[00:00:04] Speaker A: ID the Future, a podcast about evolution and intelligent design.
Can we trust our intuition that tells us that nature was designed? Hello and welcome to ID the Future. I'm Casey Luskin and today I'm speaking with Douglas Axe Maxwell, professor of Molecular Biology at Biola University, the founding director of Biologic Institute and the founding editor of the journal Bio Complexity. He's also the author of How Biology Confirms Our Intuition that Life Is Designed. Doug earned his PhD in biochemical engineering from Caltech, did postdoc work at the University of Cambridge, and has published his research in top journals like the Journal of Molecular Biology and Proceedings of the National Academy of Sciences. So, Doug, it's a real pleasure to have you on the podcast today.
[00:00:51] Speaker B: Doug, it's great to be here. Thank you, Casey.
[00:00:54] Speaker A: Sure. And the occasion is that we're talking about your two chapter contributions to a book that's being released in October of 2021 titled the Comprehensive Guide to Science and Exploring the Ultimate Questions about Life and the Cosmos. It's available on Amazon and I'm a co editor along with William Demski and Joseph Holden. We really appreciated your two chapters that you contributed to this book, Doug. One is titled is Is Our Intuition of Design and Nature Correct? And another is titled Can New Proteins Evolve? So I was hoping I could pick your brain about these chapters today and maybe whet our listeners appetite for what you have to say in those chapters.
[00:01:31] Speaker B: Sounds good. Let's do it.
[00:01:32] Speaker A: Okay, so you start your first chapter about whether our intuition of nature being designed is correct by giving an example of baking cookies. I'm actually glad I went back and reread this chapter in preparation for this podcast because I was trying to remember who was it that gave that example of cookies? Just sort of, you know, the cookie dough falling out of the cupboard and everything coming together just right randomly to make cookies. I couldn't remember where it was and it was from your chapter in this book. So it's a very nice example. It's an everyday activity that even a four year old intuitively knows does not happen by chance when you see cookies being baked. So what is it exactly about baking cookies that allows our design intuition to say, we know this didn't happen by chance, it was designed?
[00:02:15] Speaker B: Yeah, well, I picked, I picked that because I often quote Allison Gopnik, UC Berkeley psychology professor, as saying, by elementary school age, children start to invoke an ultimate godlike designer to explain the complexity of the world around them. Even children brought up as atheists. So that makes me think this sort of four year Old age, it even goes back further than that. But this is the sort of age of wonder where you're discovering things anew. And it turns out you don't have to be taught that there's a God in order to intuit that there's a God. When these kids see a butterfly or dragonfly or an ant, they automatically intuit that this was made by a godlike design. So I want to pick something that sort of in my mind is something that takes us back to that age, like our age of wonder. Four years old. And what could better do that than cookies?
So I start by having us go back in our imagination to that age. And we come trotting out of our bedroom because we smell something wonderful coming from the kitchen. We don't see a person in the kitchen. We don't know who did this, but we see a sheet of freshly baked hot cookies and we steal one and go back to the bedroom and eat it. Now, it would never occur to that child that these cookies are a product of accidental physical causes. It's, it's automatic. We know someone did it, even though we don't know who did it. The thinking, I think, is as simple as this.
We know by age four that there's certain things that require know how in order to be done. And those are precisely the things that we want to learn how to do. So I can imagine a four year old wanting to help mom or help dad or help brother or sister make cookies, but they're still in this learning phase where they know this is something that requires some mastery of skills. And I don't yet have them, but I want to have them.
I think that's what gears us up as human beings very early on, well before the age of four, to recognize just those sorts of things, the things that require know how, because we want to know how to do those sorts of things when we see something like a dragonfly. For a four year old to say, oh, I want to make one of those would be way beyond what their, their ambitions. They simply want to be able to make, you know, a dragonfly out of Legos or something like that. The things that they see older brother, older sister or mom or dad do. So I think it is this simple. It's as simple as seeing something that's operating at a functional level that's way beyond what the ordinary things like rocks and water and clouds and sand and mud do. We see something that's doing something way above that. We know that someone had to put it together. We knew what they were doing.
[00:04:57] Speaker A: Yeah, you asked this question. This is a paraphrase. If we know that cookies were designed and why not dragonflies? And why do people struggle so much with making that connection that if cookies were designed, then of course dragonflies must be designed.
[00:05:11] Speaker B: It has to be.
