What should students learn in the age of AI?

For centuries, education systems were built on a simple assumption: knowledge was scarce. Teachers, textbooks, and libraries were the primary gateways to information.

Classrooms, therefore, focused on transmitting knowledge, often through memorisation, repetition, and standardised testing.

Artificial intelligence is quietly dismantling that model.

Today, a student can generate an essay, summarise complex readings, solve mathematical problems, or receive explanations on nearly any topic within seconds. The central question confronting educators is no longer whether students have access to information.

They do, more abundantly than any generation before them. The deeper question is what it now means to be educated in a world where information is instantly available.

The distinction between information and understanding has become central to the purpose of schooling. Many traditional assignments—structured essays, textbook summaries, and formulaic answers—are precisely the tasks AI systems can now perform with ease.

Attempting to ban these technologies is unlikely to succeed. Technology has always reshaped learning environments, and AI will be no different.

Instead, AI exposes a deeper issue: much of schooling still rewards the reproduction of information rather than the cultivation of thought.

This moment calls for a rethinking of learning itself. If machines can generate answers, schools must focus on forms of thinking that cannot be automated.

Dialogue, interpretation, imagination, and judgment become central. Oral examinations, debates, collaborative inquiry, and project-based learning may become far more meaningful indicators of understanding than standardised essays.

Teachers are already encountering this shift. A student who once struggled to structure an essay can now generate one in seconds. The challenge is no longer detecting AI use, but designing tasks where thinking cannot be outsourced.

Asking students to defend arguments, reflect on personal experiences, or interpret contemporary events through theoretical frameworks demands engagement that automated systems cannot fully replicate.

Paradoxically, AI may compel education systems to rediscover creativity and critical pedagogy.

In Creativity and Critical Pedagogy in Education, co-authored with Professor Arpan Yagnik of Pennsylvania State University, we argue that creativity in education cannot be reduced to individual originality or isolated innovation. It must be understood within broader social, cultural, and political contexts.

Classrooms should not simply produce efficient problem-solvers but also thoughtful individuals capable of questioning dominant narratives and imagining alternatives. AI makes this argument more urgent.

If machines can generate content, synthesise information, and replicate patterns of knowledge production, the uniquely human dimension of learning lies in the ability to interpret, critique, and reimagine the world. Creativity, in this sense, is not merely about producing new ideas but about cultivating the intellectual courage to challenge established frameworks.

This is also where the humanities regain relevance. Disciplines such as philosophy, history, literature, and political theory train students to grapple with ambiguity, ethical dilemmas, and competing perspectives—questions that no algorithm can answer conclusively.

In India, where schooling remains exam-centric and driven by memorisation, AI exposes the limitations of a system organised around information recall. When machines can reproduce information instantly, memorisation alone loses much of its value.

As policymakers debate the integration of AI into education, the conversation cannot remain limited to digital infrastructure. The deeper question is pedagogical. How should curricula, teacher training, and assessment evolve in a world where information is abundant but judgment remains scarce?

The challenge before educators is not merely technological but philosophical. What kinds of thinkers should schools cultivate—individuals who can retrieve answers or citizens capable of exercising judgment in a complex world?

If classrooms are to adapt, teachers must be supported in navigating this transition. Teacher training still focuses on curriculum delivery and assessment compliance rather than on inquiry-driven learning.

Teachers must guide students in interpreting information, questioning automated outputs, and developing judgment. Preparing educators for this shift will be essential if AI is to strengthen learning rather than merely accelerate information consumption.

The writer is an education specialist, currently pursuing her PhD at Sharda University.

(Disclaimer: The views expressed above are the author's own. They do not necessarily reflect the views of DH.)