Neetu Chettri
Volume-XIV, Issue-IV, JULY 2026
Volume-XIV, Issue-IV, July 2026 | ||
Received: 10.07. 2026 | Accepted: 20.07.2026 | |||
Published Online: 31.07.2026 | Page No: | |||
DOI: 10.64031/pratidhwanitheecho.vol.14.issue.04W. | ||||
Generative
Artificial Intelligence and Educational Equity in Indian Higher Education
Neetu
Chettri, Assistant Professor, Acharya Brojendra Nath Seal College, West
Bengal, India | |
Generative artificial intelligence will not advance
educational equity in Indian higher education unless the conditions surrounding
its use change in fundamental ways. That is the central claim of this article.
A well-resourced university in Bangalore and an under-funded college in rural
Chhattisgarh may both have access to the same AI tools, but their students’
capacity to use those tools for genuine learning is worlds apart. The
differences come down to language, infrastructure, prior schooling, teacher preparedness,
and whether anyone has bothered to teach students what AI can actually do —
and, just as importantly, what it cannot.
This article traces those fault lines. It looks at what
generative AI genuinely offers Indian higher education — personalised learning,
multilingual support, broader access to academic resources — and at the
structural barriers that prevent those benefits from reaching students
equitably. NEP 2020 provides the policy backdrop. Bourdieu, Bernstein, Freire,
and Visvanathan supply the theoretical grounding. The argument is that equal
access to a technology does not produce equal educational outcomes, and that treating
AI as inherently beneficial without attending to infrastructure gaps,
linguistic inequality, weak AI literacy, and the absence of clear institutional
policies is a recipe for reproducing the very disparities that education policy
claims to address. | |
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