A Quick Primer for Design Faculty
The design profession and the way faculty prepare future design
professionals in the higher ed classroom are at a pivotal moment.
Generative AI can now produce polished images, layouts, video,
text, and visual variations before students have fully researched
an audience, developed a concept, tested ideas, participated in
critique, or worked through an iterative design process.
This raises questions specific to the design classroom: How do we
preserve process when outputs appear finished too early? How do we
evaluate work that may be visually convincing but conceptually
weak? How do we continue to teach authorship, judgment, craft, and
responsibility when parts of creative production are increasingly
shared with automated tools?
Why These Modules Exist
Design faculty are being asked to respond to generative AI while
the tools, institutional policies, professional expectations, and
student attitudes surrounding them are still changing. Students
may enter the classroom expecting to use AI, feeling pressured to
avoid it, or unsure when and how to disclose its use. Faculty are
also reconsidering how to teach and assess process when a student
can generate a polished-looking result before demonstrating
research, iteration, or intentional design decisions.
AI Literacy for Creative Classrooms
This is the first set of materials from Creative Futures Council,
built from real questions design and film educators are already
raising about AI in the classroom. This document contains nine
modules, two tracks, and an arc from the basics to professional
judgment.
Track 1 — Technical Foundations and Skills
- Foundations: What generative AI is and how it works
- Skill: Prompting as a design skill
-
Process: Maintaining the creative process with assistive AI
- Critique: Evaluating and editing AI output
Track 2 — Professional Practice and Ethics
- Ethics: AI ethics and model differences
-
Collaboration: Human-AI workflows Communication: Presenting
AI-assisted work
- Integrity: Content credentials and provenance
- Anthropology: Investigating questionable assets
What each module contains
-
Topic intro: faculty-facing framing, no AI expertise required
- In-class activity: 75–90 min structured exercise
-
Facilitation notes: how to introduce it, what to watch for
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Discussion questions: five per module, for critique or LMS
boards
Designed to evolve
These modules are also intended to remain fluid. Generative AI
models, creative platforms, institutional policies, professional
expectations, and public attitudes will continue to change. As
technology advances, AI literacy must advance alongside it.
Faculty may need to update examples, replace tools, revise
terminology, reconsider ethical questions, or adapt activities to
reflect new classroom and industry realities.