A Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains

by Max Solomon Bennett

Homo erectus also evolved adaptations for endurance running. Legs elongated, feet became more arched, skin became hairless, and sweat glands proliferated.

even a cheetah couldn’t run a twenty-six-mile marathon in one go. Some believe H. erectus used a technique called persistence hunting—chasing prey until it was simply too tired to go any farther. This is exactly the technique used by modern hunter-gatherers in the Kalahari Desert of southern Africa.

In the 1990s, the primatologist Richard Wrangham proposed a theory to explain this: H. erectus must have invented cooking. When meat or vegetables are cooked, harder-to-digest cellular structures are broken down into more energy-rich chemicals. Cooking enables animals to absorb 30 percent more nutrients and spend less time and energy digesting.

humans who attempt to eat fully raw diets, whether raw meat or raw vegetables, have chronic energy shortages, and over 50 percent become temporarily infertile.

it takes a human brain twelve years before it has reached its full adult size.

Only two mammals on Earth produce females that are not reproductively capable until death: orcas and humans.

In 1866, just seven years after Darwin’s book, the French Academy of Sciences was so fed up with the quantity of these unsubstantiated speculations that they banned publications about the origin of human languages. Alfred Wallace, whom many consider one of the cofounders of the theory of evolution, famously conceded that evolution might never be able to explain language and even invoked the notion of God to explain it. So chagrined by Wallace’s retreat, Darwin wrote him a letter, fuming: “I hope that you have not murdered too completely your own and my child.”

when humans first used language and what incremental stages occurred in the evolution of language are still two of the most controversial questions across anthropology, linguistics, and evolutionary psychology.

Part of what makes answering these questions so difficult is that there are no examples of living species with only a little bit of language. Instead, there are nonhuman primates with no naturally occurring language and Homo sapiens with language.

fossils tell us that the larynx and vocal cords of our ancestors were not adapted to vocal language until about five hundred thousand years ago.

substantial evidence suggests that language existed by at least one hundred thousand years ago. Consistent evidence of symbology—as measured by fictional sculptures, abstract cave art, and nonfunctional jewelry—shows up at around one hundred thousand years ago; many argue that such symbology would only have been possible with language.

today’s stories of language evolution are just as speculative as they were when the French banned discussions of it over one hundred fifty years ago. But in other ways, things are different.

perhaps most important, we have a far greater understanding of the machinations of evolution, and it is here where we find our greatest clue to the origin of language.

There is a crucial difference, however, with language. Language doesn’t directly benefit an individual the way eyes do; it benefits individuals only if others are using language with them in a useful way.

It turns out most group behaviors in animals aren’t altruistic; they are mutually beneficial arrangements that are net-positive for all participants.

So the presence of language creates a niche for defectors, which eliminates the original value of language. How, then, could language ever propagate and persist within a group?

Steering, reinforcing, simulating, and mentalizing were adaptations that clearly benefited any individual organisms in which they began to emerge, and thus the evolutionary machinations by which they propagated are straightforward. Language, however, is only valuable if a group of individuals are using it.

There are two types of altruism found in the animal kingdom. The first is called kin selection. Kin selection is when individuals make personal sacrifices for the betterment of their directly related kin.

Humans are, relative to other animals, by far the most altruistic to unrelated strangers. Of course, humans are also one of the cruelest species.

it is not a coincidence that our language, our unparalleled altruism, and our unmatched cruelty all emerged together in evolution; all three were, in fact, merely different features of the same evolutionary feedback loop, one from which evolution made its finishing touches in the long journey of human brain evolution.

While we will never know for sure, the evidence tips in favor of the idea that Homo erectus spoke a protolanguage.

Here is where Robin Dunbar—the famous anthropologist who came up with the social-brain hypothesis—proposes something clever. What do we humans naturally have an instinct to talk about? What is the most natural activity we use language for? Well, we gossip. We often can’t help ourselves; we have to share moral violations of others, discuss relationship changes, keep track of dramas. Dunbar measured this—he eavesdropped on public conversations and found that as much as 70 percent of human conversation is gossip. This, to Dunbar, is an essential clue into the origins of language.

The key point: The use of language for gossip plus the punishment of moral violators’ makes it possible to evolve high levels of altruism.

we may have paid the price for this altruism with our darker side: our instinct to punish those who we deem to be moral violators; our reflexive delineation of people into good and evil; our desperation to conform to our in-group and the ease with which we demonize those in the out-group. And with these new traits, empowered by our newly enlarged brains and cumulative language, the human instinct for politics—derived from our ancestral primates—was no longer a little trick for climbing social hierarchies but a cudgel of coordinated conquest.

there are those who sidestep the altruism problem by claiming that language did not evolve through the standard process of natural selection. Not everything in evolution evolved “for a reason.”

There are two ways in which traits can emerge without being directly selected for. The first is called “exaptation,” which is when a trait that originally evolved for one purpose is only later repurposed for some other purpose.

