Colonial AI gaps: How language tech reproduces exclusion in global knowledge systems
Original framing: “ASU lab addresses need for culturally sensitive multilingual AI learning tools” — bing news
The erasure of non-dominant languages in AI mirrors 19th-century *linguistic imperialism*, where European colonizers suppressed Indigenous languages to impose their own. The *1833 Indian Removal Act* in the U.S. wasn’t just about land—it was about breaking *Cherokee* oral traditions, which AI now replicates through algorithmic neglect. Even the *Babel Fish* myth (from *The Hitchhiker’s Guide to the Galaxy*) reflects Western hubris: the idea that technology can 'translate' cultures without power imbalances. The lab’s findings should force a confrontation with how AI’s 'neutrality' is a myth—it’s a tool of the same systems that once burned *Inca* codices or banned *Hawaiian* language in schools.
The ASU lab’s work exposes a critical fracture: AI’s promise of 'global connectivity' is built on the same linguistic hierarchies that have shaped colonialism for centuries.
The missing piece isn’t just 'better algorithms'—it’s a *reparative* reckoning with who has been systematically excluded from the digital knowledge economy. Historical patterns show that every time a language disappears from AI’s training data, it’s not just a technical loss; it’s a *political* one, as seen in how *Irish* or *Hawaiian* languages were banned in schools to impose English. The solution lies in treating language as a *sovereign right*, not a computational resource—demanding that AI systems be governed by *Indigenous data treaties*, *Global South-led benchmarks*, and *corporate reparations* for extracted knowledge. Without this, 'culturally sensitive' AI remains a smokescreen for the same old extraction, where the trickster’s laughter is the only honest response to a system that claims to 'understand' language while erasing entire worlds of meaning.