The Hidden Curriculum of AI: Obedience, Not Curiosity
AI’s Lesson of Obedience
In the classroom, obedience often operates invisibly. It shows up as turning work in on time, formatting assignments exactly as instructed, and producing answers that match expectations. Step too far outside the brief, and your grade drops.
Grades remain the primary reward system in schools. Success is measured by finding the "right answer" quickly, not by exploring alternatives or, in design education, pursuing more creative possibilities. Given this, it's no surprise students aim for efficiency: good grades signal future opportunity. How can we blame them for using any tool available to maximize their grade?
Educators, for their part, want students to succeed but are reluctant to give lower grades for fear of backlash. If you're an educator, you know the story: that one time you dared give an A- and had the student in your office hours, demanding to know why they didn't get an A+. The extra labor of defending grades becomes exhausting. In the end, nobody wins.
This system creates the perfect conditions for AI adoption. It delivers fast, polished responses that feel authoritative, reassuring students they'll earn the grade they want. In design, polish is easily mistaken for correctness. Yet the rough, experimental work we as educators value is often misread by students as failure. The very structure of AI tools reinforces this obedience.
AI's design amplifies these problems. The tools train students into a ritual that looks deceptively efficient:
The Prompt Box. Type in almost anything (no matter how vague, incomplete, or incoherent) and the system obligingly produces a well-packaged reply. It feels authoritative, reads smoothly, and sounds like something a teacher might approve of. Predictable, clichéd, but reassuringly "correct.
The Single Window. Out goes the clutter of sketches, messy notes, and false starts. No napkin scribbles or divergent mindmaps. Just one polished solution, framed as the solution.
The Workflow. Generate, copy, paste, submit. Brutally efficient, yes, but also corrosive. The mess, the struggle, the happy accident of stumbling into an unexpected idea are airbrushed out.
The result? Students adopt AI's answers wholesale, mistaking polish for depth, and obedience for creativity. What remains is compliance, neatly formatted and turned in on time, with a high resolution finish.
Argument as Combat, Provocation as Risqué
Each semester, I start with two questions. The first: “what is an argument?” Almost unanimously, they reply that it is a fight. Not a reasoned exchange, not a structured back-and-forth of ideas, but a quarrel with winners and losers. The second: “what does provocative mean?” With equal certainty, they tell me it means risqué. Not a provocation that unsettles assumptions or sparks new ways of thinking, but something titillating and ornamental. In both cases, the underlying concept, the intellectual richness of dialogue and the generative spark of critique, has been quietly hollowed out.
This narrowing reflects something deeper. Ambiguity is treated as intolerable, problem-solving becomes thin, and students are unable to hold competing perspectives without assuming that someone must be wrong.
Add an education system that prizes quick, polished answers over experimentation, and you get creative decline. Creativity requires mess: false starts, rough drafts, and the proud defence of an experiment that mattered not for its outcome but for its process. Yet classrooms reward the tidy product rather than the turbulent journey.
The consequence is a generation trained to consume answers rather than to produce ideas, to obey rather than to wrestle with complexity. The very qualities that should make education expansive, argument, provocation, curiosity, are redefined into their most reductive forms, leaving us with students fluent in compliance but strangers to creativity.
Creativity ≠ Efficiency
We are often reassured by the makers of AI that its great gift will be efficiency. It will shave off hours of drudgery, they tell us, leaving us free to pursue the “real” work: deeper, more creative, more meaningful. In a corporate context this may sound plausible. Businesses thrive on time saved and processes streamlined. But creativity does not.
Creativity feeds on struggle. Wrestling with a stubborn idea, testing it against constraints, pushing through the frustration of not knowing is not wasted time. It is the engine of originality. The constraint becomes the spark, the dead end becomes the detour to somewhere unexpected. Remove the friction and you also remove the chance to stumble on something genuinely new.
If we surrender too eagerly to AI’s promise of speed and polish, we risk hollowing out the very habits that matter most in education: curiosity, resilience, and the willingness to venture into uncertainty. What efficiency cuts away is not wasted time at all but the messy process through which discovery, invention, and new forms actually emerge.
Pedagogy of Curiosity
If AI's hidden curriculum teaches obedience, then our response must be to design for its opposite: a pedagogy of curiosity that makes compliance impossible and exploration inevitable. How do we actually nurture creativity in a classroom culture that increasingly fetishises efficiency?
Four approaches:
1. Require process, not just product.
Shift the emphasis from the shiny final submission to the messy scaffolding that got a student there. Ask for sketchbooks, drafts, false starts, and reflective notes. Reward the courage to experiment, not just the ability to arrive at a neat solution. Students must learn to think like producers, not consumers: to take pride in the attempt as much as the outcome.
2. Emphasize human-only skills.
AI can generate fluent text and polished images. What it cannot do is draw on lived experience, emotion, and embodied understanding. Encourage storytelling, critique, humour, intuition, improvisation, and the subtle art of conversation. These are not inefficiencies to be ironed out. They are the very qualities that make human creativity resilient and distinctive.
3. Build intentional friction.
Constraints are not the enemy of creativity; they are its raw material. Assign tasks with limits that force invention. Restrict the palette, narrow the brief, or insist on a medium that students find awkward. Make them wrestle with boundaries instead of outsourcing the struggle to a machine. Creativity thrives where there is resistance.
4. Redesign assessments.
Perhaps the most important shift of all. As long as grades reward speed, correctness, and polish, students will continue to chase them like currency. Instead, design assessments that value risk, originality, and process. Grade the quality of the questions asked, not just the answers provided. Make room for projects that fail in interesting ways. Without assessment reform, every other intervention is cosmetic.
Classroom Strategies
The strategies below put these principles into practice. Each one rewards precisely what efficiency culture discourages: wrestling with problems, embracing dead ends, and finding value in the struggle itself.
1. Require Process, Not Product
Assignment: Material Constraint Challenge
Task: Create three versions of the same idea, each constrained by a different material.
Examples:
Model a shoe using cardboard, tape, and recycled plastic
Build a chair in an hour using only fabric scraps
Create a playground structure using only rope and bamboo
Model a wearable hat using string, rubber bands, and cardboard tubes
Learning Goal: To show that physical process actively shapes thought, not just output.
2. Emphasize Human-Only Skills
Assignment: Unsolvable Problem Challenge
Task: Give students a deliberately impossible brief and ask them to attempt three different solutions, documenting why each fails or succeeds partially.
Examples:
Design a portable house that fits in your pocket
Build a device that guarantees permanent happiness to anyone who uses it
Compose music for a full orchestra that must never make a sound
Draw a map that shows every possible journey a human being could take in their lifetime
Learning Goal: To emphasize reasoning, imagination, and insight in the face of impossibility.
3. Build Intentional Friction
Assignment: Two-Phase Problem-Solving
Task: Phase 1: Students solve a design or writing prompt without AI, documenting their thought process in detail. Phase 2: They input the same prompt into an AI tool and compare results.
Examples:
Create a recipe for a three-course meal with only five ingredients
Design packaging for food that is both edible and structurally sound
Design a chair that folds into something unexpected (a kite, a raft)
Design a museum of smells: how would exhibits be arranged, preserved, and experienced?
Deliverable: A comparison chart plus reflection answering: "What could I see that the AI did not? What did it show me that I had not considered?"
Learning Goal: To highlight what emerges only through human struggle and where AI can both limit and expand perspective.
