Why We Need to re-teach the Art of the Question

In a world increasingly shaped by artificial intelligence—where answers are instantaneous and information is abundant—it is no longer enough simply to know. What matters now is knowing what to ask.

Recent large-scale research into how people interact with ChatGPT suggests a striking pattern: an OpenAI/NBER study (September 2025) found that around three-quarters of conversations focus on practical guidance, seeking information, and writing. Many prompts, in other words, are framed around immediate utility—finding out what something is, how something works, or how a task can be completed. This seemingly superficial observation points to something deeper: the shape of our questions is shaping the structure of our thinking—and revealing a great deal about the way we teach, learn, and imagine the future.

As an educator and researcher currently developing cross-disciplinary learning models, I’ve become increasingly concerned by what this linguistic pattern implies. For me, it reflects a culture within education that prizes outcomes over inquiry, answers over curiosity, and content over connection.

If we are to prepare students for a future that is not only AI-literate but also critically, ethically, and creatively fluent, we must return to one of the most fundamental intellectual tools we possess: the question.

The Questions We Ask Shape the Minds We Build

Many AI queries begin with practical “What” or “How” prompts. These are pragmatic, outcome-oriented questions. They reflect a society increasingly conditioned for speed, clarity, and utility—all valuable traits, but insufficient on their own.

They serve the logic of productivity rather than the spirit of understanding.

In contrast, “Why” questions—the bedrock of philosophy, ethics, and critical inquiry—are comparatively rare. “Why does this matter?” “Why did this happen?” “Why do we believe this?” Such questions don’t yield tidy answers. They invite ambiguity and reflection, and require us to confront causality, consequence, and context.

Other question forms—“Who,” “Where,” “Which”—are similarly neglected. These help us locate ideas in people, places, systems, structures, and ourselves. When they are absent, we risk dislocating knowledge from the very world in which it operates.

In educational environments, this separation of content from context is more than a linguistic pattern—it’s a symptom of a deeper cultural condition: one in which the process of thinking has been eclipsed by the performance of knowing.

Siloed thinking

Here lies one of the great ironies of contemporary education and technology. We have built AI systems trained on the vast, interconnected corpora of human knowledge—capable of drawing threads between philosophy and physics, art and economics—and yet we often use them in linear and compartmentalised ways.

In my current teaching practice (Wellington College International Bangkok), we are challenging this fragmentation head-on. My proposed PhD research focuses on reintroducing cross-disciplinary learning in the crucial years of early secondary education. We are excited to be trialling thematic, project-based modules that deliberately collapse subject boundaries in favour of conceptual synthesis.

One proposed project, The Garden of Knowledge, invites Year 9 students, aged 13–14, to explore the interconnected nature of knowledge through scientific, artistic, and historical lenses. An artwork inspired by the growth of roots might lead to explorations of colonial botany, ecological systems, or the metaphorical networks of data and language. Students work both independently and collaboratively, with each idea branching into others like roots sharing the same soil.

Rather than stopping at “What is a garden?” or “How does it grow?”, they are guided toward questions like:

“Why do certain knowledge systems dominate others?”

“Who gets to decide what counts as valuable knowledge?”

“Where do art and science intersect in the way we imagine the world?”

These are the questions that rarely appear in typical AI interactions or indeed in departmental schemes of work. And yet, paradoxically, they are exactly the kinds of questions AI could help us pursue—if we approached it with a spirit of inquiry rather than efficiency.

The Moment for Inquiry Is Now

By engaging AI merely as a tool for instruction or automation, we are not just missing an opportunity; we risk mispreparing and falsely mis-guiding a generation. These technologies could help us map complex ideas, interrogate assumptions, or simulate ethical scenarios. Instead, they are too often used to shortcut essays, reword emails, or summarise content already known.

This stems from educational systems still defined by subjects in isolation, content rather than curiosity, and assessments that reward accuracy over ambiguity.

Teachers are stretched, students are hurried, and inquiry is often squeezed out in the name of outcomes. The result is a missed opportunity—not just to expand knowledge, but to model thinking as an art form.

It seems that not only are we outsourcing research and response to AI we are, gradually, subtly and somewhat blindly outsourcing the capacity for reasoned thought and inquiry itself.

Toward an Interrogative Culture

If we want to prepare students for a world saturated with machine intelligence, we must reimagine the purpose of education itself. Classrooms should not simply prepare students to use technology—they must equip them to interrogate it.

This is not a marginal concern. Research from the National Literacy Trust (2025) found that 86.2% of teachers agreed students should be taught to engage critically with generative AI tools.

This means:

Designing learning that encourages broader, deeper, and more contextual questions

Reconnecting subjects to surface shared tensions, metaphors, and ideas

Using AI not just for productivity, but for reflection, comparison, critique, and creative divergence

Instead of asking “What is the answer?”, we might begin with:

“Why is this question being asked in this way?”

“Who is affected by this knowledge?”

“Where are the blind spots in this argument?”

“Which other disciplines might help us think more clearly?”

These are not easy questions. But they are the questions that lead us toward wisdom, not just information.

Conclusion: The Future Belongs to the Inquisitive

At its best, AI can be a partner in thought and a co-creator—a mirror to our assumptions and a window into new perspectives. But for that to happen, we must change not just how we use these systems, but how we teach people to think and work alongside them. Rephrased, we must change our system first.

If we continue to ask machines narrow questions, we will continue to receive narrow answers. But if we cultivate a generation of thinkers who ask better, braver, more generous questions—questions that cross disciplines, challenge orthodoxies, and consider consequences—we open the door not only to technological intelligence, but to something deeper: integrated intelligence.

Plato records Socrates’ famous claim that “the unexamined life is not worth living.” In an age of artificial intelligence, the same might be said of the unexamined question.

We should be careful not to imagine questioning as harmless. Revolutions, intellectual or technological, rarely begin by following the status quo; they begin when new questions become possible, permissible, or urgent.

If human beings stop asking the larger questions—ethical, social, imaginative—we should not assume those questions disappear. They may simply be pursued elsewhere, by systems increasingly capable of generating, testing, and acting on lines of inquiry, but without fear, care, or responsibility in the human sense.

The future will not be built by those with the quickest answers, but by those with the most difficult questions—and the courage to ask them.

Daniel Scott - July 2025