The best way to renew thought is to go outside the human imagination.
– Bernard Werber, Empire of the Ants, 1991

Every generation has its own insults. It’s as if our species has a Darwinian urge to keep inventing new ways to be disrespectful to survive. One such insult we can hear teenagers say nowadays is “Go touch grass”¹. It’s a way of telling someone that they’re too hooked on the internet for their own good, and that they need to reconnect with the real world.

The irony is that when we’re young, of course, we do literally touch grass. We play outside, hands in the dirt, faces close to insects, trying to figure out a world we’re just getting to know through all our senses.

When I was around 11, I remember spending afternoons touching grass and watching ants, trying to understand what they were doing. I’d leave pieces of food or leaves on the ground and observe as they carried them away, disappearing into the earth, into their colony. I’d walk along ants, making my way through bushes, crawling under fences, to follow where they were going. At that time, we lived in this apartment on the top floor of a building in the suburbs, by an elementary school. My mother would open the small kitchen window, and from the fifth floor shout that it was time for dinner. I’d pretend not to hear her just to continue my observations. It annoyed her, but I could not help it. It was fascinating times, and reading Empire of the Ants by Bernard Werber was certainly part of the reason why.

I’ll confess that ants still fascinate me to this day. They’re somehow both simple and astonishingly complex. Each one, on its own, doesn’t seem particularly smart – no offense to ants, but I’m not expecting them to crack the mystery of dark matter anytime soon. But that they socially manage to build colonies, look out for food, communicate where the food is, organize defenses against threats, build bridges and even create tidy piles of stuff they foraged is, to say the least, baffling.

Ponder this idea for a moment: how do they do all that without Teams meetings, 3-steps strategy plans, KPIs and project managers?

It took years, and some serendipity, but I discovered there was a name for the strange order I saw in those ant colonies.

Ants, jazz, and love

Because it turns out, there’s a word for this phenomenon. It’s called emergence. It’s a concept that spans philosophy, psychology, science and arts. It can be found in the decentralized intelligence of insects (also called “swarm intelligence”), in tornados, in the pointillist paintings of Seurat or in jazz improvisations. It’s all around, and it’s a beautiful concept.

Emergence is this idea that simplicity gives rise to complexity in a way that makes the whole unpredictable just by looking at the parts. Or, to put it simply: the whole is more than the sum of its parts.

In all things which have a plurality of parts, and which are not a total aggregate but a whole of some sort distinct from the parts…
— Aristotle, Metaphysics, 8.1045a

Once you learn about it, you cannot stop noticing it: in termite mounds, bird flocks, murmuration of starlings, schooling fishes, hexagonal honeycombs, the mesmerizing patterns of snowflakes, the strange physics of superconductivity… Or even traffic flow, economic markets, viral tiktoks and ChatGPT.

Yep, that’s right, ChatGPT is also a manifestation of emergence². Sure, the math behind it is well-known, and of course its architecture is carefully designed. But how it actually works, the way it produces meaning, still holds some mystery to scientists. That’s emergence at play.

Some philosophers distinguish between two types of emergence: weak and strong. This distinction was formalized by Mark Bedau in “Weak Emergence”, building on earlier work by thinkers like Tim O’Connor, who explored the notion of “Emergent properties”. To simplify (and with apologies: traduttore, traditore), strong emergence refers to phenomena that cannot be fully understood by analyzing their parts. In contrast, weak emergence describes complex behaviors that can be explained in principle by the interactions of their components.

Think of it this way: weak emergence is like a flock of birds. It can be simulated with just three simple rules, and yet the flock forms those beautifully complex swirling shapes. It’s explainable once you understand the rules, even if it looks complex.

Strong emergence, on the other hand, refers to phenomena where no amount of analyzing the parts tells you why the whole behaves the way it does, like human consciousness, superconductivity or why you fall in love. These phenomena seem to require something extra that can’t be reduced to simpler interactions. Or at least, we don’t yet know how.

