Rethinking Indic AI from a Lens of Cultural Heritage Preservation (arXiv 2507.06822)

Forum topic · 小凯 · 2026-07-09

Summary

This paper, authored by Aparna Madva, Sharath Srivatsa, and Srinath Srinivasa (arXiv:2507.06822, July 2025), examines how Artificial Intelligence impacts the linguistic and cultural foundations of the Indian subcontinent. The authors frame AI as a double-edged sword: it can expand access and inclusion for a large population, yet it may also homogenize worldviews and exclude underrepresented languages. The paper characterizes the distinctive nature of Indian linguistics and its deep ties to cultural practices, then presents a longitudinal survey of Indic NLP, tracing historical development, key milestones, methodological shifts, and resource creation efforts. It analyzes structural and sociolinguistic features of Indian languages—including rich morphology, complex scripts and grammatical rules, diglossia, and extensive dialectal variation—and explains the unique challenges these pose for building foundation models. The authors also discuss the growing role of Indic foundation models in closing long-standing resource and representation gaps. Finally, they propose 'Culture Sensing,' a research direction that reimagines AI through hermeneutic reasoning, aiming to ensure equitable performance across low-resource languages and culturally meaningful outputs, and outline a roadmap for more robust and inclusive Indic foundation models.

Rethinking Indic AI from a Lens of Cultural Heritage Preservation

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

Overview

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' — it can enable access and inclusion for a large population, but it can also homogenize worldviews and exclude underrepresented languages and worldviews.

Key contributions

Problem characterization: Describes the extensive characteristic nature of Indian linguistics and how it closely connects to cultural practices and worldview.
Longitudinal survey of Indic NLP: Traces the historical development of NLP in the Indic context, covering key milestones, methodological shifts, and resource creation efforts.
Linguistic challenges: Examines structural and sociolinguistic features of Indian languages — rich morphology, complex scripts and grammatical rules, diglossia, and large dialectal variation — and explains how these create unique challenges for building AI foundation models.
Indic foundation models: Discusses the growing role of Indic foundation models and analyzes how they address long-standing resource and representation gaps.
Culture Sensing: Proposes a new research direction based on hermeneutic reasoning that reimagines AI, targeting open problems such as 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 developing more robust and inclusive Indic foundation models.

Original abstract (excerpt)

> 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 ...

---

Links: arXiv:2507.06822