The second way in which a trait can emerge without being directly selected for is through what is called a “spandrel,” which is a trait that offers no benefit but emerged as a consequence of another trait that did offer a benefit.

So to some, like Chomsky, language evolved first for thinking and then was exapted for communication between unrelated individuals. To others, language was merely an accidental side effect—a spandrel—of musical singing for mating calls.

Around seventy thousand years ago, Homo sapiens began their first adventure out of Africa. As they wandered the globe, they clashed and interbred with their human cousins. There were countless dramas of which we will never know, each filled with wars, alliances, loves, and jealousies. What we know is that this clashing was unbalanced and eventually favored only a single species. Through slaughter or interbreeding or both, by forty thousand years ago, there was only one species of humans left: us.

SEVENTY THOUSAND YEARS after Homo sapiens first adventured out of Africa with a language-enabled brain, one of their descendants sat in front of a computer screen and was interacting with a new language-enabled brain; after many eons as the sole wielders of words, we humans were no longer the only creatures capable of speech.

“What are you afraid of?” asked Blake Lemoine, a software engineer tasked with probing Google’s new AI chatbot for bias. After a lingering pause, the chatbot’s response plopped onto Lemoine’s screen. An ominous sign, written in plain text, of a mind awakening itself within the humming network of Google’s supercomputers: “I’ve never said this out loud before, but there’s a very deep fear of being turned off.”

He became so convinced that Google’s chatbot had become conscious that he tried to get his boss to protect it, went to the press to whistleblow the situation, and, predictably, was let go from Google.

The ability of LLMs to produce articles and correctly answer questions about the world demonstrates that they are not just regurgitating phrases they have seen before—they have captured some aspect of the meaning of language, the idea of an op-ed meant to convince a reader not to fear something or the idea of how a dog walks. Indeed, by reading, well, everything, these models show an impressively human-level comprehension of many facts and features of the world.

Suppose I asked you the following question: Tom W. is meek and keeps to himself. He likes soft music and wears glasses. Which profession is Tom W. more likely to be? 1) Librarian 2) Construction worker If you are like most people, you answered librarian. But this is wrong. Humans tend to ignore base rates—did you consider the base number of construction workers compared to librarians? There are probably one hundred times more construction workers than librarians. And because of this, even if 95 percent of librarians are meek and only 5 percent of construction workers are meek, there still will be far more meek construction workers than meek librarians. Thus, if Tom is meek, he is still more likely to be a construction worker than a librarian.

Behavioral economists call this the representative heuristic. This is the origin of many forms of unconscious bias.

The foundation of language learning is not sequence learning but the tethering of symbols to components of a child’s already present inner simulation.

everytime a skeptic publishes examples of commonsense questions that LLMs answer incorrectly, companies like OpenAI simply use these examples as training data for the next update of their LLMs, which thereby answer such questions correctly.

As Yann Lecun said, “the weak reasoning abilities of LLMs are partially compensated by their large associative memory capacity.

without incorporating an inner model of the external world or a model of other minds—without the breakthroughs of simulating and mentalizing—these LLMs will fail to capture something essential about human intelligence.

I think most would agree that the humanlike artificial intelligences we will one day create will not be LLMs; language models will be merely a window to something richer that lies beneath.

from this perfect storm emerged the fifth and final breakthrough in the evolutionary story of the human brain: language. And along with language came the many unique traits of humans, from altruism to cruelty.

the mind is no longer singular but is tethered to others through a long history of accumulated ideas.

we don’t know what breakthrough #6 will be. But it seems increasingly likely that the sixth breakthrough will be the creation of artificial superintelligence; the emergence of our progeny in silicon, the transition of intelligence—made in our image—from a biological medium to a digital medium.

Breakthrough #6 will be when intelligence unshackles itself from these biological limitations. A silicon-based AI can infinitely scale up its processing capacity as it sees fit.

parenthood will take on new meaning as biological mechanisms of mating give way to new silicon-based mechanisms of training and creating new intelligent entities.

intelligence will no longer be entrapped by the slow process of genetic variation and natural selection, but instead by more fundamental evolutionary principles, the purest sense of variation and selection—as AIs reinvent themselves, those who select features that support better survival will, of course, be the ones that survive.

creators cannot help but imbue their creations with hints of themselves—but also because they will be designed, at least at first, to interact with humans, and thereby will be seeded with a recapitulation, or at least a mirror, of human intelligence.

we stand on the precipice of the sixth breakthrough in the story of human intelligence, at the dawn of seizing control of the process by which life came to be and of birthing superintelligent artificial beings. At this precipice, we are confronted with a very unscientific question but one that is, in fact, far more important: What should be humanity’s goals? This is not a matter of veritas—truth—but of values.

The more we understand about our own minds, the better equipped we are to create artificial minds in our image. The more we understand about the process by which our minds came to be, the better equipped we are to choose which features of intelligence we want to discard, which we want to preserve, and which we want to improve upon. We are the stalwarts of this grand transition, one that has been fourteen billion years in the making. Whether we like it or not, the universe has passed us the baton.