SECTION: Features; Pg. 30

LENGTH: 2668 words

HEADLINE: The language bug;
Could language be a parasite that has evolved to fit a unique ecological niche, the human brain? Ken Grimes investigates

BYLINE: Ken Grimes; Ken Grimes is a freelance science writer based in London

BODY:
AT THE University of Edinburgh, Simon Kirby and his colleagues are running a world-record-breaking game of Chinese whispers. At any one time, hundreds of players may be passing on literally millions of whispers. A single game can last for many generations, with old players dying and being replaced by new ones. And these games are repeated, with slight variations in rules, many thousands of times. A somewhat whimsical research project? "Far from it," says Kirby. "What we are actually doing is uncovering the origins of the most fundamental property that makes us human -- language."

Of course Kirby's "players" are not real people. They are artificial agents, composed of hundreds of lines of computer code. His "game" is a complex computer simulation. And the "whispers" are phrases in an artificial language, mutating through time as they are repeatedly spoken, heard and spoken again by different agents. Just as in a real game of Chinese whispers, the interesting thing is to see how utterances change along the way. And that is central to Kirby's unusual take on the evolution of language, because he and his team choose to focus on what is spoken, rather than on the speaker. They are working within a new linguistic paradigm, one which considers language as an organism evolved to fit a unique ecological niche -- the human brain.

In this view, language is a parasite, unable to live without us. Although we don't need the "language bug" we give it houseroom in our brains because it allows us to do clever and useful things that we couldn't otherwise do. Morten Christiansen, who pioneered similar research in his lab at Cornell University, New York, uses more technical terms to describe the relationship. Language, he says, is a "non-obligate mutualistic endo-symbiont". That puts it in the same category as microbes that live in our guts and earn "free" food and board in return for helping us process otherwise indigestible B vitamins.

Orthodox ideas of language evolution emphasise how natural selection shaped our ancestors to improve their talent for complex communication. Noam Chomsky from the Massachusetts Institute of Technology famously pointed out that infants learn language quickly and reliably from sparse and chaotic input. For him and many linguists, this "poverty of the stimulus", as it is known, is evidence that much of our language ability is innate, directly encoded in our genome, and takes the form of a neurologically hard-wired universal grammar. Chomsky's colleague Steven Pinker argues that the ability to communicate effectively would have given early humans a "fitness" advantage. Natural selection favoured genetic mutations that improved our language faculty, so they spread through the hominid gene pool. The legacy is that we all have brains adapted for speech.

"But what if our brains are not so specifically designed for language?" asks Kirby. "What if we appear to be biologically adapted to language because language has culturally adapted to us?" Christiansen points out that language changes far faster than biology. Languages as different as Danish and Hindi have evolved in less than 5000 years from a common Proto-Indo-European ancestor. Yet it took between 100,000 and 200,000 years for modern humans to evolve from archaic Homo sapiens. "Of course language confers selective advantages on our species," says Christiansen. But, he argues, humans can survive without language, whereas the language bug has to adapt and evolve to live with us, otherwise it will become extinct. "Languages that are hard for humans to learn simply die out, or, more likely, never even come into existence," he says.

It may seem like a minor shift in perspective, but the implications of this way of thinking are radical. For a start, Christiansen questions the need to invoke a Chomskian universal grammar at all. Instead, he argues, language has adapted to plug into more general cognitive processing capacities that were already part of our ancestors' brains before language came along. Among these, Christiansen is focusing on "sequential learning" -- the ability to encode and represent the order of the discrete elements in a sequence. This ability is not unique to humans: mountain gorillas, for example, use it in the complicated preparation of certain spiky plant foods, where a sequence of tasks is required to remove the edible part. The idea that sequential learning underlies language has been given a boost recently by studies of people who have a medical condition known as aphasia, in which language impairment is associated with a breakdown of more general, non-linguistic sequencing abilities, such as the ability to copy a sequence of hand movements.

