New York:

Edward Gibson

Edward (Ted) Gibson received a B. Sc. from Queens University (1985), an M. Phil. from Cambridge (1986) and a PhD (computational linguistics, 1991) from Carnegie Mellon University.  He joined the faculty at MIT in the Department of Brain and Cognitive Sciences in 1993, where he has been a full professor since 2004.  He was elected a fellow of the Cognitive Science Society in 2017. In a past life, he competed for Canada at the 1981-1985 World Championships and the 1984 Olympics (7th), and for Cambridge in 1986 in the Oxford-Cambridge boat race (won by 7 lengths).

Gibson’s research examines how language is processed, and how language processing constraints constrain language structure (words and sentences). One constraint is that language is processed over a noisy-channel, leading to systematic misunderstandings in particular contexts (Gibson et al. 2013, PNAS).  This approach may lead to a better understanding of language deficits such as aphasia (Gibson et al. 2015, Aphasiology). In recent projects exploring language universals (Gibson et al., 2019, Trends in Cognitive Science), Gibson’s group has shown that all the world’s languages minimize syntactic dependency lengths (Futrell, Mahowald & Gibson, 2015, PNAS) and that information-theory can explain how different cultures divide the visual color space into different sets of color terms (Gibson et al., 2017, PNAS).


Information processing and cross-linguistic universals

Finding explanations for the observed variation in human languages is the primary goal of linguistics, and promises to shed light on the nature of human cognition. One particularly attractive set of explanations is functional in nature, holding that language universals are grounded in the known properties of human information processing. The idea is that lexicons and grammars of languages have evolved so that language users can communicate using words and sentences that are relatively easy to produce and comprehend. 

In this talk, I summarize results from explorations in two linguistic domains, from an information-processing point of view.  First, in the lexical domain, I show that word lengths are optimized on average according to predictability in context, as would be expected under an information theoretic analysis. I then apply a simple information theory analysis to the language for color.  The number of color terms varies drastically across languages. Yet despite these differences, certain terms (e.g., red) are prevalent, which has been attributed to perceptual salience.

Our work provides evidence for an alternative hypothesis: The use of color terms depends on communicative needs.  Across languages, from the hunter-gatherer Tsimane’ people of the Amazon to students in Boston, warm colors are communicated more efficiently than cool colors. This cross-linguistic pattern reflects the color statistics of the world: Objects (what we talk about) are typically warm-colored, and backgrounds are cool-colored. Communicative needs also explain why the number of color terms varies across languages: Cultures vary in how useful color is. Industrialization, which creates objects distinguishable solely based on color, increases color usefulness.

Finally, in the realm of syntax, I show that all the world’s languages that we can currently analyze minimize syntactic dependency lengths to some degree, as would be expected under information processing considerations.



Piantadosi, S.T., Tily, H., Gibson, E. (2012). The communicative function of ambiguity in language. Cognition 122: 280-291.

Piantadosi, S.T., Tily, H., Gibson, E. (2011). Word lengths are optimized for efficient communication.Proceedings of the National Academy of Sciences 108(9): 3526-3529.

Gibson, E., Futrell, R., Jara-Ettinger, J., Mahowald, K., Bergen, L., Ratnasingam, S., Gibson, M., Piantadosi, S.T., Conway, B.R. (2017). Color naming across languages reflects color use. Proceedings of the National Academy of Sciences” 114(40): 10785-10790.

Futrell, R., Mahowald, K., Gibson, E. (2015). Large-scale evidence of dependency length minimization in 37 languages. Proceedings of the National Academy of Sciences 112(33): 10336-10341. doi: 10.1073/pnas.1502134112.

Gibson, E., Futrell, R., Piantadosi, S.T., Dautriche, I., Mahowald, K., Bergen, L., Levy, R. (2019). How Efficiency Shapes Human Language. Trends in Cognitive Science.

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