Evolution and Cognition

(This month’s post features a photo of Stentor coeruleus by Jasper Nance on Flickr. Under a microscope, this little guy looks translucent white, with green and brown bubbles trapped inside of it. It’s roughly cone shaped, rooted to some debris at its narrow base, bent at a ninety degree angle as its wide, cilia-lined mouth quests about for food)

Sometimes I like to talk about all sorts of living things as “intelligent,” even ones that are very simple and reflexive in their behaviors. That’s because I tend to think of the process of evolution itself, and everything it creates, as intelligent. In some sense, I feel like the simplest of creatures are particularly intelligent in their design, because they don’t waste any effort on “thinking” or complexity when they don’t have to. But this isn’t how most people use the word “intelligent,” which is a problem. It’s not a particularly well defined word, either, so I think my view deserves some clarification. How are evolution and cognition related to each other? That’s something I’ve been thinking about a lot lately.

Perhaps it’s best to start with some of the simplest life on the planet: bacteria. They are basically just little robots, controlled by a simple “computer” made out of proteins and genes (here’s a great book on the subject). They certainly don’t “think” like we do, but they do perceive their environment and respond to it appropriately. They seem to have a model of their tiny selves, and their relationship with their environment, that lets them make good decisions from moment to moment, to survive in a hostile world with intermittent food, and many poisons and predators about. They aren’t particularly creative, but their evolved programming can handle a very wide range of contingencies, responding in appropriate ways to just about anything that their ancestors have encountered in the past.

Even very simple computer programs can learn. It’s just a matter of observing when two experiences tend to go together, and recording that association for later. This is all that “AI” is doing, and it can be shockingly effective. There’s no reason that a “computer” made of proteins and genes couldn’t do the same thing. But simple cells like bacteria don’t need to do this. They reproduce so quickly, they can simply evolve instead. The difference is surprisingly subtle. Bacteria use a relatively fixed “program” for themselves. Unlike a mind, it isn’t made to reorganize itself to conform with experiences in the world, it just does what it does. However, this “fixed” program is constantly being subjected to random edits (mutations), so it does change. The main difference is that genes accommodate to the environment by death and survival, rather than learning within a lifetime. Bacteria are incredibly prolific. E. coli can easily fill a single square millimeter with over 10 billion cells, and a population can double in twenty minutes. As long as some of the random edits are good, and they spread quickly, bacteria can adapt in real time to their changing environment, without learning.

What’s interesting is that more complex cells do seem to learn. Animals like you and me are built out of vast numbers of eukaryotic cells, but our ancestors were actually single-celled eukaryotes, and there are still plenty of those thriving out in the wild today. These cells are much larger and more complex than bacteria. In the past, they actually swallowed up other cells, that went on living inside of them. So, they’re actually like little clusters of several cells in one, working together as a team. Thanks to one of these symbiotic partners, mitochondria, eukaryote cells have a much larger energy budget than bacteria. Their genomes also have much more complex structure and regulatory mechanisms. They can actually re-write the instructions in their genes after reading them, using a process called splicing. We’re still not completely sure that these single cells do what we’d call “learning,” because we only recently thought to look for that, and it’s rather difficult to prove definitively. But there’s good reason to suspect they can.

There’s a single-celled eukaryote called Stentor coeruleus that is shaped like a tiny trumpet. It’s actually considered to be huge for a single cell, at a whopping two millimeters long. That may not seem like much, but it’s 1,000 times bigger than an E. coli bacterium. This little guy is very sensitive to vibrations, which it uses to detect predators. When it feels threatened, it contracts into a tiny ball to make itself harder to catch. What’s interesting, though, is that when it feels the same vibration over and over again and doesn’t get eaten, it learns to ignore vibrations at that frequency (but not other frequencies). That learning is flexible, because if the vibrations get stronger (as if the predator were getting closer, perhaps), it can change its mind and go back to treating them as a threat. This sort of behavior is pretty simple, but I would consider it “intelligent” in a minimal sense. It has a non-trivial model of the world that it updates in real time without having to evolve to do it.

