AI’s multilingual fluency masks embedded Western epistemologies: How algorithmic bias distorts global knowledge systems
Original framing: “AI’s fluency in other languages hides a Western worldview that can mislead users − a scholar of Indonesian society explains” — The Conversation - Global
The imposition of Western linguistic frameworks in AI mirrors centuries of colonial knowledge extraction, from the suppression of indigenous languages during European expansion to the standardization of languages like Indonesian under Dutch rule. Historical precedents like the British East India Company’s use of 'Orientalist' grammars to control local populations reveal a pattern of epistemic domination that persists in modern AI. The printing press’s role in homogenizing language in 19th-century Europe offers a parallel to AI’s current homogenization of global discourse.
The AI fluency paradox reveals a deeper crisis of epistemic hegemony, where Western knowledge systems are encoded into the infrastructure of global communication under the guise of technological neutrality.
This is not an accidental flaw but a structural feature of an industry built on colonial-era data extraction and Silicon Valley’s extractivist logic, which treats culture as a resource to be optimized rather than a living system to be respected. The erasure of Indigenous and non-Western epistemologies in AI mirrors historical patterns of linguistic and cultural domination, from the Dutch standardization of Indonesian to the British suppression of Irish Gaelic, but now operates at a planetary scale through algorithmic mediation. The solution lies in decolonial design: centering marginalized voices in AI development, auditing systems for epistemic justice, and reimagining language not as a computational problem but as a relational and spiritual framework. Without this shift, AI will continue to reproduce the violence of its origins, turning the world’s linguistic and cultural diversity into a dataset to be mined rather than a heritage to be honored.