Recently, geologist Casey Luskin interviewed Eric Cassell, author of Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts (2021) on one of the central mysteries of biology: How do animals “know” things that they can’t have figured out on their own? Here’s the first part, with transcript and notes. Below is the second part, which looks at some “how” questions.
Eric Cassell is an expert in navigation systems, including GPS whose experience includes more than four decades of experience in systems engineering related to aircraft, navigation and safety. He has long had an interest in animal navigation. His model for animal navigation is the natural algorithm: The animal’s brain is “programmed” to enable navigation.
Here’s Part II of our three-part series on “Animal Algorithms Webinar: One of Nature’s Biggest Mysteries,” (January 20, 2022), where a partial transcript and notes follow:
Casey Luskin: We already talked about this a little bit, the idea of path integration, where animals keep track of their compass heading and distance traveled so they can fly directly home — but not necessarily along the path that they took. And you say that they can do this without necessarily following landmarks. You talk about honeybees and their ability to navigate using the sun’s angle. So they can learn how to navigate using the sun’s angle at different times of day to find their way home, regardless of what time it is. Or they can use polarized light by studying different regions of the sky to determine the position of the sun. (21:23)
This requires doing trigonometry, spherical geometry, and other complex math. They [insects] have a brain with a million neurons and I have supposedly a hundred billion neurons in my brain. And I don’t think I can do those kinds of calculations in my brain. I find this all incredible.
There are cases that seem to require inherited know-how. How does a sea turtle “innately” know how to swim to its feeding area hundreds of miles through murky water and return to its exact nesting beach 35 years later? How do chicks of the Pacific golden plover find the Hawaiian Islands, mere specks in the trackless ocean, never having been there before? How do monarch butterflies in Canada get to the same trees in Mexico their great-grandparents wintered on? Some of these natural miracles cannot be dismissed easily with other labels like a “map sense” or other terms of art.Evolution News, “Uncannily Organic: Navigation Is More than Genes” at Evolution News and Science Today (January 26, 2022)
Casey Luskin: So the fact that these kinds of features evolved really just makes me wonder, how could they arise by an unguided, stepwise Darwinian process. I’d love to see a stepwise evolutionary explanation for this, if it exists. And I’m wondering, are you aware of attempts to explain behaviors like this through a standard typical Darwinian model? (21:58)
Eric Cassell: The short answer is no. I have not come across any name in the literature about those kinds of behaviors and how they could have evolved. I think it’s such a daunting task to try to explain how something is sophisticated as an algorithm, particularly a mathematical type of algorithm, could have evolved in the first place.
It has to be in the genome somehow. And then that information that’s in the genome has to be encoded in a neural network when the brain develops, and then it all has to be run, as the animal is performing the behavior. So there’s a lot of unanswered questions about how all that takes place. (22:42)
Casey Luskin: Figure 3.3 [in the book] it talks about the different components necessary for animal navigation and migration behavior to work. You’ve got to have navigation sensor physiology, a navigation algorithm. You’ve got to have destination location information, migration decision algorithm, and migratory physiology to implement all of this. And if you’re missing one of those components, one of those elements, then it doesn’t work. Those five separate groups of genes, and as you put it, other genetic information in the genome, all have to be there in order for these navigation and migration algorithms to work. (23:36)
So let’s talk about another example you give, the Monarch butterfly, which in North America requires three generations for the migration to complete itself. And so that has to be, genetically programmed because, obviously, the butterflies that are maybe in the middle of that migration pathway — how could they have learned where they’re going? They weren’t even alive when the migration started. So how did they know where to go? They’ve never been to the destination. to me that obviously implies I’m- I’m sure you- you argue this in the book, very persuasively that the information had to be pre-loaded into those organisms, when they’re born, you call it pre-loaded software. So where do they get the pre-loaded software that tells them where to go and how does this evolve by an unguided Darwinian process? (24:22)
Eric Cassell: Again, that’s a really difficult question that nobody has an answer for. There’s, there are some theories out there about how, in some cases, animals might have developed a behavior, or basically learned the behavior, and then somehow that behavior gets transferred into the genome. How that happens, that’s a good question. It’s a theory that I’ve seen, people propose, but I don’t understand how it could even work, in reality because you have a behavior that somehow then gets transmitted into the gametes and the genomes. But it’s a serious proposal that a number of people, believe in. (25:09)
Casey Luskin: It sounds very Lamarckian… So maybe there is some influence of, you know, inheritance of acquired characteristics going on here, but as you said, it’s yet to be demonstrated. So these sound very mysterious at the present time. (26:05)
Note: Jean-Baptiste Lamarck (1744–1829) was a French evolutionary thinker who held that characteristics could be acquired during the lifetime of a life form and passed on to offspring. Although at one time widely dismissed, this mechanism of evolution is becoming more widely accepted in the form of epigenetics.
