving forward and helping people to appreciate, appreciate design. So anyway, I just wanted to add that, sorry, I forgot the question you actually asked me, but I wanted to add that. Well, no,
Speaker 2 00:06:34 I, that's fine. I mean, so, so what do you think is a better approach than the current way of thinking about this?
Speaker 3 00:06:40 Yeah, well, um, let's go back say almost a hundred years. If you look back to, uh, Sewell Wright, who was working with how and Fisher both, and he published a paper in 1932, which talked about the fitness landscape, and he kinda gave us this fitness landscape. But what happened there is that if you look at this idea of the fitness landscape, it really doesn't hold up for a couple of reasons. So lemme back up and share one more thing. Imagine its a little hard for listeners, but I hope you can, you can visualize what I'm talking about, what I showed to the, to the group here. Imagine that you have some population of organisms and it's sitting at, at some point, um, on my chart, it's on the lower left. What evolution, uh, says is that this population or this organism will experience some environmental pressure, which will cause it to move in a particular direction.
Speaker 3 00:07:32 And if that happens over a long enough time or if the pressure is sufficient, then supposedly it'll turn into an entirely new, new kinda organism. But if you look at all of the examples that are the classic examples, you know, the peppered moss, the pys, the insects, again, all these kinds of things, that is not what we see. In fact, what we see, if you just look at the data, is that you have these organisms that vary around a norm. Ok? The finches always remained fis, the peppered MAs never became something else. The e coli is still e coli. It hasn't even turned into a different type of bacterium, much less, you know, anything more than that or some multicellular organism. So there's a great disconnect between the theory which says, Hey, we're watching an organism transform itself into something else. And the data, which says what's really happening, Casey, is these organisms are fighting mightily and valiantly to remain alive as they're to remain peppered mos to remain finches, to remain, uh, e coli.
Speaker 3 00:08:34 And the changes that they're making are allowing them to, to adapt often in real time to challenges that they experience in the environment so that they can remain e coli or phis or whatever it may be. So it's a completely different way of looking at this. And again, I would, I would just emphasize, yeah, Darwin saw some organisms changing, but he, he completely misunderstood what he was, was observing. We've gotta stop patting him on the back for completely misunderstanding what he was observing, which is not that they're turning into something else, but that they're fighting valiantly to remain the kinda organism that they're,
Speaker 2 00:09:06 What about mutations? They seem to be random, at least with respect to what the organism needs. Sometimes we see variation that is just, you know, out of left field that doesn't make any sense. So some people might say that this is still best understood within a Darwinian framework where random mutations are being selected and cied by natural selection is, does this still hold valid?
Speaker 3 00:09:27 The model that I'm presenting, and lemme just describe the model a little bit, hopefully folks can visualize it, is an engineering based model. And what that means is, if you look at how any complex functional system operates in the real world, there are going to be certain parameters, operational parameters we call them, around which that, uh, entity has to function, or within, which I should say that entity has to function. So one of the examples that I give is, if you look at a, a solar cell, uh, power graph, then you can see the voltage compared with the power, and that can be grafted out and it looks like a curve. Or if you look at the engine, uh, you've got the fuel air mixture and the power on, on fuel, air mixture on one axis and the power on another axis. And you can graph how that works out, or you can look at the torque and the speed and do a graph of that.
Speaker 3 00:10:15 And so in a really simplified version, Casey, what I show is just kind of like, uh, you know, a simple bell curve and you can kind of think of whatever that parameter is. As long as you're within that operating region, you get to continue to operate. You go outside of that, you stop operating. It's very simple and we understand that from an engineering standpoint. Now, how does that apply to a biology? Well, what I'm suggesting is that organisms also operate within parameters. And so whether that's a salinity or pH or temperature or some other factor that that organism has to take into account within its environment, as long as it keeps operating within that environment, then it gets to keep living. If once it goes outside of its operating parameters, then it dies. It's really quite simple in that regard. And so what I've, I've done is I've taken this idea of these operating parameters, which again, you can think of a bell curve.
Speaker 3 00:11:07 And now if you can visualize kinda flipping that upside down, and I do that for a reason that that maybe we can talk about. But if you, if you turn it upside down and you graph a bunch of these different parameters that are required for an organism to live in kind of a three dimensional space, you get something that looks what I call like a gravity. Well, if you can imagine that, you know, you've seen sort of the, the graphs of a gravity. Well, and as long as that organism exists within that range, it gets to keep living. And so to your question, uh, what about a situation where we have a genuine bonafide mutation or a genuine bonafide random mutation, which is sort of the typical terminology? Well, the first thing I would say, Casey, is that we're learning that many of the things we were random mutations actually aren't.
