Diversity in AI is not your problem, it's hers

I came to a shocking conclusion while writing about diversity for my book on machine learning: diversity in Artificial Intelligence is not your problem, it's hers. I mean, of course, that the problem is with the English pronoun "hers". There is a bias against "hers" in most major AI systems today, and the source of the bias is the perfect metaphor for bias in AI more broadly. Like you might remember from high school, "hers" is a pronoun. Each word in a sentence belongs to one of a small number of categories: nouns, pronouns, adjectives, verbs, adverbs, etc. One common building block in many AI applications is to identify the right category in raw text. Today, "hers" is not recognized as a pronoun by the most widely used technologies for Natural Language Processing (NLP), including (alphabetically) Amazon Comprehend, Google Natural Language API, and the Stanford Parser. The video shows that in the sentence "the car is hers", Amazon and Google classify "hers" as a noun and the Stanford parser classifies "hers" as an adjective. They don't make the same mistake with the sentence "the car is his", correctly identifying "his" as a pronoun.