Computer Science

What artificial intelligence might teach us about the origin of human language

A. Kilpatrick

Delve into an intriguing study by Alexander Kilpatrick that uncovers how AI research leverages sound symbolism. Discover how machine learning algorithms may reflect our instinctual caution by overpredicting perceived threats while analyzing Pokémon names across languages. This fascinating work examines the intersection of technology and human psychology.

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Playback language: English

Index

Abstract

This study explores a pattern emerging from AI research combining artificial intelligence with sound symbolism. Supervised machine learning algorithms, efficient learners of sound symbolism, show a bias towards overpredicting categories perceived as threatening. The study uses XGBoost models on Pokémon names across different languages to test if this bias reflects an adaptation for cautious behavior, as suggested by error management theory.

Publisher

Not specified; study has not undergone peer review.

Published On

Jan 01, 2023

Authors

Alexander Kilpatrick

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