Ep 49: AI in the Classroom with Emily Allen Burroughs from DSA
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AI in the Classroom with Emily Allen Burroughs from DSA
The Director of Education at the Designer Society of America on what is actually happening when students use AI uncritically, why foundational skills are irreplaceable, and how educators and mentors can shape what comes next.
- Student work is starting to sound identical — not because students lack talent, but because unedited AI output replaces individual voice. When students do not believe their own perspective is worth sharing, they let the algorithm speak for them. That is the real problem to solve.
- Foundational design skills are not optional background. Code compliance, spatial planning, hand drafting, and understanding structural feasibility are the judgment layer that makes AI output safe to use. Without that foundation, a beautiful AI render can be unbuildable.
- Voice memos are one of the most effective ways to use AI without losing your voice. Recording a rough verbal thought and then refining the AI output preserves your priorities and tone in a way that prompting from scratch rarely does.
- AI is excellent at early-stage client communication. Using quick visuals or mood boards to ask "is this the direction?" before committing to detailed drawings is one of the smartest, most time-efficient applications available right now.
- DSA is launching a new Student Membership as part of a full organizational relaunch — creating a structured entry point for the next generation of designers to connect, learn, and find mentorship in the industry.
Emily Allen Burroughs is the Director of Interior Design Education at the Designer Society of America (DSA), where she leads education initiatives and mentorship programming for both students and professionals across the DSA network. With over a decade of experience in design education, Emily works at the intersection of traditional design training and emerging technology — helping the next generation of designers develop the judgment, voice, and technical foundation to use AI with integrity.
The Generational Gap: How Students and Professionals Are Using AI Differently
Emily sees both ends of the spectrum daily. Students are frequently all-in with AI tools — which is not inherently a problem, except when they are all-in without critical evaluation of what comes out. Established professionals tend to be curious but cautious: aware of AI's potential, but protective of workflows that have served them well and uncertain about where AI actually fits.
- High adoption, low editorial judgment on outputs
- Tendency to publish AI-generated copy without personal input
- Uneven work losing individual voice
- Sometimes lack confidence that their own perspective is worth keeping
- Need a framework for responsible use, not just access to the tools
- Curious but cautious — aware of AI without being immersed in it
- Protective of tried-and-true workflows
- Concern about losing the human spark that defines their practice
- Often waiting for clear proof that the tool is worth the disruption
- In many cases, have more to gain from AI efficiency than they realize
The framing both Jenna and Emily return to: AI is a tool, like AutoCAD or Photoshop or Revit. It is at its most valuable when it supports expertise that already exists. The problem is not the technology. It is the absence of a thoughtful framework for using it — and that framework is exactly what design education has the opportunity and responsibility to provide.
The Voice Problem — When Student Work Starts to Sound Identical
Emily shared one of the most eye-opening observations in this conversation: student submissions are starting to sound nearly identical, even when coming from students with completely different backgrounds, aesthetics, and design sensibilities. That homogenization is not a coincidence. It is what happens when AI-generated content is published without personal input — when the prompt goes in and the output goes out with nothing in between.
The underlying issue is more concerning than a formatting problem. Many students do not believe their own voice is compelling enough. They feel their unedited thoughts are too rough, too informal, too uncertain — and AI offers the appearance of polish and confidence. So they let it do the talking. And in doing so, they trade away the exact quality that makes design personal, emotional, and worth hiring for.
"Your work is more than a deliverable. It is a reflection of your perspective. And that cannot be replicated by an algorithm."
— Emily Allen BurroughsJenna's approach to this in her own work: voice memos. Recording a quick verbal note — even into ChatGPT directly — and then refining the output means the starting point is her actual thinking, her priorities, her tone. The AI organizes it. It does not originate it. Teaching that distinction — between AI as a starting point versus AI as a replacement — is one of the most important things design education can do right now.
The Visual Side: When AI-Generated Design Work Breaks Down
AI tools can now generate renderings, floor plans, mood boards, and elevations — and the outputs often look polished and professional on the surface. The problem is that visual polish has no relationship to design validity. Emily has seen student submissions where the AI-generated work looked compelling in presentation and was structurally or legally indefensible in reality.
- Floor plans that ignored building codes, egress requirements, or structural feasibility
- Multiple student submissions featuring nearly identical renderings — same composition, same palette, different names on the cover sheet
- Furniture that appears to float, clash in scale, or violate basic spatial logic
- Renderings that looked designed but had no designer thinking behind them
- Visual output submitted as design work without any evidence of planning, iteration, or judgment
Jenna draws the line clearly: she uses Midjourney for early concepting and exploration. The mural in her office started as an AI-generated image. But it was a starting point — not a finished product, and not a substitute for the design decisions that came after it. That distinction between AI as exploration tool and AI as deliverable is the one that design educators need to make explicit.
"Just because it looks good doesn't mean it's grounded in good design. AI should support our process — not take it over."
— Jenna GaidusekWhy Foundational Skills Are Not Negotiable
Emily is direct on this point: hand drafting, spatial planning, code compliance, and technical knowledge are not quaint remnants of pre-digital design education. They are the judgment layer that makes any design output — AI-generated or otherwise — safe to actually build.
A designer who understands egress requirements can look at an AI-generated floor plan and immediately see where it fails. A designer who has planned spaces by hand understands scale in a way that allows them to evaluate a rendered image critically. A designer who knows code can catch the unbuildable detail before it becomes an expensive conversation with a contractor or a liability.
Without that foundation, AI tools do not elevate design work. They produce convincing images of bad design. And the client who hired a designer because the portfolio looked compelling has no way to know the difference until the project is underway.
Design is not about pretty pictures. It is about function, flow, and solving real problems for specific people in specific spaces. That takes judgment built on technical knowledge — and no amount of AI capability changes that requirement.
Where AI Genuinely Helps — Practical Applications for Designers at Any Level
Despite the cautions throughout this episode, both Jenna and Emily are clear: there are specific, high-value applications of AI in design practice that work well and are worth building into a workflow. The common thread is that these are all applications where AI serves communication or organization rather than replacing design judgment.
Disclaimer: This blog was written using AI as a recap from the recording then edited by the author for accuracy and details.
