The debate about AI in design education often begins with the tool.
- Should students use it?
- When should they use it?
- What platform should they use?
- What counts as acceptable use?
Those questions matter.
But I am increasingly interested in what happens before the tool enters the process.
Before a student generates something, what have they noticed?
- What have they researched?
- What do they understand about the problem?
- What connections have they made?
- What are they trying to communicate?
- What is their point of view?
- What are they curious about?
- These are not AI questions.
- They are design questions.
Visual thinking gives students ways to spend time in this space.
- They can write.
- Sketch.
- Map.
- Collect.
- Connect.
- Sort.
- Question.
- Diagram.
- Annotate.
- Reflect.
None of those actions needs to produce the final outcome.
Their value lies in helping students decide what the outcome needs to do.
AI can then enter the process as one possible collaborator or tool.
- It can help generate variations.
- Challenge assumptions.
- Visualise possibilities.
- Extend something already underway.
But there is an important difference between:
- using AI to explore an idea
- and
- using AI instead of developing an idea.
That distinction is becoming central to my current research and teaching.
Perhaps the most useful question we can ask students is not:
What did you prompt?
It is:
What thinking happened before the prompt?