Harnessing Artificial Intelligence through Indigenous Ways of Knowing in Education

Abstract

Indigenous way of knowing represents holistic, relational, place-based knowledge and an ecologically sound knowledge system that has sustained indigenous communities from generation to generation. However, our modern education system is primarily shaped by Western epistemologies, which have historically marginalized these core knowledge traditions and customs, leading to epistemic injustice and cultural erosion. Nowadays, Artificial Intelligence (AI) has become very crucial and inevitable in the education process. With the rapid development of AI in Education, it has created many opportunities that compel us to reimagine and reconstruct our pedagogical framework in a culturally responsive, inclusive framework. Without technological knowledge, we are unable to adapt to this change, and without change, we lag, deprived and marginal in the technocrats’ eyes. As we know, technology not only helps to develop our IT industry but is equally vital in the educational sector, mainly in the teaching-learning process. Therefore, it is now also a major challenge to implement Industry 4.0 and 5.0 in this educational setup. Technology not only helps us adapt to change but also enables us to develop our entire educational process with great effort and to address the changes and challenges in the educational paradigm. Through the utilisation of technology, education became more viable, affordable, and available in all contexts. In this context, AI is proven to be a game-changer, making it easier to implement ideas, facts, and knowledge in real-world contexts. This study explores the potential of Artificial Intelligence as a pedagogical tool for integrating, and harnessing, Indigenous ways of knowing into the formal education system, with special focus on the tribal context. This paper also contributes to the growing discourse on sustainability, creature-centric education, and environmental justice education in the digital age.

Introduction

The rapid development of digital technologies and Artificial Intelligence (AI) is transforming modern education by enabling personalized learning, automated assessment, and learner-centered teaching. AI can act as a mentor that supports students with adaptive learning and feedback. At the same time, Indigenous Ways of Knowing (IWOK)—holistic knowledge systems based on oral traditions, community wisdom, ecological relationships, and lived experiences—remain largely marginalized in formal education, particularly in India. Although NEP 2020 emphasizes integrating indigenous knowledge into curricula, implementation at the grassroots level remains difficult.

The study argues that AI can help bridge Indigenous knowledge and formal education systems. AI tools can analyze learning patterns, support digital learning environments, and potentially preserve and integrate Indigenous knowledge if designed ethically and respectfully. Indigenous Knowledge Systems (IKS) include ecological wisdom, traditional medicine, sustainable agriculture, and cultural practices preserved by tribal communities such as the Santhals, Gonds, Bhils, and others. However, these systems are often undervalued in modern curricula.

The relationship between AI and Indigenous knowledge is complex but promising. AI technologies—such as speech recognition, natural language processing, and multimedia archiving—can preserve endangered languages, oral traditions, and cultural knowledge. Integrating Traditional Ecological Knowledge with AI analytics can also support sustainability, climate resilience, and biodiversity conservation. For this integration to succeed, AI must respect Indigenous data sovereignty, ethics, and community participation.

The study proposes a 3P framework—Preservation, Promotion, and Protection of Indigenous Knowledge through AI. AI can preserve knowledge through digital documentation, promote it by incorporating culturally relevant content into educational platforms, and protect it through ethical safeguards and controlled access.

The research uses a qualitative methodology, analyzing secondary data from academic studies, policy documents, and ethnographic research. Findings highlight that Indigenous knowledge is contextual, relational, community-based, experiential, and transmitted through oral traditions, emphasizing harmony with nature rather than domination over it.

Overall, the study concludes that ethically designed AI systems can help integrate Indigenous knowledge into formal education, promoting cultural inclusion, ecological awareness, and equitable learning while preserving the cultural heritage of Indigenous communities.

Conclusion

Artificial Intelligence, often viewed as a symbol of technological dominance, also serves as a tool for epistemic inclusion when guided by Indigenous values and ethical frameworks. This paper has argued that Artificial Intelligence can help integrate Indigenous Ways of Knowing into formal education by preserving and promoting oral traditions to foster place-based learning and develop creature-centric wellbeing. Artificial Intelligence does not replace Indigenous pedagogies but strengthens them when communities remain at the centre of knowledge production. Tribal teaching is an essential component of the knowledge framework and it\'s essential for the inclusive development of the nation. The tribal community in Purulia district, West Bengal, has its own knowledge framework. Now it\'s time to codify and document to preserve, protect, and promote through Artificial Intelligence. Suppose that codifying the Tribal community\'s indigenous cultural practices and documenting them using Artificial Intelligence (AI) will help build a digital database for future reference and protect them from erosion and the loss of indigenous knowledge. Documentation of this endeavour, indigenous knowledge, helps give recognition to indigenous people and their knowledge systems. Indigenous knowledge has many aspects that give alternative ways of living and lifestyle, and also help in adapting to new knowledge creation through human learning.

References

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Copyright © 2026 Manas Khan, Dr. Laxmiram Gope. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.