Speaker 3 00:11:49 And there's vast literature that's pushing us to concept of, of random mutations. But things do break down. Things can fall apart. You know, complex systems do fail. And so even in that case, I think it's very easy to understand what's going on in the context of an engineering type model, which is yes, things can break, but as long as it continues to function within those operating parameters, it continues to work. So let's say you've got a car, you know, this, the window breaks or something. Alright, well it, that's, that's a breakage. It's a true detriment to the overall function of the vehicle. But as long as the engine still works, as long as other things are still happening, the pistons still pump and so forth, then you still get to drive your car. So there's lots of things that can happen to organisms that can be deleterious, but they can continue to exist. And, and as long as they're within those operating parameters, great. They get to con they get to continue. If they're outside of it, they don't.
Speaker 2 00:12:47 So it sounds like you're saying that even random mutations might sort of happen within a defined range that allows an organism to continue to operate in that sort of gravity Well, space that you're saying is its survival zone. Is that, is that basically right? Or what are you saying?
Speaker 3 00:13:03 Yeah, that's well said. That's a good way to put it. So we can have different changes. You can either have proactive changes like the organism tracking the environment, and we had a great talk on that also at the conference or hedging, which another speaker talked about. You can have, uh, preprogrammed responses or you can have bonafide, you know, breaks and random mutations, but as long as all of those are within the operating parameters, it gets to operate. So I, I just think it's a more complete, it's a more, you know, wholesome fulsome way of thinking about the way that organisms operate. And we really don't need the Darwinian paradigm, which again says what you're observing is this thing turning into something else? No, it's not. It's just trying to continue to operate within this parameters.
Speaker 2 00:13:47 I feel like the first misconception or sort of normal assumption we need to get rid of is that all variation that we see is random. Mm-hmm. <affirmative>, that's not true, but some of it is. But you're saying that whether it's random or non-random, it might actually be part of a designed range in which an organism is, is designed to vary in its survival zone?
Speaker 3 00:14:06 Yeah, as long as it's still within that range. Okay. Very
Speaker 2 00:14:08 Simple. So what you're talking about right now are, are fitness landscapes where there are basically states where an organism can exist in different states, have different fitness values. Is that how you would describe it? Or how would you describe the fitness landscape if, if this is what we're talking about here?
Speaker 3 00:14:24 Yeah, so the fitness idea has gotten a lot of criticism over the years. In fact, there's a great, uh, new book that came out from the scientific publisher that has whole chapter on problems with this idea of fitness within, within evolutionary theory. Now, I guess we could come up with a fitness term in an engineering sense, but we're already talking about function. And so I prefer to talk about function rather than this word fitness, which has been really abused over the years. And I think, think even a lot of, uh, evolutionists have started to acknowledge is not really a helpful term. So, but again, back to the, to the difference here. So if you go back to Sewell's landscape and you can look up any landscape on, you know, just Google it, there's tons of these different fitness landscape. What what they always give you the impression of is that there's some peak and an organism is pushed up the peak by natural selection.
Speaker 3 00:15:13 I was, I was looking at one landscape image the other day, and it literally says, anyhow, natural selection pushes the organism up the peak as though the, the organism is some passive entity in the environment is driving it, but it's really not the case. And then what happens if it falls off the peak? Well, the natural selection will push it to some other peak. And so you have this image of these organisms kinda stuck on peaks. You know, imagine I, I flew down from Seattle a while back and there was completely cloud covered, but you could see the peaks sticking up above the clouds. And so that's what we're really evolutionary theory is asking us to imagine, is that we've got these organisms stuck on the peaks and we can't see what's down below the clouds. But, but trust us, there was a lot of really interesting stuff going on down below millions of years ago or whatever it may be in hazy of time.
Speaker 3 00:15:56 But we data is just organisms in these isolated spaces with no connection between them. Now obviously you've got two extremely closely related organisms that are from the same type or the same kind, or the same, however you wanna say that, then those are gonna be closely related. But if I look at a cat and a dog, okay, those are distantly related, nevermind a cat and an elephant. And so I think a better way to to view this is to abandon this idea of a fitness landscape that is connected through these peaks and valleys and instead view organisms the way that we, we really view them, which is they're separate isolated gravity wells if you, you allow me to use that term again, or separate isolated areas where they can survive. And so the, the, the slide that I shared to the group, which again, maybe is a little hard to visualize, but imagine you're out in space and you've got this huge distant area that you're looking at. And here and there around in distance space you see these isolated wells where certain things can operate and function properly, but they're not connected to each other.
