AI models that promised to dissolve language barriers instead helped expose a widening digital language divide in 2024 — a gap where mainstream systems perform brilliantly in a handful of dominant tongues while delivering vague, incorrect, or simply absent support for the world’s many minority and indigenous languages. This pattern, documented in recent reporting and regional initiatives, is not a transient bug: it is the product of training choices, dataset imbalances, and institutional...