ILN Journal: Indian Literary Narratives

Articles

Vol. 3 No. S2 (2026): ILN Journal: Indian Literary Narratives

Lost in Translation, Lost in Nation: AI-Induced Linguistic Homogenisation as a Threat to Rastravadah

Submitted
16 July 2026
Published
2026-10-09

Abstract

In Indian philosophy, Rastravadah is not a single, unified identity but a collection of many identities. This idea depends on the coexistence of India’s many languages, dialects, and ways of speaking. This paper examines a subtle threat to that foundation: how AI can make language more uniform. Large language models are mostly trained on widely used languages and tend to prefer the most standard forms. As a result, they often smooth out regional expressions, dialects, and cultural details in translation, writing, and daily communication. More people are using these tools to write or translate in Tamil, Malayalam, Hindi, and other Indian languages. Over time, their language starts to sound more average and less unique. This slow change weakens the special qualities that have shaped India’s diverse national identity.

This article argues that this threat to Rastravadah comes from the tools we use every day, not from official policies. First, it explains how Indian nationhood is built on linguistic diversity. Next, it examines how AI can make language more uniform, focusing on training data and patterns in AI output. Finally, it discusses what this means for teaching and language policy, and suggests solutions like developing regional language models and teaching critical AI skills in language classes. The paper brings together ideas from philosophy, nationhood, and AI to discuss India’s linguistic and cultural diversity.

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