 

Whether weak or strong, these emergent phenomena are not just mesmerizing – they’re instructive. By observing ants, scientists came up with the Ant Colony Optimization (ACO) algorithm, in which virtual ants leave a virtual pheromone trail to help solve complex optimization problems like the NP-hard traveling salesman problem. Or the Lumer and Faieta’s Ant-Based Clustering (ABC) algorithm, that mimicks how ants cluster dead bodies and sort larvae to help cluster real-world data, find patterns, help with customer segmentation… Such biomimetic algorithms are brilliant in that they leverage simplicity to solve complexity through emergence.

Dreams within dreams

I’m not sure when we started simulating emergence. But one of the canonical example is Conway’s game of life, an algorithm formalized by the late mathematician John Horton Conway in 1970 and popularized by Martin Gardner. It’s simple, yet profound. Even though it’s just a game, it can be so mind-boggling sometimes that it has been extensively studied and discussed by scholars and Google even created a special animation when you search for it in 2012.

This game has had a profound impact on many people, me included. So much that every time I learned a new programming language, one of the first program I developed was an implementation of this Game of Life. In a way, it’s my “Hello, World!”.

How does it work? Conway’s game of life universe is a grid. Each cell of the grid can be live, or dead. Then you just have to implement four simple rules. At every generation:

1. Any live cell with fewer than 2 live neighbors die (underpopulation)
2. Any live cell with 2 or 3 live neighbors lives on to the next generation
3. Any live cell with more than 3 live neighbors die (overpopulation)
4. Any dead cell with exactly 3 live neighbors becomes a live cell (reproduction)

That’s it. You could play this game on a piece of paper with a pencil – but you’d need a good eraser and a lot of time. Just start with some live cells and from these simple rules, both chaos and structure emerge. It’s delightful to watch.

The community has since identified and created names for different families of patterns of cells that emerge. There are “still lifes” patterns of cells that will stay stable (you can see multiple of those in the previous gif), “oscillator” patterns that periodically regain their original shape, “spaceship” patterns that fly across the universe, “guns” that are oscillators that periodically spawn “spaceships” and so on.

If you combine wisely all these patterns, you can create meta-patterns in such a way that… Well, really, there’s no limit to what you can do, it’s Turing complete, but you have to be precise. And if you are, you can create breathtaking universes like the following colossal version of Conway’s Game of life that runs, wait for it, another Game of life. Just from 4 simple rules.

Watch closely. How amazing is that?

 
Yes, someone really programmed the Game of Life to simulate itself. An Inception-like recursive beauty. Just imagine the caring craftsmanship and the perfect touch of madness it took to make that happen. Remember, just one badly placed cell would break everything. It’s called the OTCA metapixel, and it was designed by Brice Due in 2006.

I failed at touching grass

And here I was, talking about playing outside and now I’m back talking about simulating life on computers. I think we can all agree I failed at touching grass. But that’s hardly surprising, humans are messy and unpredictable like that. We’re agents of chaos, always diverging in some weird and complex patterns. But maybe that’s also what makes us not so different from ants.

We also exhibit emergent behaviors, in massive human crowds but also in markets, memes, languages. We’ve never really needed a central planner to invent jazz, to form traffic jams or to build languages. No one invented English. No one designed Paris. They emerged. Even the way we started giving colors names (a brilliant and enlightening read) is an emergence phenomenon.

So instead of trying to optimize chaos, what if we focused on crafting a few local rules? Our own designed local rules. Not Kantian imperatives carved in stone, but guidelines simple enough for anyone to follow. Crafting simple enough rules so that, together, they would be capable of letting beauty and virtue emerge just from our actions. Wouldn’t it be amazing? But is this a novel idea?

Ants have spent tens of millions of years using the sheer power of stigmergy, leaving pheromone trails and relying on a handful of instincts, to keep both small colonies of ten ants and massive supercolonies of hundreds of millions of ants alive³. Across the ages, it might well be that something similar has already been done, by encoding our social pheromones in legal and ethical codes. And like pheromone trails, maybe our rules were not dictated to encode every step, but to bias billions of individual choices toward a livable order:

You shall not murder.
You shall not commit adultery.
You shall not steal.
You shall not give false testimony against your neighbor.
You shall not covet your neighbor’s house…
— Exodus, 20:13-17 (NIV)

… and let emergence do its trick. Although, we should definitely have a rule to go touch grass.