Casey Luskin: Maybe 100 years ago or 2000 years ago, humans navigated much differently than they do today. So how has technology changed the way we navigate? (26:28)
Eric Cassell: Fundamentally animals are better navigators than humans. We’re able to use that information and landmarks, but other than that, humans are very poor natural navigators, whereas all of these animals are actually expert navigators. They’re all designed to perform, accurate navigation, to suit their own purposes. (27:09)
It’s only been in within the last couple of hundred years that we’ve even developed any, any useful technology for navigation. We’re basically just trying to catch up to what animals have been doing for a long time. (27:51)
Casey Luskin: I did not appreciate how important the sun is for human navigation till I moved to the Southern hemisphere during my PhD. Obviously if you’re living in the Northern hemisphere, which is where I grew up, the sun is always in the south. but when I moved to South Africa, the sun is always in the north. I lived just north of the university and there were literally a couple times where I would get in my car to drive home from school and start driving in the opposite direction, south, because in my mind I was orientating myself with the sun. I knew I was supposed to go north, and for me going north meant you drive away from the sun. I didn’t even think about it. I did not even appreciate how much, intuitively as a human being, I used the sun to navigate — until the sun was in the “wrong” place and I was going in the wrong direction. (28:28)
You also talk about spider webs in your book and, they’re probably one of the most famous examples of an amazing animal behavior. How do spiders produce silk and what does the theory say about how spiders know instinctively how to produce a web. Are there evolutionary explanations for the origin of spiderwebs? If so, what do, what do you think of them? (29:19)
Eric Cassell: The question about silk, it’s a very complex material that involves a lot of, proteins and it’s a very complex process to produce the material. Humans have been trying to duplicate [spider] silk artificially for a long time. Basically we’ve never been able to do it because it’s so complex. We have some materials that sort of approximate the composition of silk, but never really duplicate it. So that’s one thing there. (30:00)
And the process that the spiders use to generate it is a complex process, also. There has been a lot of research into web designs and, how they possibly could have evolved over time. But there are issues there as well because, for example, there are species of spiders that are completely unrelated, but yet produce the same exact web design. So how do you explain that? (30:42)
The typical Darwinian explanation that it’s convergent evolution, … selection pressure, or some other vague term but really, the origin of the webs and then how spiders are able to manipulate them is really a complex behavior that’s pretty sophisticated. (31:16)
Casey Luskin: I note that you provide a really striking quote in your book from Jerry Fodor and Massimo Piattelli-Palmarini from their book What Darwin Got Wrong (2010). They’re talking about animal behavior and they say that, “Such complex sequential, rigidly pre-programmed behavior could have gone wrong in many ways, at any one of its steps…” And they say spiderwebs, bee foraging, as we saw above and many more, “cannot be accounted for by means of optimizing physical, chemical, or geometric factors.” (32:26)
They go on to say that, “They can hardly be accounted for by gradual adaptation either. It’s fair to acknowledge that, although we bet some naturalistic explanation will one day be found, we have no such explanation at present. If we insist that natural selection is the only way to try, we will never have one.” (32:59)
These are two authors who describe themselves in their book as “outright, card carrying, signed up, dyed in the wool, no-holds-barred atheists.” And yet they’re saying that there is no Darwinian natural selection-based explanation — and they’re really doubtful there ever will be — for the origin of these complex behaviors. You also talk about a textbook that says, “We still know little about the rate and type of evolutionary change, experienced by behavioral traits.” (33:20)
Eric Cassell: In my research in the literature, for the most part, there is only one, there’s one particular type of behavior [for which] at least some theories have been proposed and that concerns insect social behavior. The basic theory is that there are, insects — ants, et cetera — that exhibit solitary behaviors. There’s, in other words, there’s a difference between those that are social and those that are solitary. (34:14)
The theory is that when an animal transitions from a solitary lifestyle to a social lifestyle, it’s just a matter of adding a few algorithms, if you will, a few steps to integrating that information into a social environment. Well, at first that sounds somewhat plausible, but the evidence really is not there that that’s the case, for two reasons. One is that the social behaviors that these animals exhibit far exceed the behaviors that solitary animals do. That’s one thing. (34:47)
The other is that insect social behavior is one area that has seen quite a bit of research into the genomes, And what’s been found is that the genomes of the social insects have undergone significant… change, when they transition from solitary to social. So there’s literally hundreds of thousands of genetic changes that take place in these animals, when they’re social. So how that could have happened through a step by step linear Darwinian fashion is not very plausible. (35:28)
Casey Luskin: So, okay. Well, this will, I think, lead into my final question during our conversational part of the interview. It sounds like a lot of information goes into the origin of these animal behaviors. So how does information important for the origin of these animal behaviors and what is your view on what this implies for intelligent design? (36:18)
Eric Cassell: These behaviors, for the most part, are controlled by algorithms in one form or another. And to have an algorithm, you have to have the information. Where does information come from that even defines the algorithm in the first place? So that’s the part that’s challenging. A lot of the research that’s been done by the ID community tends to indicate that you really can’t generate information through a- random process, which is, you know, mutations and natural selection. (36:44)
It’s just incapable of doing that. If you look at the work of design theorist William Dembski and some others, regarding these No Free Lunch theorems, that’s basically what they say. It’s difficult to explain the origin of this kind of information through a purely random process. I think that’s one of the biggest hurdles to overcome in trying to explain, the origin of these kinds of behaviors. (37:24)
Next: Challenges from the audience, as well as challenges from nature
Here’s the earlier portion of the episode, with transcript and notes.
Neuroscience mystery: How do tiny brains enable complex behavior? Eric Cassell notes that insects with brains of only a million neurons exhibit principles found only in the most advanced manmade navigation systems. How? Cassell argues in his recent book that an algorithm model is best suited to understanding the insect mind — and that of many animals.
You may also wish to read: A navigator asks animals: How do you find your way? The results are amazing. Many life forms do math they know nothing about. The question Eric Cassell: asks is, how, exactly, is so much information packed into simple brain with so few neurons?