When computers learn human languages, they also learn human prejudices

Implicit biases are a well-documented and pernicious feature of human languages. These associations, which we’re often not even aware of, can be relatively harmless: We associate flowers with positive words and insects with negative ones, for example. But they can also encode human prejudices, such as when we associate positive words with European American names and negative words with African American ones. New research from computer scientists at Princeton suggests that computers learning human languages will also inevitably learn those human biases. In a draft paper, researchers describe how they used a common language-learning algorithm to infer associations between English words. The results demonstrated biases similar to those found in traditional psychology research and across a variety of topics. In fact, the authors were able to replicate every implicit bias…


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