Our Paper has been Accepted to eCAADe 2026!
We’re excited to announce that our paper “Why Students Don’t Use Urban AI: A Study of Machine Learning Tool Adoption in the Design Studio” has been accepted to the 44th eCAADe Conference — Informed Creativity and Fabrication in Architecture and Engineering!
The paper, co-authored by Ofir Glassman, Orly Cohen-Moas, Achituv Cohen, Noam Teshuva, and Jonathan Dortheimer, investigates a question that sits at the heart of our research: if we build AI tools for urban design, do students actually use them?
We studied how third-year architecture students engaged with a web-based machine learning tool that predicted pedestrian volumes as a proxy for walkability. Despite being introduced to the tool in a design studio setting, students rarely integrated it into their iterative design process. Through a usage survey and 12 semi-structured interviews, we identified four key barriers to adoption:
- Mistrust of opaque outputs — the tool’s predictions often felt implausible and hard to verify
- Translation difficulty — students struggled to convert predictive maps into concrete design decisions
- Unmet expectations for dialogue — students expected an interactive, conversational AI rather than a one-way analytics tool
- Time-benefit misalignment — studio culture and assessment structures made the tool feel too costly to learn mid-project
These findings point to a broader sociotechnical challenge: making AI tools genuinely useful in design education requires more than technical capability. It demands attention to model transparency, pedagogical scaffolding, and the realities of studio culture.
We look forward to sharing this work at eCAADe 2026 and to the conversations it will spark about the future of AI in architectural education.