Not that there's a difference in the reasoning or the one is illegitimate and the other is legitimate. It has to be that we're all okay with saying, yes, a person made these cookies, but a number of us are not okay saying to the four year old, yes, that dragonfly was made by a godlike designer. It's a worldview thing where many of us don't want to acknowledge that God is the designer of life. And so we construct a worldview that gives us all kinds of alternatives other than God.
And we suppress these simple commonsensical four year old reasoning that's telling us, no, this was made by God. Romans 1 describes it as suppression of the truth. I think that's exactly what it is. I tell my students the people who call themselves atheists according to scripture would really be more accurately described as theophobes. They are people who dislike or hate God. They don't want anything to do with him. And it's interesting that some of the most candid atheist thinkers, some that I admire, like Thomas Nagel, is tops there. He has admitted this. He said he doesn't want this to be the kind of world that has a God over it. And he's not claiming that. That's irrational deduction. It's a gut desire.
[00:06:32] Speaker A: So Doug, you use the phrase intuition over calculation.
I love how you go through some of those studies about how children intuitively know that things were designed. Those studies are really incredible. And it actually directly contradicts a common atheist claim that we're all born atheists. I mean, can give me a break. That's not what the science says. The science suggests we're all born. Yeah, the opposite is true, that we're born theist. We intuitively recognize design. But what do you mean? Can you unpack this phrase for us? Intuition over calculation and what you mean by that.
[00:07:02] Speaker B: So I think there's this immediate thing that does not require meditation. The four year old, when they see the butterfly, just immediately is tickled by it, wants to watch it is doing something remarkable.
This four year old has already played with mud and water and sand and rocks and pebbles. But the butterfly is nothing like those things. It's floating along, finding flowers and doing all kinds of neat things. And much more remarkable in what it. What it Looks like what I mean is there's something immediate, but it turns out that this immediate thing is not devoid of intellectual content. You can methodically go back and say, okay, is it possible that what the four year old sees immediately is also verifiably true? And it turns out that this is one of those things.
I trace this back to our instinct or intuition for dealing with coincidence where there are things that we're happy to say happen just by chance. They're a coincidence, but there are things that we automatically know can't be a coincidence. They have to have a different explanation and that turns out to be very closely related to the mathematics of probability and statistics.
So we have this happy circumstance where something can be both obviously true and not need any calculation, but also provably true. Both are correct.
So we don't need the calculator to show that the 4 year old is right, but you can use the calculator and you can do something very rigorous that shows, yes, that four year old got it right. They didn't do it this way, they didn't do complex math on this, but they got it right immediately. And we can show why these probabilities blow up so outrageously. You don't need to have a number at the end of the day in order to get it right.
[00:08:50] Speaker A: Doug, you quote Richard Dawkins saying, however many ways there are of being alive, it is certain that there are vastly more ways of being dead. Why is that quote so important to our intuition that life was designed? And how can you connect that quote to this intuitive argument that you're making?
[00:09:07] Speaker B: Sure.
So that comes from my favorite Dawkins book, which is the Blind Watchmaker. I think he, I think it's an excellent book. It puts forward the case for the modern Darwinian view, the Neo Darwinian synthesis, as well as it's ever been put forward. And yet it also, by being frank and giving lots of examples, exposes the fallacy, the problems with that view. And here's one portion that I quote there from the Blind Watchmaker that really shows what's wrong with this Darwinian view. What Dawkins is saying in that quote is that he acknowledges that you cannot overcome these improbability simply by having lots of opportunities, simply by having lots of chances. So normally if something is improbable and you want to see if chance can overcome that improbability, the only way for chance to overcome an overwhelming improbability is for there to be a huge number of opportunities.
I mean, a familiar example would be the lottery. If I purchase one lottery ticket and take a guess at the winning lottery number, I'm very unlikely to win. If I wanted, if I were determined to win, I would have to purchase tens of millions of these tickets, and that would not be a good investment.
But someone is going to win by chance eventually. And the way that happens is by lots and lots and lots of people playing the lottery and taking lots and lots of guesses.
So that's the only way for extreme improbabilities to be overcome.
[00:10:39] Speaker A: So, okay, Doug, let's transition into your chapter on whether proteins can evolve. First off, what are proteins and why are they so important to assessing the creative potency of the mechanism of natural selection and random mutation?
[00:10:53] Speaker B: I think, well, what they are first is they're called macromolecules. In biology, they're molecules. And when the word molecule, everyone knows you're talking about something very, very small. Sounds like an oxymoron to say macromolecule, because it's basically saying a huge version of something that's very, very small. But that's exactly what they are. They're molecules in that they're all connected through chemical bonds.