As organisms get larger and more complex, they also become slower. They move more slowly and they reproduce more slowly. They also tend to have larger, more complex genomes which are much harder to successfully edit with random mutations. As this happens, life needs to find ways to keep responding quickly, and one solution is to invest more in cognition. Even single celled organisms like Stentor seem to do this. Larger organisms like plants have even more complex cognition. Plants may not seem very intelligent, but they can learn, behave strategically, and even communicate. They interpret clues over a season to guess when it’s safe to grow, they maneuver around obstacles and each other to get access to light, and warn each other when pests show up. This isn’t thoughtful, exactly, but neither is it simply hard-wired. There’s flexibility, context sensitivity, memory. Real, non-trivial computation. More complex organisms, like animals, have even evolved their own specialized “computers” built out of cells: brains. They are much more intelligent than plants, in one sense, because their behavior is so much more flexible and dynamic. They really can think, which for most people seems to be the gold standard for intelligence.

The powerful thing about investing in cognition is that it makes evolution easier. An intelligent organism doesn’t need to evolve exactly the right behavior for a situation, it just needs to be “close enough” from birth that learning can take it the rest of the way. For instance, most animals have to learn how to walk. That means when an animal is born a little different, say with legs that are shorter than usual, it can figure out how to work with that. In fact, if having short legs turns out to be useful, they might do better than their peers, even if they have a body type never seen before in their family history. If a species has to re-learn the same behavior in every generation in order to survive, then natural selection will favor individuals that learn that skill more easily and reliably. For instance, baby deer learn to walk very quickly, seemingly because they are born with some innate clues for how to do this, and an urgent desire to do so. In this way, behaviors that were at first creative solutions to novel problems can slowly become reliable programs encoded in the genes. This sort of dynamic is sometimes called “genetic assimilation” or “the Baldwin Effect,” and it’s one of the key ways that life uses its evolved intelligence to shape the process of evolution to make it more efficient.

This is why I like to think of evolution and cognition as continuous with one another. They are different things, but they are both kinds of learning, just happening on different time scales, and there is flow between them. Flexible cognition can make evolution much easier, and evolution can generate new opportunities for cognition to work with. You might say that organisms like bacteria, which are little more than fully-automated evolved mechanisms, aren’t intelligent because their behaviors are rigid and can’t adapt without evolution. But perhaps an evolving population of bacteria is intelligent? It can be quite flexible and dynamic, adapting to dramatic changes in the environment in minutes. This is why they can be so difficult to control, and often very challenging for our immune system (which is very intelligent and flexible) to keep up with.

Organisms like plants rely a lot on evolved mechanisms, but they also have some minimal real-time learning and flexible behavior, so I would consider even a single plant to be intelligent. Animal species like insects, reptiles, and mammals shift the balance even further toward real-time cognition. In a sense, every organism is precisely as smart as it needs to be to live its lifestyle. If it can be successful and thrive without expensive, complicated, biological computation that can learn in real time, that’s a good “design.” I consider that to be intelligent, even if the organism itself doesn’t seem so intelligent. Every organism evolved from a single common ancestor, and has had just as much time to adapt. Some have become extremely good at being extremely simple, with precisely honed, fully automatic routines controlled by genetics that have stayed stable for hundreds of millions of years. Others have less refined innate behaviors, and make up for it with flexible learning and cognition. Neither option is better, and evolution explores the full range of that spectrum, finding a huge variety of strategies to survive and thrive in a complex world!

Status Update: DISI and ALife

(This post’s photo was taken by me at the castle ruins in St. Andrews, Scotland. This is the front of the castle, as seen from the inside. It’s basically just one wall, with the ones on either side collapsed. The wall itself has a main gate to the right, passages on a second story running along the whole wall with windows to the outside, and a crumbling tower to the left. The inside floor is short trimmed grass, with a recently walkway added recently to minimize erosion, made of small parallel slats set flush to the ground. This was shot on a beautiful sunny day, with a lovely blue sky and just a few wispy clouds.)

