Miller's Monkey Updated: Communicative Efficiency and the Statistics of Words in Natural Language

Resumen

Is language designed for communicative and functional efficiency? G. K. Zipf provided a famous argument in the affirmative: shorter words, which are easier to use, tend to be more frequent, apparently due to the pressure to minimize speaker effort. However, G. A. Miller showed that even a monkey randomly typing at a keyboard, and intermittently striking the space bar, would generate "words" with similar statistical properties. Recent quantitative analyses of human language lexicons (Piantadosi, Tily, & Gibson, 2012) have revived Zipf's functionalist hypothesis. Ambiguous words tend to be short, frequent, and easier to articulate in language production, which is interpreted as evidence for communicative efficiency as the context of language use often provides cues to overcome lexical ambiguity. In this study, we update Miller's monkey thought experiment to incorporate empirically motivated phonological and semantic constraints on the creation of words. We claim that the appearance of communicative efficiency is a spandrel (Gould & Lewontin, 1979), as lexicons formed without the context of language use or reference to communication or efficiency exhibit comparable statistical properties. Furthermore, the updated monkey model provides a good fit for the growth trajectory of English as recorded in the Oxford English Dictionary. Focusing on the history of English words since 1900, we show that lexicons resulting from the monkey model provide a better embodiment of communicative efficiency than the actual lexicon of English. We conclude by arguing for the need to go beyond correlational statistics and to seek direct evidence for the mechanisms that underlie principles of language design.

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Cómo citar (APA 7)

Caplan, S., Kodner, J., & Yang, C. (2020). Miller's Monkey Updated: Communicative Efficiency and the Statistics of Words in Natural Language. https://doi.org/10.1016/j.cognition.2020.104466