Christiansen's hypothesis is simple: if neural networks designed for sequential learning -- but without any built-in linguistic knowledge -- can learn languages as we do, then there is little need to invoke a universal grammar. In one experiment, he exposed his agents to 32 different artificial grammars, each of which possessed different rules for word-order in sentences. He found the agents could learn the languages. What's more, there was a correlation between how easily they learned an artificial grammar and how often a similar grammar occurs among the 6000 languages humans use in the real world. Further evidence that there are parallels between ourselves and agents with no innate linguistic knowledge came when Christiansen selected two of his artificial grammars and trained separate groups of people to use them. The group learning the grammar with the rare word-order had qualitatively similar problems to the neural networks. "This is clearly an important result," he says.

Pinker is not so impressed. "No one has ever doubted that languages are adapted to the human brain," he comments. "Since language wasn't handed down to us by a committee of Martians, how else could it be?" But we still need innate language abilities. "We still need to explain why children learn languages -- real human languages, not simplified artificial ones -- leading to a cycle of evolution over the generations, whereas monkeys don't, even when exposed to the same input." . Kirby agrees. "Ultimately we need to understand why humans are unique in this respect, and why human languages are the way they are," he says. We are beginning to see that satisfactory answers to these questions must take into account the complex interactions between human evolution and linguistic evolution."

To tackle these issues Kirby's team use what's known as an "iterated learning model" in which each new generation of speakers learns by observing and copying the behaviour of the previous one. They have found that the most successful languages to emerge in this simulated world have important similarities to the languages we speak in the real world. Their models also suggest that a major force shaping language evolution is the bottleneck that occurs when infants learn to speak on the basis of the limited input they get from their carers. In other words, the "poverty of the stimulus" isn't necessarily a problem that has to be solved by invoking innate language skills, but might actually explain why language is as it is.

Whereas Christiansen designs complex artificial languages for his simulations, Kirby allows his agents to generate their own. In his version of Chinese whispers they begin with "random" languages, with each agent choosing chance symbols for each meaning it wants to express. The agents talk about an imaginary world inhabited by a small group of people. So, for example, one agent prompted to express the meaning "Mary admires John" might produce the alphabet symbol-string "ldg". Another might use the strings "gj" to say "Mary admires Gavin". A third could come up with "xkq" for "Mary loves John". These utterances form the input for newborn, language-naive agents. To reflect the observed learning capacities of real children, these baby eavesdroppers can occasionally "mind-read" -- intuitively pick up the meanings behind individual symbols -- and also try to infer what linguistic system lies behind the utterances.

In the early stages the language is "holistic", so the whole of each symbol-string ("gj", say) corresponds to the whole of its meaning ("Mary admires Gavin"). But such a language is highly unstable, with pairings between symbols and their meanings being broken and remade. Eventually, as generations of agents die and are replaced by new ones, this unstable holistic language evolves into a so-called "compositional" one, in which individual parts of the symbol-string start to correspond to separate elements of its meaning. So, bits like "tej" and "m" might become consistently linked to the meanings "Mary" and "admires". And after 1000 generations, the agents say things like "gjhftejm" for "Mary admires John"; "gjhftejwp" for "Mary loves John" and "gjqpftejm" for "Mary admires Gavin". Such compositionality is a fundamental feature of human language structure.

Kirby's model mirrors at least one independently developed theory of language evolution. Alison Wray of Cardiff University, editor of the recent book The Transition to Language (Oxford University Press, 2002), proposes that human language began as a holistic communication system of unique sound strings for complete messages, and only later got broken down into words that had to be strung together with grammar. The traditional explanation for this transition is that our ancestors evolved as natural selection favoured individuals who were better communicators. But in Kirby's model speakers don't evolve. All agents are born identical throughout the entire simulation, and an agent's survival is unrelated to its ability to communicate. Despite this, the language still evolves.

"What happens is that at some point in the initial randomness, an apparent regularity shows up," explains Kirby. Parts of the language start to follow general rules, which makes them easier to learn, so they persist for longer. In evolutionary terms, these bits of language are better survivors because they are better adapted to be learned by the agents. Gradually, this process produces more and larger generalisations, until the whole language follows regular rules . By now the language has become very useful to its users: they can learn it from few examples and communicate meanings they never encountered while learning. "The key point," says Kirby, "is that although language turns out to be optimal for communication, this isn't what drives its evolution."

