In Defence of Creative Fitness
On his podcast “Deep Questions”, in his book “Deep Work”, and in a recent New York Times opinion piece, Cal Newport talks about “cognitive fitness,” which he defines as the mental equivalent of physical exercise, requiring deliberate, active contemplation and mental focus to push against the shallow thinking caused by modern digital tools and AI. As a design educator, I’d like to apply that concept to creative fitness.
Educators have understood for a long time that creative exercise, including productive struggle, builds creative capacity. Just as cognitive fitness depends on regularly exercising attention, memory, reasoning, and contemplation, creative fitness depends on regularly exercising the capacities involved in making: observing, researching, drawing, writing, generating ideas, making connections, evaluating possibilities, tolerating uncertainty, and making decisions. As AI embeds itself in our daily lives and classrooms, design education should develop creative fitness, not simply artifact production or a hot portfolio. The classroom should deliberately protect the parts of the design process where students need to exercise the cognitive and creative capacities they came to art school to develop. I do want students to struggle with questions such as: Where do I start? What is the design problem? Whose perspective am I missing? What could I do that isn’t obvious? Why is this design better than that one? That struggle has real educational and creative value.
One of the dangers of AI is that it seductively offers easy cognitive and creative offloading. It allows us to bypass some of the difficult work that develops cognitive and creative capacities in the first place.
As design educators, we must ask: What capacities are we trying to develop in a student designer, and which of those capacities require exercise? And, when we introduce AI, is it exercising the student’s creative capacity and agency, or replacing the exercise?
I don’t necessarily need a fourth-year design student to spend six hours painstakingly removing backgrounds or producing twenty correctly sized digital assets simply because those tasks were once part of professional practice. There is relatively little educational value in preserving inefficient production labour for its own sake (unless it is the goal of the exercise). AI can reasonably participate in the design process where it removes that kind of labour. The distinction is between productive struggle and unnecessary labour.
If we repeatedly use AI to avoid difficult moments of concentration, ambiguity, ideation, writing, or problem-solving, we become less practised at precisely the activities that develop creative fitness. AI should only support the design process without replacing the intellectual and creative work the student needs to learn to do.
Therefore: Human first. AI second (if at all).
Students should develop understanding, judgment, ideas, and authorship before introducing AI. Once they have something of their own to bring to the conversation, AI may be used to challenge, extend, test, and materialize their thinking. Using AI to challenge an idea, generate counterarguments, expose assumptions, compare possibilities, or critique something the student has already developed can increase creative fitness because the student still has to interpret, judge, reject, refine, and decide. Agency remains with the student.
Using AI to generate the initial concept, write the rationale, produce the imagery, make the strategic connections, and polish the final presentation is different. In that case, the student may have outsourced precisely the cognitive and creative activities the assignment was intended to develop. That delivers a poor outcome.
The role of design education is therefore shifting. Rather than simply teaching students how to produce increasingly sophisticated artifacts—something AI can now do quickly and increasingly successfully—we need to teach them when to think for themselves, when human-made work matters, when or if AI is useful, how to maintain authorship and judgment when using it, and how to recognize when convenience is costing them intellectual or creative capacity.
What this means for curriculum and assessment
From my perspective, this means placing greater emphasis on design process and design thinking in the classroom. As AI becomes increasingly capable of producing convincing finished work, the quality of the artifact tells us less about the quality of the thinking that produced it.
My opinion, and a grading approach I will be following in my classroom, is to place greater weight on research, observation, ideation, drawing, experimentation, iteration, critical thinking, writing, decision-making, and students’ ability to explain and defend their choices.
My grading shift follows logically from that:
Old emphasis: Design Process → Artifact (finished design)
New emphasis: Thinking → Process → Decisions → Artifact (finished design)
The artifact still matters. But it should be evidence of the student’s thinking rather than a substitute for it, and grading should follow. Ultimately, the goal is to graduate designers who can use AI without surrendering the creative fitness, judgment, and agency that make them designers.
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