Reclaiming Indigenous Knowledge Systems in the Age of Technological Modernity: A Critical Analysis of Cultural Westernization and Epistemic Erosion in India

This paper critically examines the relationship between technological modernity and the gradual erosion of Indigenous Knowledge Systems (IKS), with specific reference to the Indian context. It argues that contemporary digital infrastructures—while offering unprecedented global connectivity and operational efficiency—simultaneously accelerate epistemic homogenization, digital colonialism, and cultural Westernization. Drawing on decolonial theory, Science and Technology Studies (STS), and recent scholarship on data sovereignty, the study situates the marginalization of IKS within a broader socio-technical framework. Employing a critical-interpretive methodology that triangulates documentary policy analysis with three India-specific case studies—the National Education Policy (NEP) 2020 and the EdTech sector, generative artificial intelligence (AI) and linguistic marginalization, and Adivasi agricultural-data extraction—the paper demonstrates how digital systems restructure cognition, commodify cultural memory, and displace indigenous epistemologies. The analysis identifies four structural mechanisms of erosion—epistemic standardization, algorithmic bias, data dispossession, and cognitive restructuring—which together produce a condition of epistemic dependency in which interpretive authority shifts from communities to privately owned platforms. Empirical indicators are integrated throughout: India recorded 19,569 raw mother-tongue returns in the 2011 Census yet officially recognizes only 121 languages, while English constitutes roughly 46% of the most recent Common Crawl corpus and over 90% of the training data underpinning large language models. The paper advances two conceptual models—a comparative epistemological paradigm and an epistemic erosion–revitalization framework—and argues for a paradigm of technological sovereignty that critically engages digital advancement while safeguarding pluralistic knowledge ecosystems. The findings carry implications for education policy, AI governance, and indigenous data rights, suggesting that hybrid pedagogies, collective-consent data protocols, and decolonial AI design can convert digital infrastructure from a vector of erosion into an instrument of epistemic revitalization.

ndigenous knowledge systems; digital colonialism; epistemic erosion; generative AI; NEP 2020

1. Agrawal, A. (1995). Dismantling the divide between indigenous and scientific knowledge. Development and Change, 26(3), 413–439. https://doi.org/10.1111/j.1467-7660.1995.tb00544.x [Google Scholar] [Crossref]

2. Carr, N. (2010). The shallows: What the Internet is doing to our brains. W. W. Norton. [Google Scholar] [Crossref]

3. Census of India. (2013). Primary census abstract and language data, Census of India 2011. Office of the Registrar General & Census Commissioner, Ministry of Home Affairs, Government of India. https://censusindia.gov.in [Google Scholar] [Crossref]

4. Centre for Economic Data and Analysis. (2025). One nation, many disconnects: Mapping India's home internet gaps. Ashoka University. https://ceda.ashoka.edu.in [Google Scholar] [Crossref]

5. Couldry, N., & Mejias, U. A. (2020). The costs of connection: How data is colonizing human life and appropriating it for capitalism. Stanford University Press. [Google Scholar] [Crossref]

6. Ellul, J. (1964). The technological society (J. Wilkinson, Trans.). Vintage Books. (Original work published 1954) [Google Scholar] [Crossref]

7. Etxaniz, J., Sainz, O., Perez, N., Aldabe, I., Rigau, G., Agirre, E., Ormazabal, A., Artetxe, M., & Soroa, A. (2024). Latxa: An open language model and evaluation suite for Basque. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (pp. 14952–14972). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.acl-long.799 [Google Scholar] [Crossref]

8. GlobalData. (2024). India EdTech market summary, competitive analysis and forecast to 2029. GlobalData Plc. https://www.globaldata.com [Google Scholar] [Crossref]

9. Heidegger, M. (1977). The question concerning technology and other essays (W. Lovitt, Trans.). Harper & Row. [Google Scholar] [Crossref]

10. Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Choudhury, M. (2020). The state and fate of linguistic diversity and inclusion in the NLP world. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 6282–6293). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.560 [Google Scholar] [Crossref]

11. Kemp, S. (2024). Digital 2024: India. DataReportal. https://datareportal.com/reports/digital-2024-india [Google Scholar] [Crossref]

12. Lakshmi, S. (2025). Rebranding empire in the age of generative AI. Frontiers in Communication, 10, Article 1604361. https://doi.org/10.3389/fcomm.2025.1604361 [Google Scholar] [Crossref]

13. Ministry of Education, Government of India. (2020). National Education Policy 2020. https://www.education.gov.in/sites/upload_files/mhrd/files/NEP_Final_English_0.pdf [Google Scholar] [Crossref]

14. Ministry of Tribal Affairs, Government of India. (2013). Statistical profile of Scheduled Tribes in India 2013. https://tribal.nic.in [Google Scholar] [Crossref]

15. Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press. [Google Scholar] [Crossref]

16. Ong, W. J. (1982). Orality and literacy: The technologizing of the word. Routledge. [Google Scholar] [Crossref]

17. Postman, N. (1992). Technopoly: The surrender of culture to technology. Vintage Books. [Google Scholar] [Crossref]

18. Qadri, M., Gillespie, T., & Peters, J. (2024). Digital marginalisation, AI bias, and cultural erasure in South Asia. Journal of Underrepresented & Minority Progress. https://ojed.org/jump [Google Scholar] [Crossref]

19. RAYSolute. (2026). Indian EdTech market 2026: BYJU'S collapse, Physics Wallah's rise, and the 2035 forecast [Industry report]. RAYSolute Consultants. https://www.raysolute.com/indian-edtech-analysis-2026.html [Google Scholar] [Crossref]

20. Santos, B. de S. (2014). Epistemologies of the South: Justice against epistemicide. Routledge. [Google Scholar] [Crossref]

21. Suhaiu, S. (2025, September 3). Digital colonialism: How Big Tech marginalizes indigenous rights. Kautilya Society, NUSRL Blog. https://kautilyasocietynusrl.in/2025/09/03/digital-colonialism-how-big-techs-marginalize-indigenous-rights/ [Google Scholar] [Crossref]

22. The India Forum. (2021, December 19). What the census obscures about India's linguistic diversity. https://www.theindiaforum.in/article/what-census-obscures [Google Scholar] [Crossref]

23. Tilde.ai. (2025, November 27). The LLM data dilemma: Why data quality matters for multilingual models. https://tilde.ai/blog/the-llm-data-dilemma/ [Google Scholar] [Crossref]

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