More intriguing still, Kirby's models indicate that language only takes the leap from holistic to compositional and generalisable under certain circumstances. When agents are exposed to every possible meaning in their world, holistic language is stable and doesn't evolve further. But most of Kirby's simulations deliberately expose agents to sparse and chaotic input of language, mimicking the real- world circumstances in which infants learn to speak. His radical conclusion is that language did not develop despite the "poverty of the stimulus", but because of it.

For Christiansen, this also explains the so-called "critical period" in childhood, after which people find it increasingly difficult to learn language. "To reap the fullest adaptive advantage from their language symbiont, humans need to acquire it as early in life as possible," he says. "So languages have evolved to be learnable primarily by children." And this has implications for what languages can and cannot be. "Easily learned linguistic forms will establish themselves early, and thus may pre-empt more complex and potentially more communicative forms," he says. "Language forms not learnable by children will disappear." Even if such forms might be of more use to adult speakers.

In a further counter-intuitive twist, Christiansen argues that children's limited cognitive abilities in areas such as perception and memory may actually help them learn to speak. Recent evidence from both computer simulations and experiments with human adults learning artificial languages support this idea. "Children's perception and memory limitations force them to focus on the basic 'building blocks' for further language learning," says Christiansen. "In contrast, the superior processing abilities of adults prevent them picking up these blocks directly. They have to find them using more complex computations, making language learning more difficult."

Other language experts are taking these ideas seriously. They have particular resonance for proponents of the theory of memes, in which units of culture are seen to evolve in much the same way as genes. Daniel Dennett from Tufts University in Boston points out: "Richard Dawkins and others, including me, have been arguing for some years now that memes are symbionts, and words -- and hence language -- are a prime example of memes." Nevertheless, Dennett is uneasy about extrapolating from computer simulations to the real world. "It is important to say, firmly and clearly, just how abstract, how unlike human agents, these software agents are," he says. Wray agrees that simulations can oversimplify and magnify errors. "It's certainly possible to get a lot of nonsense out if you don't know what you're doing," she says. "Fortunately, Kirby and his team do."

Even if this work doesn't dislodge universal grammar from its central role in language evolution, it adds another dimension to the story. Kirby's team is already working on simulations where both the agents and the language evolve, to see how this complex interaction plays out. And there is no doubt that their approach has a future. "It's definitely the way forward," says Wray. Kirby's colleague, Jim Hurford, agrees. A decade ago, in his book The Language Instinct, Pinker described Hurford as "the world's only computational evolutionary linguist". "There are now several hundreds of us," says Hurford, "and Kirby is easily one of the most prominent."
 
Talking heads
 
Ken Grimes

Why are we the only animals that speak? Some other primates use holistic language, so why has this never evolved into a complex, compositional language like ours? Morten Christiansen believes it helps to see language as a parasite that has evolved to live in the human brain. The question then becomes: what makes this habitat uniquely desirable for language?

Comparative studies reviewed by Christiansen suggest that humans and other primates share certain fundamental cognitive abilities. Non-human apes, for example, can learn fixed sequences such as the strings of sounds that make up words. They can also chop up the continuous sounds of spoken phrases in appropriate ways. But there are also big differences.

Our brains are much better at learning hierarchical structures than those of other animals. "This is crucial for the syntactic processing of language," says Christiansen, because grammar requires the ability to build up a series of phrases into a meaningful sentence. We are also particularly good at recognising and taking an interest in what other people are attending to, a skill known as "joint attention". And we have an aptitude for "mindreading", attributing separate viewpoints and motivations to other individuals. Christiansen suspects that the ability to speak requires a combination of many such skills.

Even so, there's some evidence that the language bug can colonise new territory. Bonobos, most notably Kanzi, have learned to communicate with a lexigram-based artificial language -- a simple compositional system. And Kanzi has tried to communicate with other bonobos, chimps and even a dog, using the lexigrams. "It's at least conceivable that a group of language-trained bonobos could maintain their language ability in the wild, transmitting it both to non-trained peers and to offspring," says Christiansen.

Language Evolution, edited by Morten Christiansen and Simon Kirby, Oxford University Press (2003)

LOAD-DATE: January 21, 2003