Then you split your set in half and guess again. I say yes, because my chip is in fact one of those. You can choose a whole set of color chips that you think corresponds to my color “blue.” Maybe you pick a set of 12 color chips corresponding to all those in columns M, N and O. Now in this thought experiment, you as a listener are trying to guess which physical color I meant. Maybe the word I choose is “blue.” If I had picked A3, I would have never said “blue.” And if I had picked M3, maybe I would have said “blue,” maybe “green” or something else. I choose a word to label the color that I picked. Suppose the color I select at random is N4. To evaluate the communication-based idea, we need to think of color-naming in simple communication terms, which can be formalized by information theory. Participants had to communicate one of the 80 color chip choices from across the color grid. The speaker’s task is to simply label the color with a word (“red,” “blue” and so on). Each pair of neighboring colors is the same distance apart in terms of how different they appear. In our study, we used 80 color chips, selected from Munsell colors to be evenly spaced across the color grid. Consider the task of simply naming a color chip from some set of colors. Our research groups therefore explored a completely different idea: Perhaps color words are developed for efficient communication. The visual systems of people across cultures are the same: in this model, industrialization should make no difference on color categorization, which was clearly not the case. What’s more, this nativist theory doesn’t address why industrialization, which introduced reliable, stable and standardized colors on a large scale, causes more color words to be introduced. Their original generalization isn’t as clear in this larger data set: there are many exceptions, which Kay and his colleagues have tried to explain in a more complicated vision-based theory. While this approach seemed promising, there are several problems with this innate vision-based theory.īerlin, Kay and their colleagues went on to gather a much larger data set, from 110 nonindustrialized languages. So black and white are the most salient, then red, and so on. They suggested that cultures start by naming the most salient colors, bringing in new terms one at a time, in order. They observed some commonalities among sets of color terms across languages: If a language had only two terms, they were always black and white if there was a third, it was red the fourth and fifth were always green and yellow (in either order) the sixth was blue the seventh was brown and so on.īased on this order, Berlin and Kay argued that certain colors were more salient. In their early work in the 1960s, they gathered color-naming data from 20 languages. The most widely accepted explanation for the differences goes back to two linguists, Brent Berlin and Paul Kay. Is it about which colors stand out the most? The goal of our project was to understand why cultures vary so much in their color word usage. So while English has 11 words that everyone knows, the Papua-New Guinean language Berinmo has only five, and the Bolivian Amazonian language Tsimane’ has only three words that everyone knows, corresponding to black, white and red. Nonindustrialized cultures typically have far fewer words for colors than industrialized cultures. Interestingly, the ways that languages categorize color vary widely.
But this is still a tiny fraction of the colors that we can distinguish. Maybe if you’re an artist or an interior designer, you know specific meanings for as many as 50 or 100 different words for colors – like turquoise, amber, indigo or taupe. In an industrialized culture, most people get by with 11 color words: black, white, red, green, yellow, blue, brown, orange, pink, purple and gray. But human language categorizes these into a small set of words. People with standard vision can see millions of distinct colors.