Smart Economy

The advantage of ambiguity --why does human language has so many words with multiple meanings?

Cognitive scientists develop a new take on an old problem: why human language has so many words with multiple meanings.

CAMBRIDGE, Mass. — Why did language evolve? While the answer might seem obvious — as a way for individuals to exchange information — linguists and other students of communication have debated this question for years. Many prominent linguists, including MIT’s Noam Chomsky, have argued that language is, in fact, poorly designed for communication. Such a use, they say, is merely a byproduct of a system that probably evolved for other reasons — perhaps for structuring our own private thoughts.

As evidence, these linguists point to the existence of ambiguity: In a system optimized for conveying information between a speaker and a listener, they argue, each word would have just one meaning, eliminating any chance of confusion or misunderstanding. Now, a group of MIT cognitive scientists has turned this idea on its head. In a new theory, they claim that ambiguity actually makes language more efficient, by allowing for the reuse of short, efficient sounds that listeners can easily disambiguate with the help of context.

“Various people have said that ambiguity is a problem for communication,” says Ted Gibson, an MIT professor of cognitive science and senior author of a paper describing the research to appear in the journal Cognition. “But once we understand that context disambiguates, then ambiguity is not a problem — it’s something you can take advantage of, because you can reuse easy [words] in different contexts over and over again.”

Lead author of the paper is Steven Piantadosi PhD ’11; Harry Tily, a postdoc in the Department of Brain and Cognitive Sciences, is another co-author.

What do you ‘mean’?

For a somewhat ironic example of ambiguity, consider the word “mean.” It can mean, of course, to indicate or signify, but it can also refer to an intention or purpose (“I meant to go to the store”); something offensive or nasty; or the mathematical average of a set of numbers. Adding an ‘s’ introduces even more potential definitions: an instrument or method (“a means to an end”), or financial resources (“to live within one’s means”).

But virtually no speaker of English gets confused when he or she hears the word “mean.” That’s because the different senses of the word occur in such different contexts as to allow listeners to infer its meaning nearly automatically.

Given the disambiguating power of context, the researchers hypothesized that languages might harness ambiguity to reuse words — most likely, the easiest words for language processing systems. Building on observation and previous studies, they posited that words with fewer syllables, high frequency and the simplest pronunciations should have the most meanings.

To test this prediction, Piantadosi, Tily and Gibson carried out corpus studies of English, Dutch and German. (In linguistics, a corpus is a large body of samples of language as it is used naturally, which can be used to search for word frequencies or patterns.) By comparing certain properties of words to their numbers of meanings, the researchers confirmed their suspicion that shorter, more frequent words, as well as those that conform to the language’s typical sound patterns, are most likely to be ambiguous — trends that were statistically significant in all three languages.

To understand why ambiguity makes a language more efficient rather than less so, think about the competing desires of the speaker and the listener. The speaker is interested in conveying as much as possible with the fewest possible words, while the listener is aiming to get a complete and specific understanding of what the speaker is trying to say. But as the researchers write, it is “cognitively cheaper” to have the listener infer certain things from the context than to have the speaker spend time on longer and more complicated utterances. The result is a system that skews toward ambiguity, reusing the “easiest” words. Once context is considered, it’s clear that “ambiguity is actually something you would want in the communication system,” Piantadosi says.

Implications for computer science

The researchers say the statistical nature of their paper reflects a trend in the field of linguistics, which is coming to rely more heavily on information theory and quantitative methods.

“The influence of computer science in linguistics right now is very high,” Gibson says, adding that natural language processing (NLP) is a major goal of those operating at the intersection of the two fields.

Piantadosi points out that ambiguity in natural language poses immense challenges for NLP developers. “Ambiguity is only good for us [as humans] because we have these really sophisticated cognitive mechanisms for disambiguating,” he says. “It’s really difficult to work out the details of what those are, or even some sort of approximation that you could get a computer to use.”

But, as Gibson says, computer scientists have long been aware of this problem. The new study provides a better theoretical and evolutionary explanation of why ambiguity exists, but the same message holds: “Basically, if you have any human language in your input or output, you are stuck with needing context to disambiguate,” he says.

Written by: Emily Finn, MIT News Office

Why bats, rats and cats store different amounts of fat

Animals differ in the amount of fat they carry around depending on their species, status and sex. However, the causes of much of this variation have been a mystery. The Bristol study shows that many differences can be understood by considering the strategies animals employ to avoid two causes of death: starvation and being killed by predators.

These causes of death often exert opposite pressures on animals, for example, storing lots of fat helps animals survive periods without food but also slows their running and so makes getting caught by a predator more likely. Animals can be stronger to compensate, but the energetic costs of extra muscle mean that the animal would starve quicker during a food shortage.

Led by Dr Andrew Higginson of Bristol's School of Biological Sciences, the researchers used mathematical models to explore how much muscle and fat animals should have in their body to give themselves the best chance of survival. They showed that an important consideration was how much carrying fat increases the energetic costs of movement. The models revealed that the size of this cost influenced whether larger animals should have more fat than smaller animals, or vice versa.

Dr Higginson said: "Our results explain differences between different families of mammal. For example, larger bats carry proportionally less fat than small bats but larger carnivores carry more fat than small carnivores. Among rodents, it's the medium-sized species that carry around the most fat! These differences agree with the models predictions if you consider the costs of carrying fat for these three groups. Bats fly and so have high costs of carrying extra weight, whilst carnivores spend much of their time resting and so will use less energy than busy scurrying rodents."

The work, published in The American Naturalist, also shows that much of the variation between animals in their amounts of fat and muscle can be explained by differences between the sexes, how much animals have to fight to get food, and the climate in which they live.

The researchers plan to put the theory to the test by looking in more detail at the amounts of fat stored by different animals. If their theory is correct, much of the mystery in how species and sexes differ in their amount of fat will have been solved.

###

 

---