Rethinking Indic AI from a Lens of Cultural Heritage Preservation

Forum topic · 小凯 · 2026-07-09

Summary

This paper (arXiv:2507.06822, July 2025) by Aparna Madva, Sharath Srivatsa, and Srinath Srinivasa examines how AI impacts the linguistic and cultural foundations of the Indian subcontinent. Framing AI as a 'double-edged sword'—capable of enabling access and inclusion while risking homogenization of worldviews—the authors characterize the distinctive nature of Indian linguistics and its ties to cultural practices. They provide a longitudinal survey of Indic NLP, covering historical milestones, methodological shifts, and resource-creation efforts, and analyze structural and sociolinguistic features such as rich morphology, complex scripts, diglossia, and extensive dialectal variation that pose unique challenges for foundation models. The paper then assesses the growing role of Indic foundation models in closing resource and representation gaps, and proposes a new research direction called 'Culture Sensing,' which reimagines AI through hermeneutic reasoning to ensure equitable performance across low-resource languages and culturally meaningful outputs.

Overview

Field: NLP Authors: Aparna Madva, Sharath Srivatsa, Srinath Srinivasa Published: 2025-07-09 arXiv: 2507.06822

Abstract (translated)

This paper characterizes this problem by addressing the extensive characteristic nature of Indian linguistics and the way it closely connects to cultural practices and worldview. The authors perform a longitudinal survey of how Natural Language Processing (NLP) techniques have evolved in this space, tracing the historical development of Indic NLP across key milestones, methodological shifts, and resource-creation efforts.

The paper further examines the structural and sociolinguistic features of Indian languages—rich morphology, complex scripts and grammatical rules, diglossia, and large numbers of dialectal variants—and explains how these pose unique challenges for building AI foundation models. It then discusses the growing role of Indic foundation models and analyzes how they address these long-standing resource and representation gaps.

Finally, the authors propose a research direction called Culture Sensing, which reimagines AI based on hermeneutic reasoning. Culture Sensing aims to address open questions such as ensuring equitable performance across low-resource languages and producing culturally meaningful outputs. By integrating past work, current technologies, and emerging trends, the paper outlines research directions that can guide the next phase of Indic NLP and contribute to building more robust and inclusive Indian foundation models.

Original Abstract

As Artificial Intelligence (AI) makes inroads into different parts of the Indian subcontinent, there is significant interest in studying how AI impacts the linguistic and cultural foundations of this civilization. AI is seen as a 'double-edged sword' where on the one hand, it can enable access and inclusion for a large population, on the other, it can homogenize worldviews and exclude underrepresented languages and worldviews. In this paper, we try to characterize this problem by addressing the extensive characteristic nature of Indian linguistics and the way they closely connect to cultural practices and worldview. We then perform a longitudinal survey of how Natural Language Processing (NLP) techniques have evolved in this space, tracing the historical development of Indic NLP, covering ...

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