It’s been a while since I gave a status update. Things are going really well! I’m mostly done with the course requirements for my PhD. Just two more classes to take, and they can be whatever I want, so I might do some independent studies to blend my research with my learning. I just got back from a summer institute, which was a new and fulfilling experience for me! I had a great time, learned a lot, and met some truly incredible people. I also just found that the paper I submitted to the 2025 Artificial Life conference was accepted! Let me share a bit more about all that…

This summer I got to attend the Diverse Intelligences Summer Institute (disi.org), in St. Andrews, Scotland. It was a three-week immersive experience, full of lectures, events, projects, and networking. They brought together researchers from around the globe, studying intelligence from different perspectives. There were folks who study bats, birds, primates, or dogs in the field or in the lab, trying to test their cognitive abilities or unravel the complexity of their communications. There were philosophers, trying to wrap their heads around AI, language, society and more. There were folks studying gut feelings, and psychedelic therapies in humans. Folks doing science communication and wearable art. Folks studying how animals evolve, how software evolves, and how to build evolving cybersecurity systems modeled on the immune system. And so much more! It was truly incredible to meet so many brilliant and interesting people, to explore all our different specialties, and to see how they blend into one another.

St. Andrews itself is a lovely venue, with beautiful beaches, medieval ruins, and one of the oldest universities in the world. It’s also home to the first golf course, which makes it a sort of Mecca for golfers, though that didn’t mean a whole lot to me. I was there in July, when the weather was 60° F (15° C), with a lovely sea breeze, and lots of sunshine, which is pretty unusual for Scotland. The town center was cute, with plenty of pubs, shops, and restaurants, but I also got to explore nature quite a bit, walking along the coastline, hiking in the woods, and visiting the lovely botanical gardens. This was only my second visit to the UK, and the first time where I wasn’t just stuck in a big city. It was a very different biome than I’m used to, so it was fun to see the fine, dark sands, and the dramatic cliff sides and castle ruins overlooking the beach. I also got to see flowers and bees and all sorts of other plants and critters that were new to me.

As part of DISI, I did a group project with four other people. We were thinking about how animals pick up on lots of different cues in their environment to figure out what’s going on. We drew inspiration from a paper on cultural intelligence, where they talked about about “calendar plants.” A good example of that might be some berry bushes that fruit at about the same time that the deer are ready to hunt in a particular locale. We were wondering, when is it better to look for a sign that’s easier to spot but indirect and unreliable (like whether the berries are ripe), rather than paying a high cost to be sure about what you really care about (like scouting for deer)? We made a mathematical model that could work for a wide variety of systems like this, solved some simple versions of that model by hand, then used an evolutionary algorithm to validate our results and scale to larger, more complex systems. This is a bit of a departure from my usual research, but I thought it was a neat idea, I really enjoyed getting to work with biologists and philosophers on a project, and I had fun coding up a simulation of evolution in an unpredictable environment. I got to a probabilistic programming language (probmods.org), which was new to me and hopefully useful in the future!

I really appreciate what the folks at DISI are doing. Fundamentally, I think intelligence is a diverse, messy, and tangled thing, so the only way to study it properly is with a mix of many different perspectives. It’s incredibly useful to see what problems other fields are investigating, and what tools they use to do that. Some ideas transfer really well between fields, and there’s some great opportunities for collaborations at the intersections between them. It’s fantastic to get a chance to do that sort of cross-pollination, and to meet so many folks who care about related topics and who are eager for new perspectives. I made fast friends with several researchers and science communicators who I hope to stay in touch with and maybe collaborate with in the future! I’m really grateful I got to participate, and I’d highly recommend it to anyone who feels like it might be a good fit for them.

