A funny thing happens to languages that have huge numbers of speakers: over time, they seem to simplify. They lose all the fiddly bits that make languages like Hungarian so incredibly hard to learn, and instead become more regular and grammatically simple.

But at the same time that the grammatical challenge of these languages shrinks, their vocabulary explodes. This leaves a mystery for researchers who study how language structures emerge in humans: why does population size seem to drive increased complexity in vocabulary but reduced complexity in grammar? There are some intuitive answers to this question, but we need to confirm whether those intuitions are backed up by data.

Evolutionary linguists Florencia Reali, Nick Chater, and Morten Christiansen have used a computational simulation to suggest an answer: the two different kinds of complexity are very different in how easy they are to learn, and they're passed on to others through conversation. Their results imply that “language, and possibly other aspects of culture, may become simpler at the structural level as our world becomes increasingly interconnected,” they write.

Lots of words, little grammar

English, despite its reputation for being difficult to learn, is on the simpler end of languages when it comes to structural complexity. Compare it to a language like Serbian, where a noun changes form depending on how it is used in a sentence: a book is knjiga, but in I see the book it becomes vidim knjigu, and about the book is o knjizi. Those are only a few of the possible forms. In English? It's just “book,” regardless of whether you’re reading it, talking about it, or hitting someone over the head with it.

Of course, English has its famously nutty spelling system and plenty of other eccentricities—no language is absolutely simple or absolutely complex. But it's the Serbian style of complexity that seems to go hand in hand with population size. Languages spoken by small numbers of people, like small groups of hunter-gatherers, are rife with this complexity. Languages spoken by huge populations, like Mandarin Chinese, tend to have less of it.

One possible explanation for this is how old people are when they learn different kinds of languages. Small, in-group languages tend to be learned in infancy, when the brain is astonishingly adept at learning complicated linguistic systems and large lists of exceptions to the rules. But languages like English and Chinese are learned by huge numbers of people later in life, including adulthood, when the brain has become much less cooperative. So, one hypothesis goes, the features that are harder to learn in later life get lost from languages that are learned by plenty of second-language speakers.

But Reali, Chater, and Christiansen think we can make that explanation even simpler and not worry about when in life a language is learned. They point to evidence that vocabulary is easier to learn than fiddly grammar, and the team suggests that, when you combine this ease of learning with different population sizes, the results we see in languages around us fall out naturally.

Town bot and country bot

To show how this works, they built a simulated computational world. In this world, simulated language learners, in the form of mini-bots, communicate with each other. They can use existing conventions or make up new ones. The more times a bot has come across a convention, the more likely it is to use that convention itself.

Some conventions are easy, like a new word, and can be adopted into a bot’s repertoire after hearing it only once. Others, like complex grammatical structures, require more exposure. And while they’re learning new usages constantly, the bots also forget them sometimes, matching the real cognitive constraints of human brains.

These sociable bots were left to interact in groups of different sizes. Small populations have social networks that echo small villages: bots come across each other again and again and again, talking to the same individuals constantly. In larger populations, it’s more like a city, with each bot encountering a wider variety of different individuals.

The city bots end up having less of a chance to learn the hard conventions from one another because their interactions are often transient—they don’t have the same opportunities for repeated exposure. The village bots will come across the hard conventions repeatedly and learn more of them. But the city bots have creativity on their side: there are far more individuals who can invent things, and once they’re invented, if they’re easy to learn, they spread widely. The result of repeated simulations looked a lot like the real world. Small populations developed more hard-to-learn conventions, while large populations innovated more easy-to-learn conventions.

This shows just how few simple parameters are needed to explain what we see in language: differences in ease of learning and differences in the interaction patterns of small and large populations.

Reali and her colleagues point out that there’s obviously much more going on in the real world: “It is likely, of course, that many additional forces have shaped the relative development of different aspects of linguistic complexity,” they write. But this is a neat and clean explanation of the basic pattern we see in the world’s languages.

Does globalization lead to simple pop music?

Language is just one of the behaviors that humans pass along to each other culturally. It’s possible that the same processes apply to non-linguistic culture like music, too. There’s less evidence available on that question, but “new and structurally complex, and difficult to acquire, cultural forms develop in small, tight-knit communities who interact intensely, as in the birth of bebop in 1940s New York,” Reali and colleagues argue.

This contrasts with the general melodic and harmonic simplicity of widespread popular music, they suggest. “Perhaps an increase in community size might be associated with a reduction in the prevalence of complex dances, music, rituals, myths, or religious beliefs, but an increase in the prevalence of simpler variants.”

But our current global interconnectedness also allows us to self-organize into small, tight-knit groups, and Reali and colleagues point out that these are the kinds of groups that “innovate and propagate cultural forms of high complexity.” So, for every inescapable piece of simple pop, there's an intricate piece of black metal—along with a community of fans developing their own language to describe it.

Proceedings of the Royal Society B: Biological Sciences, 2018. DOI: 10.1098/rspb.2017.2586 (About DOIs).