But there's lots and lots and lots of atoms in one of these molecules. They're long chain like molecules. And what makes them ideal for testing the ability of chance events to produce something that works is they're kind of like an alphabetic sequence in that you have not 26 letters that get strung together to make words and sentences, but 20amino acids that get strung together into a chain.
And if this chain has the right properties, if the sequence is appropriate, these chains collapse and fold into three dimensional structures that could become part parts of motors, or they can be little chemical factories that catalyze chemical reactions. They do all really of the molecular scale processes inside of cells. So what you have in a single protein is the ability to test the Darwinian account of the origin of new things. It's not the origin of something as complex as a dragonfly or a butterfly, but it's the origin of something at the scale of a single molecule that has structure, and the structure is appropriate to a function. So you can test whether these things work.
That's really what. It's the laboratory tractability that really made this attractive to me. You can go into a lab and produce millions of mutant genes and test these genes by putting them in bacterial cells to find out how common it is for one of these mutants to actually perform the original function. So it's a very cool system for tackling the ideas that would be very hard to tackle at the level of a complex organism.
[00:13:05] Speaker A: That's very interesting. And you did this kind of research, Doug, you actually did research on an enzyme called beta lactamase, which is used to inactivate penicillin, like antibiotics in bacteria. It's a natural enzyme that they have that they use to basically evade penicillin and other drugs.
So can you walk us very briefly through the research you did? You have a very nice explanation in your chapter in the Comprehensive Guide to Science and Faith of just sort of sketching out how you did this research. But how did you conduct the research testing the likelihood of a sequence of amino acids yielding this functional enzyme in bacteria?
[00:13:44] Speaker B: Yeah, it was. I chose that enzyme, beta lactamase, because, as you said, this is an enzyme encoded by a gene that some bacteria have and some don't.
The ones that have it produce this enzyme, and it allows them to survive in the presence of penicillin, antibiotics, or any of the antibiotics are in that penicillin family.
What makes this particularly handy in the lab is I could mess up this gene any way I want to put these messed up versions by the millions inside bacterial cells and then put the bacterial cells on petri dishes that have a little bit of penicillin.
If the messed up version still works, then I would get a colony after a day of incubating this petri dish because it's able to chew up the penicillin and grow and divide. If the messed up version of the gene doesn't work, then no colony would appear.
The way you do this is you use two kinds of petri dishes, one that has no penicillin and the other that does. And you can see If I get 200 colonies on the one that has no penicillin and I get 20 on the one that has penicillin. That tells me that 90% of these things that I put down on the plates don't make a working beta lactamase, but 10% do. So it allows you to get good numbers for the fraction that work, the fraction that don't work, and then by just not being too ambitious and not trying to randomize the entire thing, if I did that, I'd get nothing. But if you randomize little parts and collect these numbers and then multiply out your numbers, you can get a probability for the whole thing. If you started from scratch, and we're hoping that random choice would give you a string of amino acids that works.
[00:15:35] Speaker A: Doug, you don't go into too much detail in your chapter on the the exact likelihood of getting a functional protein. But what is the likelihood that a random sequence of amino acids would yield a functional beta lactamase enzyme, according to your research?
[00:15:51] Speaker B: It's a combination of things that I actually measured. And the things I actually measured are doing these little sections of randomized genes and then putting them on the petri dishes and counting the colonies.
And then there's some sort of a model of how does this whole thing work. It has to work. The whole enzyme has to work by all these different sections, the right amino acids. That allows us to multiply these in probabilities.
And then I had kind of a Venn diagram in the original paper where I'm saying, okay, so if you step back and say, not just for beta lactamases, but for any enzyme, what do we need for it to work? Well, you're going to need a succession of things, some of which I measured with this number and some of which we can make very sort of well educated guesses about how these proteins work.
And I ended up with the result that it's about a 1 in 10 to the 77th power sequence that could be expected to fold and perform a particular specified function. Whether that's the beta lactamase function or not, I happen to measure it with beta lactamase. But the idea is that these principles of protein folding are universal. So whatever function you need, you're going to have to get the right fold for it.
So one in ten to the 77th power, there's one in. You'd write it out as one followed by 77 zeros. It's something like one in a trillion, trillion, trillion, trillion, trillion, trillion. A little bit worse than that, actually.
[00:17:18] Speaker A: And given, Doug, that there have only been about 10 to the 40th organisms that have lived on Earth over the course of Earth's entire four and a half billion year old history, that means that if every single organism that ever lived was gifted sort of a, a random sequence of amino acids that could potentially give it a functional protein, you would still be short by about 10 to the, what, 37th trials to get a single functional gene. If we're talking about a likelihood that a random sequence would give you 10, 1 in 10 to the 77 sequences would give you this functional protein. Is that, is that approximately right?
