AI Speaks English—But It’s Not the One Most of the World Uses

A growing body of research warns that today’s AI systems—especially the ones generating your news summaries, essays, and chatbot replies—are trained almost exclusively on one narrow slice of the English language.

According to the University of Western Australia, over 90% of generative AI training data comes from English, but not the global kind spoken by billions. Instead, it’s a hyper-standardized, Western, online-centric dialect that ignores regional variation, non-Western contexts, and indigenous languages.

The result? Bias, exclusion, and serious blind spots.

AI built on this linguistic monoculture may fail to understand non-Western phrasing, mistranslate cultural context, or produce responses that feel alien to most of the global population—even those who speak English natively in vastly different ways.

“This raises urgent equity issues,” researchers say. “If your version of English isn’t represented in the data, the AI won’t represent you either.”

In a world sprinting toward AI-powered everything, this finding is a wake-up call: language isn’t just code—it’s identity. And most of the world is being left out.

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