Within the ACESD Theory course, students will engage with both foundational theory and emerging debates.
This course explores the intersections of computational design, sustainability and artificial intelligence in architectural practice. It introduces students to the theoretical underpinnings of computational design and critically examines how AI-driven tools—from generative algorithms to data-driven optimization—are transforming the way architects conceptualize, design, and deliver projects. While sustainability is addressed as a recurring theme, the focus lies on understanding the broader social, cultural, and professional implications of AI in design.
Within the course students will engage with both foundational theory and emerging debates. Early sessions cover the history and principles of computational design, followed by an introduction to machine learning and AI applications in architecture. Midway, invited experts present on topics such as generative design, ethical considerations of automation, and the environmental impacts of data-intensive tools. Later sessions shift toward case studies, critical readings, and group discussions where students debate issues like authorship, bias in algorithms, and the shifting role of the architect in an AI-augmented profession.
The course emphasises active participation through debates, critiques, and discussions. Students are encouraged to question assumptions, challenge trends, and develop informed perspectives on how AI shapes architectural culture and labor. By the end, participants will not only gain an understanding of current computational and AI-driven approaches but also be able to articulate critical positions on their opportunities and risks, especially in relation to sustainability and the future of architectural practice.
During the course students will:
In the very first lecture of the theory class, AI was a scary, unpredictable tool for me. However, after deep thinking and various perspectives, it feels more like a “work buddy”. In this blog, I’d like to elaborate more on this shift in idea I had. Nowadays, in nearly every sector, people are scared of … Read more
Over time, and after being asked this question more than once, my answer about the purpose of AI in AEC has evolved. It hasn’t changed drastically, but it definitely became clearer and more grounded. Influence & Purpose What influenced me the most was listening to different speakers, especially the MaCAD alumni. One talk that really … Read more
Introduction — Where My Interest Began My interest in AI and its application in the AEC industry started before this course. During the IAAC GSS, I worked on a study in Bogotá using GIS and image‑recognition tools to map sensory criticality in care-focused urban zones. What surprised me most was how accessible the process was. … Read more
At the beginning of the semester, we were asked to reflect on the role of artificial intelligence in the AEC industry. Looking back, my answer then came from a much more limited understanding. Revisiting the question now, after a series of lectures, I realize that what has changed is not so much how much I … Read more