I’m also very excited about getting a paper accepted at ALife. I’m very proud of that paper, and will be sharing a longer write-up about it here once it’s published. I’m also excited to attend the conference! Artificial Life is a field of research that studies “life as it might have been.” Basically, it’s a catch all for a very wide variety of experiments where someone builds a model (usually a computer program) inspired by biology, just to see what will happen. The hope is that, even though life itself is incredibly complex, perhaps simple simulations that recreate just a bit of its mysterious qualities could help us understand life better. The kinds of experiments featured there range from small and simple tests of specific hypothesis about animal behavior, to vast and beautiful simulated worlds that can are incredibly lifelike and nearly as mysterious as the real thing. This year’s conference is in Kyoto, Japan, which is exciting for two reasons. First, Japan is kind of the center of the ALife world. They have a lot of ALife specialists, and a lot of great work comes from there. Also: My wife Christina and I have always wanted to visit Japan, and this is a perfect opportunity to do it together!

The ALife conference will be in October, and I imagine the paper will be published around that time. Hopefully my travels will go smoothly, and after the event I can share my experience as well as my work with you here.

What Intelligence is Not

(The photo from this post is of a squirrel monkey eating fruit in a tree branch. The monkey is tiny, with golden / silver fur, pale pink skin, and a dark skull cap pattern. The fruit is small and red, perhaps a date. Used without modification under the creative commons license – source)

Life has been steadily driving towards greater and greater intelligence, eventually leading to human beings, who are the very pinnacle of this trend. Our superior minds are what separate us from the animals. They empower us to make a world of human flourishing, and justify our dominion over the planet. These tropes about intelligence are so common in our culture, they almost sound self-evident. Yet, I’ll argue that they’re completely wrong. These ideas are enticing because they appeal to our pride and our sense of specialness, but this way of thinking is destroying our world. So, let’s break down these myths and talk about what intelligence is not.

One problem with this story is it presents intelligence as a linear thing. Life started out dumb, and it gradually got smarter and smarter. In a sense, this is true. More intelligent life is more complicated, so it takes longer to evolve. But life doesn’t evolve towards anything, it evolves in all directions, finding and filling every niche available. Monkeys are brilliant at navigating tree branches and spotting ripe fruit. Trees are brilliant at producing the right amount of fruit at the right moment to use local resources efficiently and maximize the spread of their seeds. Yeasts are brilliant at performing alchemy on that fruit, transmuting sugar into alcohol, which the monkeys love. These are all different kinds of intelligence, and none is “better” than the other because they’re all contextual and interdependent. Every instance of intelligence looks different, because it’s adapted to a unique lifestyle.

We live a very complicated lifestyle that depends on our big brains, so we tend to think that more intelligence is better, but that’s just not the case. Some of the simplest, dumbest organisms on Earth are also the most successful. Microbes, fungus, and plants make up something like 99.5% of Earth’s biomass, while animals (the “smart”ones) make up the rest. Being smart is metabolically expensive. Taking time to think can mean missing a moment of opportunity. Sometimes real intelligence is knowing when a mindless strategy works best. If anything, humans are a great example of how intelligence can backfire. We’ve used our intelligence to make civilization, which is amazing! But in doing so, we accidentally drove many species to extinction, exhausted resources we depend on, and destabilized the global climate. Our kind of big-brained intelligence is a high risk, high reward strategy.

This brings us to the idea that humans are the pinnacle of intelligence. The problem with a word like “pinnacle” is it suggests we are the ultimate form—the thing life’s been building up to, all this time. But we’re not the end of anything. We’re still evolving, and it’s unclear whether our intelligence will go up or down from here. We’re also not the only ones. There are a handful of species that have gone “all in” on the strategy of super intelligence. You know, elephants, dolphins, octopi, the usual suspects. Humans may, in fact, be the smartest of them all, but since intelligence is so contextual, it’s hard to say. Maybe dolphins are more intelligent than us, it just looks different in an ocean species with no hands?

