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Indigenous Knowledge Systems and AI

Deepak GuptaInstitute of Technology and Management, Gwalior, IndiaErgashev Nuriddin GayratovichDepartment of Information Systems and Technologies, Karshi State Technical University. Karshi, UzbekistanShaxnoza AkishovaDepartment of Specialized Social-Humanities and Exact Sciences, Tashken State University of Economy, Tashkent, UzbekistanIroda RasulovaDepartment of Social Sciences, Shahrisabz State Pedagogical Institute, Shahrisabz, UzbekistanAbduvali SottarovDepartment of Information Technology and Exact Sciences, Termez University of Economics and Service, Termez, UzbekistanRajabov NazirjonDepartment of International Scientific Journals and Ratings, Alfraganus University, Tashkent, Uzbekistan

2026

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ABI

Annotatsiya

Artificial intelligence (AI) systems embedded in educational technology increasingly reflect and amplify epistemological inequities rooted in colonial knowledge hierarchies. This chapter examines the structural tensions between dominant Western-centric AI paradigms and Indigenous Knowledge Systems (IKS), arguing that decolonizing AI in curriculum and instructional design requires more than technical adjustments to training datasets. Drawing on decolonial theory, epistemic justice frameworks, and the CARE Principles for Indigenous Data Governance, the chapter proposes an integrative conceptual model that positions IKS not as supplementary content but as epistemological foundations capable of reshaping how AI encodes, processes, and generates knowledge.

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Identifikatorlar

DOI: 10.4018/979-8-3373-7837-4.ch008

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