[This is a cool paper about how language affects how people remember colors!](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0158725) You would expect that the design of the eye and its colorspace to be human-universal (_modulo_ [colorblindness](https://en.wikipedia.org/wiki/Color_blindness) and [maybe some women with](https://en.wikipedia.org/wiki/Tetrachromacy#Humans) [both](https://en.wikipedia.org/wiki/OPN1MW) [kinds](https://en.wikipedia.org/wiki/OPN1MW2) of green opsin gene), but not all languages have the same set of color words. There are some regularities: [all languages have words for light and dark; if they have a third color word, then it's _red_; if there's a fourth, it'll cover green or yellow](https://en.wikipedia.org/wiki/Basic_Color_Terms)—but the details differ, as different languages [stumbled onto different conventions](/2020/Jan/book-review-the-origins-of-unfairness/). Do the color category conventions in one's native tongue affect how people think about color, in accordance with the famous [Sapir–Whorf hypothesis](https://en.wikipedia.org/wiki/Linguistic_relativity)? Maybe—but if so, how??
-Our authors discuss an experiment where people are briefly shown a color, and then try to match it on a color wheel after a short delay.
+Our authors discuss an experiment where people are briefly shown a color, and then try to match it on a color wheel, either at the same time, or after a short delay. People aren't just not-perfect at this, but—particularly in the delayed condition—show a non-monotonic pattern of directional bias: colors just on the "blue" side of the blue–green boundary are remembered as being relatively more bluish than they really were, but _very similar_ colors on the "green" side of the boundary are remembered as being relatively more greenish than they really were.
+Our authors propose to explain this with a model in which a stimulus is encoded in the brain as both a fine-grained representation of what was actually seen (this-and-such color perception, with some noise/measurement-error), and as a category ("green"). Then reconstruction of the stimulus from the both the fine-grained representation and the category, will be biased towards the center of the category, with more bias when the fine-grained representation is more uncertain (as in the delayed condition).
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+The model gains further support from a similar "two-alternative forced choice" experiment, where people try to tell the difference between the original color and a distractor, rather than picking from a color wheel.
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+You know where I'm going with this! Why do we care about the further question of what "gender" someone is, if we already have fine-grained perceptions of how the person looks and behaves?
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+This model can also explain results
Bayesian reasoning!
+/2020/Apr/book-review-human-diversity/#everyday-base-rates
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[The answer is always Bayesian reasoning.](https://www.lesswrong.com/posts/QrhAeKBkm2WsdRYao/searching-for-bayes-structure)
-You know where I'm going with this.
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projects / Ultimately_Untrue_Thought.git / blobdiff