Speaker 2 00:17:02 It's a very sci-fi image I'm looking at right now. Just for, for the record, maybe maybe you'll publish this someday, Eric. So, so is there any other evidence that you would, uh, cite in support of your model?
Speaker 3 00:17:13 Yeah, so in fact Brian Miller, uh, and I had presented this together and Brian has done a lot of work. He's got a bunch of literature that he's reviewed that shows that organisms are adapting proactively, uh, within their, their particular range of operation and that they can, if you will, fine tune knobs. One of the great examples he showed was some, some fish, I forget whether it was sticklet or Stickleback, but they have a wide range of body morphology from short and fat to long and skinny. And if you were to look at them in nature, you'd say, wow, those are wildly different, you know, wildly different species, but they're not, it's the, the same species. But what researchers have discovered is that they have some parameters, some variables that they can tune depending on what's going on in the environment, whether it be prey, whether it be the type of water that they're in. And those can actually transform the organism over generations into a very, very different looking organism without any genetic change whatsoever. Ok. This is a, an adaptation within the range of that organism's operation. And as long as it stays within that range, then it, then it's good to go. That's one area. The other very interesting presentation was from Paul Nelson, and hopefully we can get him on ID the future to share this.
Speaker 2 00:18:26 We tried, he was a little bit, uh, worn out for the weekend.
Speaker 3 00:18:28 Yeah, well, we'll catch him next week or something, but, but Paul gave a great update on what's known as orphan genes or taxonomically restricted genes. And that's not looking at an organism level, that's looking at a genetic level, right? Looking at genes, what I was looking at is sort of the classic examples of the organismal level, but Paul is finding the exact same evidence at a genetic level when you're looking at genes is that you have these widely dispersed landscapes. In fact, he and I came upon this independently. He showed a graph that was, or an image on the screen that was kind of similar to mine and said, Hey, this is like stars that are distant from each other in different parts and aren't connected. And then lastly, there was another researcher here at the conference who was talking about information theory and how when you look at sequences of functional information, um, you find that those are isolated islands that are not necessarily connected by any, any, um, connection between them, but instead they function independently as isolated islands.
Speaker 3 00:19:26 So I think all five of those, you know, really examples whether you're looking at human technology, whether you're looking at the classic examples from, you know, Darwinian evolution that we hear about the fences and so forth. Whether you're looking at the orphan genes, whether you're looking at, um, looking at information theory, I think all of these are really converging on the same truth, which is that function is hard to come by A and B, when you come by something that's functional, there's a distance between that and the next functional item. There's not this landscape. And so I would just say we need to abandon this idea of this traversable landscape. It just doesn't match up with the evidence.
Speaker 2 00:20:05 Yeah, I think, I think the name of the game here, Eric, is discontinuity. Mm-hmm. <affirmative>, we're finding discontinuity everywhere we look, whether it's at the level of individual proteins, whether it's the level of species. In just a few minutes we're gonna record another podcast on, on my talk on fossils. That's another area where we see discontinuity, but that's what we're seeing throughout biology is discontinuity and the idea that there are these fitness landscapes that connect everything, that's all below the clouds. The data that we see is isolation of various phenotypes, genotypes, whatever. So what, what's your, what's your takeaway from all of this, Eric?
Speaker 3 00:20:44 Yeah, I would just say that first of all, we need to take the design seriously and we need to stop sort of taking this view that, well, you know, there's a huge class of phenomena that are explained by evolution and all the stuff that we actually observed, but oh, by the way, there's some other things that, that, you know, it doesn't work for, you know, we need to stop saying that organisms are partly designed or kind of designed. We need to view them as deeply designed and, and purposeful and active and engaged in their environments and capable of adapting within their operating parameters. And I think when we do that, we'll come to see a level of design and capability and sophistication and engineering prowess that is just off the charts.
Speaker 2 00:21:25 I like it. And I, I would say that's my takeaway from this, this weekend as well, and I didn't expect that. I'm, I'm definitely, you guys are doing some good work on me, so. Awesome. Thank, thank you Eric. I wanna just say thank you guys for the fantastic conference that the organized and the great work that the ERG is doing. Thank
Speaker 3 00:21:41 You, Casey.
Speaker 2 00:21:42 Well, I hope that our id, the future listeners will stay tuned about the engineering research group and the projects that it's doing and a lot of the great ideas that are coming out of this. How we can use engineering and an assumption that life is designed and then make better sense of how biology works. I'm Casey Luskin with ID the Future. Thanks for listening.
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