It may seem obvious that human intelligence is something more and different from those other species. We invented the wheel, New York, wars and so on. But that really isn’t because we as individuals are so smart. This is made clear by the tragic case of “wild children,” who grow up without parents or any human community. In the few cases we’ve observed, these children were described as animalistic, violent, and cognitively impaired. They were never able to recover or integrate into human society. Our brains alone do not set us apart from animals. Our society does, and that’s a separate thing, that evolved after our big brains. We’re smarter than other animals not because of our biology, but because of the vast library of practical knowledge and resources that we share with one another.

That’s what sets us apart: other species can’t access human culture. In a sense, that’s because those species are less intelligent; to fully appreciate human society, you need language and abstract thought, which many species lack completely. Yet some species thrive in human society anyway. By being useful (like wheat), or charismatic (like dogs), or sneaky (like raccoons) other species live with us and shape our human world. That’s because nature does not set humans apart from other animals. We set ourselves apart from other life by building walls, by excluding them from our world, to the extent that we can. We decide what plants and animals are pets, food, or pests. Other species don’t need language to live in human society if we choose to accommodate them. We can coexist with nature in community, as many human societies have, and still do. Or, we can perpetuate the myth that we are special to justify excluding and exploiting nature instead.

And, ultimately, that’s the problem with this notion of intelligence: we use it to draw a line between friend and resource. If smarter is better—if our intelligence is what sets us apart from other life, and gives us the right to exploit that life however we see fit—then where do we draw the line? Should smarter people get more rights and privileges than dumber ones? Is a disabled person no better than an animal? Should we simply recycle the feeble minded from our population? This line of thinking is revolting, and it only makes sense if you believe these myths about intelligence. Similarly, if anything less than human is just a dumb resource for us to exploit, why not pave the planet? What’s wrong with processing all of that biomass, every living thing on Earth, into fuel and plastics? I think intuitively we know why: life has a right to exist, and losing all those diverse and beautiful kinds of intelligence would be tragic.

I’m excited to live in a time when our understanding of intelligence is changing so rapidly. It’s hard to define the word, just because we have so many examples that pull in different directions, and seem to contradict one another. Intelligence is many things, and we’re still fleshing out the full picture. Yet, every day we see more clearly that our old conceptions of intelligence that put human beings on a pedestal were wrong, and, more importantly, that they are at the root of so much injustice and destruction. So, while these tropes are still everywhere around us, shape the way our world works, and may still feel intuitively true, I urge you to reject them. We must move on, and embrace a more expansive view, one that doesn’t start from the premise of who to exclude.

The Universe Evolves

(This month’s featured image is a photo of the Carina Nebula taken by NASA’s James Webb telescope. It’s a vast cloud of gas and dust, slowly condensing, with hundreds of stars visible in the background behind it. The colorized image almost looks like orange mountains with a blue mist rising from them, set on a black background with bright, six-sided starbursts.)

Normally, when we talk about evolution, we mean what life does. It’s Darwin’s magic formula. You need reproduction. You need to pass on a copy of your genes, with a little variation, so things don’t just stay the same. Natural selection will weed out the less fit individuals, so they have fewer kids. The more fit individuals become more prevalent and, over time, life as a whole evolves to be more fit. Yet, this isn’t a very satisfying story. For one thing, how did it begin? Did life just start evolving out of the blue? I think story is more compelling if we think about evolution a bit more abstractly. In a sense, the physical universe itself evolves. It doesn’t have reproduction and inheritance, but it sure does have variation and selection, and this has caused it to change dramatically over the course of history.

For the first 370,000 years or so, all of space was filled with a boring, homogeneous cloud of energy and plasma. That universe is now extinct, and for one simple reason: it was unstable. In our universe, stability is the ultimate definition of “fitness.” What persists, exists. Patterns of matter and energy that get generated more often and stick around longer become more prevalent. Those that are rare and fragile exist only fleetingly. The plasma universe is gone because gravity causes matter to clump together. It was like a pencil, balanced on its tip. As soon as it became just a little unbalanced, it rapidly fell farther and farther away from that delicate equilibrium. Plasma condensed into molecules, gas clouds, and stars.

