AI is not replacing teachers. It is exposing what schools forgot to teach

That confusion made sense once. When knowledge was harder to access, teachers were the main route to it. Schools existed to transmit facts, standardise learning, and prepare children for a world in which answers were scarce. But that world is gone. Today, a student can ask a machine for an explanation, a summary, an example, or a draft in seconds. The old bargain between schooling and knowledge has changed.

The real issue is no longer access to information. It is judgment.

That is why the panic around AI in classrooms is, at best, incomplete. Schools are right to worry about cheating, shortcuts, and overdependence. But banning AI or watching students more closely will not solve the deeper problem. More control rarely produces more understanding. It usually produces more compliance. And compliance is not the same as learning.

The better question is simple: what should education do in a world where answers are everywhere?

For too long, the answer has been obvious but inadequate. Schools have rewarded memorisation, speed, and reproduction of correct answers. That model produces test scores, but not necessarily thinking. AI exposes this weakness because it can now do much of the routine work that classrooms have historically valued. If that makes us uncomfortable, it should. But discomfort is useful if it forces reform.

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In my work on self-organised learning, that started with the “Hole In The Wall” experiments of 1999, I have seen how powerfully children respond when they are given a good question, access to information, and the freedom to work together. They argue, compare, challenge, and correct one another. They learn because they are thinking, not because they are being fed answers. Learning, in practice, is social. It happens through conversation, disagreement, and shared discovery. Those results have been lauded worldwide for the last 27 years, but nothing whatsoever has been done about them because of an examination system based on memorisation and compliance.

AI can either support that process or flatten it. Used badly, it becomes a shortcut machine: another way to avoid effort and another reason for schools to confuse output with understanding. Used wisely, it can act as a prompt for deeper thought. It can ask, “What makes you think that?” It can suggest another perspective. It can help students test ideas rather than simply finish tasks. In that role, it strengthens curiosity instead of replacing it.

That distinction matters because education should not be reduced to efficiency. The goal is not the fastest answer. It is the best thinking. If AI makes learning quicker but shallower, it has failed. If it helps children question, compare, and reflect more intelligently, it has educational value.

This is also why teachers matter more than ever. In an AI-rich classroom, the teacher is not obsolete. The teacher’s role is changing. Teachers are no longer just transmitters of content that machines can now supply instantly. They are designers of questions, builders of trust, and guides through uncertainty. They create the conditions in which children feel safe enough to say, “I do not know yet,” and continue thinking.

That is not a small role. It is the central one.

India should be especially careful not to treat AI as a technological fix for an old educational system. If classrooms remain obsessed with memorisation and ranking, AI will only make those habits more efficient. But if it is used to encourage inquiry, collaboration, and critical thinking, it could help education become more relevant to the future.

The danger is not that AI will replace teachers. The danger is that it will expose how much of schooling has already been reduced to routine. That is a warning, but also an opportunity. We can respond by tightening control and lowering trust, or by redesigning learning around curiosity, judgment, and dialogue.

If education is to remain meaningful, it must do more than distribute answers. It must help young people make sense of a world in which answers are instant but wisdom is still rare. That is a human task. And it is why the future of education will depend less on machines than on whether schools still know how to help children think.

Sugata Mitra is a professor of educational technology. He retired from Newcastle University, UK and is emeritus professor at NIIT University in India. He is the creator of The Hole In The Wall experiments and Self Organised Learning Environments (SOLE). Among his many global awards are the Dewang Mehta Award in 2003, TED Prize in 2013 and the Brock Prize in 2022.