AI-augmented Universities Need Trinocular Vision


The global experience of seeding AI into the academic womb has been mixed at varied levels of adoption. Universities in North America and Europe have moved from sweeping prohibitions of generative AI towards promoting legitimate assistance and deterring academic misconduct. Aisa-Pac has also seen the rise of many innovative engagement models ranging from basic to advance while China continues to be an ideation warehouse overflowing with AI enriched finished goods and services. All of them involve redesigning assessments to include oral examinations, project-based work, supervised assignments and reflection on how AI was used. Some institutions incorporate AI literacy across disciplines rather than restricting it to computer science. An important lesson for India is the realisation of the fact that AI is not another computing department but another layer of every university.

India getting this balance right is critically important as its one of the world’s largest higher-education systems and talent provider. With millions of young learners entering universities, they no longer can be powered by legacy mono-engine but pushed by contemporary twin-engine. The first engine should remain conventional: teachers, laboratories, libraries, fieldwork, internships, seminars, studios, peer learning and face-to-face mentorship. The AI enabled second should offer personalised learning, intelligent tutoring, simulation, automated feedback, research assistance, adaptive content and data-driven academic support. A university running only on conventional education will soon become an antiquated museum while the two-engine universities become the twin-towers of learning. This is particularly important for India as it seeks to build universities towards Viksit Bharat@2047. Universities can no longer be graduate producing machines who know how to use AI but be capable of producing graduates who can build AI, govern AI, question AI and apply AI responsibly across the socio-economic spectrum. The choice for universities in this AI spread should be aligned with their private capabilities and not public status changing the role of universities.



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