Of course, evolution needs variation to work. To find what’s better, you need to weed out what’s worse. For life, reproduction is the engine of variation, but that isn’t necessary if you have unimaginably vast scale. The universe started out with very little variation, but it steadily increased as matter interacted with itself. Gravity caused hydrogen molecules to group together in uneven clumps, and held them there. They sat around for millions of years, slowly growing bigger, until the force of their own weight ignited a fusion reaction. The gas clouds became stars, and in their cores new elements were born. The universe’s population gradually became more diverse.

That’s the counterintuitive thing about stability: it can generate diversity. When patterns become more numerous, and they stick around for longer, chaos starts to kick in. Every star and every planet is a little different. They have unique histories and influences and opportunities. They might be richer in this element or that one, bigger or smaller, hotter or colder, more or less affected by collisions. This diversity only compounds over time, as these objects smash together and interact in complex ways. The longer they stick around, the more they change, recombine, and become more elaborate.

So, for 13 billion years, the universe evolved. Its population became stranger and more complicated. Today we have about a hundred “naturally occurring” elements that didn’t exist at first, but had to evolve through multiple generations of stars fusing atoms, exploding violently, and gradually reforming. We have many kinds of stars, planets, solar systems, and galaxies, that support an astonishing variety of chemical processes that have had a very, very long time to develop. They produce “primordial soups,” pocket environments full of useful molecules for life, a steady energy source, and self-perpetuating chemical reactions. We think this happened at least once to seed all life on Earth, but it may in fact be very common.

I think this story is an essential foundation for understanding evolution as life does it. Because life didn’t start this process. The universe provides energy and raw materials in vast amounts. It provides the chaos and entropy that drives seemingly random variation, and the slow, continual breaking down that causes natural selection to prefer stable, commonly made forms. The laws of physics cause the universe to evolve towards stability, diversity, and complexity, at least for a while, until it starts to wind down again and settle into entropy. Life merely constrains that process, making it more efficient and productive, for the simple reason that matter that does so becomes more prevalent.

In these primordial soups, some chemical systems evolved to enclose themselves in bubbles, protecting delicate reactions from the outside world. These self-made “individuals” evolved regular cycles of reproduction, explicitly making copies of themselves rather than waiting for the right reactants to come together again by chance. They evolved DNA to constrain these copies, and make them more precise reproductions of the original. They evolved sophisticated error checking, which made the copies more robust and reliable. But this also gave life the power to manage variation across generations, and thus shape its own evolution. Life evolved sex to further manage variation, accelerating innovation by sharing genetic recipes across lineages. Life evolved an astonishing variety of sexual and reproductive practices, allowing it to evolve in different ways, with different patterns of variation and selection, each suited to a different range of environments and lifestyles.

The physical Universe evolves—in the most primitive way imaginable, but it still produces stability and complexity in a vast number of diverse forms. It generates the seeds of life, without any guidance or direction. Life evolves differently, because it constrains this process, making it discrete, digital, and managed. This started very simply, just discovering chemical reactions that isolate and maintain themselves. But perhaps this is the origin of what we think of as “intelligence” or “agency”? Without noticing, matter became “opinionated,” preferring certain forms and acting explicitly to promote them. From there, life’s “opinions” about itself only became more demanding and elaborate.

We often present evolution as one simple story, but there are many ways to evolve. Evolution is more like a general principle than a specific algorithm. Even just life as we know it, all based on the DNA molecule, has invented an astonishing variety of different and complex ways of evolving. Bacteria, fungi, plants, and animals use DNA differently. They grow, behave, and reproduce in completely different ways. How many other ways might there be to do it? When we present evolution as a single, constant thing, we limit our imagination. Evolution evolves, and it takes as many diverse forms as it makes.