In the age of Al, human language diversity is more vital than ever

We are racing to teach machines to understand human language. But what if the data we're feeding them represents only a tiny fraction of human expression? Our AI future, often portrayed as a pinnacle of intelligence, risks being culturally impoverished and fundamentally biased if we don't act now. The fight to preserve the world's endangered languages is not a nostalgic look backward; it is an urgent, forward-looking necessity to build a truly intelligent and equitable technological world.

- ANNA MAE YU LAMENTILLO

The core problem is a severe data famine. Large language models and AI systems are trained on terabytes of text and speech scraped from the internet. This content is overwhelmingly in English, Mandarin, Spanish, and a handful of other dominant languages. This creates a dangerous feedback loop: AI is built on a narrow linguistic foundation, becomes proficient only in those tongues, and then amplifies their dominance across the digital landscape. The result is a form of technological colonialism. Al that cannot understand the nuanced grammar of an Indigenous language or the cultural concepts embedded within it will inevitably fail-and even harm-the communities that speak it. Imagine a healthcare chatbot missing a vital symptom description because it doesn't recognize the local dialect, or a legal AI misinterpreting a testimony given in a minority