[00:17:54] Speaker B: Yeah. That's a good way to put that number into perspective is to compare it to the number of individuals in the most prolific species, or you could even say all the individuals of any kind of species that have existed on the planet. You're going to get a number of something like 1 in 10 to the 40th for a single species, I come up with a number lower than that, like 1 in 10 to the 30th, maybe. But regardless, those numbers, as large as they are, they're huge numbers. They're Nowhere near the 10 to the 77th power.
That means even if you could somehow justify saying that every single organism on the planet was a trial for getting a functional version of this new protein, if it requires a new protein fold, we would guess that that's not nearly enough trials.
[00:18:41] Speaker A: Great explanation, Dr. Axe. Thank you.
I want to go through a principle that you develop in your chapter called the Conservation of Coincidence. Obviously, evolutionary biologists like Dawkins, they will say, well, we don't have to deal with these huge improbabilities because we can evolve things one little step at a time. That first mutation gives us an advantage, and the second one builds on the first advantage and gives us an additional advantage. And eventually you get something highly unlikely. But when you break down the probabilities, when you walk up the backside of Mount Improbable, as it were, then you can actually accomplish what seems to be this highly unlikely achievement of evolving this complex feature. So what do you mean when you say conservation of coincidence? And how does that kind of, I guess, defeat this argument that you can somehow overcome these low probabilities?
[00:19:32] Speaker B: I'm not claiming that Dawkins was trying to deceive others. I think he deceived himself here. And it's an easy thing to do when you're trying to convince yourself that something that's extremely unlikely to happen by chance actually did happen by chance or by natural processes, it's easy to tell yourself a story that seems to make that more plausible. But at the end of the day, if the overall improbability is what it is, and it's extraordinarily, frighteningly improbable, whatever story you've told that you think makes it more probable is itself that improbable. I illustrate this sometimes by saying, if we were to roll a die, I've got a ten sided die. If we were to roll that ten times and write down the digits that come up, we would have one number, and it'd be a number that's 1 in 10 billion, so that's 10 to the 10th power.
And then I say to students, if I'm describing this to a class, what are the odds that you could produce one guess and get this number right? If you know it's a 10 digit number, what are the odds that you're going to be right if you produce one guess? And they say 1 in 10 billion because. And that's correct.
And then I say, well, what if we said if we're going to take five of you and line you up and each of you only has to guess two digits and the first person guesses the first two and then the second two, second, two, second. So there's five of you. You each guess two digits. You're only responsible for getting a 1 in 100 number. Right.
That seems if you don't think about this carefully, does that make it easier? Because now you only have. You have a 1% chance of being correct, whereas you had 1 in 10 billion before.
But then the students go, no, that's the same thing. It's the exact same thing. You've told a story that makes it sound like it makes it easier. Oh, I just had to do a 1 in 100. And you do that and you do that, and if we all do it, then we're done.
But at the end of the day, the improbability of that outcome is precisely what it is. It doesn't matter what story you tell.
If you're counting on chance to solve the problem, the odds are exactly what they are. Dawkins and Darwin didn't get this. And most either evolutionary biologists get this and they sweep it under the rug and ignore it, or they don't get it. Clearly, if we go back to that quote of Dawkins where he says you can mix cells together for billions of years and not once would you get a conglomeration that runs or burrows or swims or whatever he says or does anything that could even remotely be construed as working to keep the organism alive.
He thinks that it's that word random that gets him out of that, that if you throw these things together at random, it won't work. But selection is not random.
And it's true that selection is not random. But it's also true that if it's blind, its odds of hitting a small target are precisely the same as if it were random. It gives you no advantage. And that's the thing that's not often recognized.
[00:22:37] Speaker A: Well, Dr. Axe, you quote some leading atheists like Thomas Nagel, acknowledging that the likelihood of evolving a protein through Darwinian mechanisms is just too unlikely to be considered plausible. And so I really encourage our listeners to check out Doug Axe's chapters in the Comprehensive Guide to Science and Faith in especially the one on Can New Proteins Evolve? Has some really incredible and impactful quotes from atheists making these admissions. So, Dr. Axe, thank you so much for coming on the podcast today and explaining to us why our intuition that nature was designed is correct.
[00:23:12] Speaker B: It's been great to be here.
[00:23:13] Speaker A: Thank you. Well, I'm Casey Luskin. Be sure to check out the comprehensive guide to Science and Faith. It's available on Amazon. Thanks for listening.
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