Education for a World We Cannot Yet Imagine
We often judge education by how well students answer questions. But what happens when the questions themselves change?
I see three levels of education, each preparing students for a different relationship with the unknown.
The first is education for the known knowns. We teach students facts, concepts, and procedures, then ask them questions similar to those they encountered in class. Success means recognizing the question and recalling or applying the expected answer.
This knowledge matters. But a student who performs well in a familiar classroom setting may still struggle to use that knowledge in the real world.
The second is education for the known unknowns. Here, we go beyond recall to develop critical thinking, problem-solving, and storytelling within a field. Students learn to identify gaps in their understanding, investigate problems, and communicate what they discover.
These skills help them respond when a situation is different from what they have seen before. They may not know the answer, but they can recognize the problem and work toward a solution.
But what happens when their world changes so profoundly that even familiar ways of defining problems no longer work?
That brings us to the third level: education for the unknown unknowns.
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At this level, students need more than answers or methods. They need the capacity to notice that their assumptions no longer fit, imagine possibilities they have not been taught, and discover what they need to learn next. They must be willing to ask unfamiliar questions, experiment without a clear path, and revise their understanding as the world changes.
We cannot teach unknown unknowns in advance. We can, however, create opportunities for students to encounter uncertainty and practice responding to it.
My concern is that much of our education system remains organized around the first level, with growing attention to the second and too little attention to the third.
AI makes this imbalance harder to ignore.
When students can turn to AI for explanations, summaries, and answers, reproducing knowledge becomes less convincing as the central purpose of education. That does not make knowledge irrelevant: students still need enough understanding to question an answer and judge whether it makes sense. But it changes what we should ask them to do with that knowledge.
AI also challenges the second level. Tasks involving analysis, problem-solving, and communication can increasingly be performed with AI assistance. Teaching these skills now requires us to reconsider where students exercise judgment and how they take responsibility for the result.
The third level may therefore become education’s most consequential task. Creativity, imagination, and an innovative mindset help students decide what is worth investigating when neither the question nor the answer is clear.
I would hesitate to call these capacities “untouched by AI.” A stronger argument is that they become more important as AI expands what we can do. Students will need to choose purposes, question assumptions, and decide which possibilities deserve pursuit.
The question for educators is no longer simply, “Can our students solve the problems we give them?”
It is also, “Can they recognize and respond to problems we have not yet imagined?”
