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:
From automation to infrastructure Before starting this course, I primarily understood Artificial Intelligence in the AEC industry as a productivity tool—something used to automate repetitive tasks, accelerate modeling, or optimize isolated steps within the design workflow. AI was, in my mind, an add-on: powerful, useful, but largely standalone. Over the duration of the course and … Read more
The Purpose of AI in the Age of Resource Scarcity Introduction: Redefining the Question The question “What is the purpose of AI in AEC?” often elicits a predictable response focused on speed. For years the industry has viewed Artificial Intelligence primarily as a mechanism for automation. It is seen as a faster way to produce … Read more
Artificial Intelligence (AI) is changing the Architecture, Engineering and Construction (AEC) industry in ways we’re only beginning to understand. As computational design and software advances and is tasked to handle more complex and data-intensive forms, AI offers real potential to optimize workflows and improve design team collaboration from initial concepts on Schematic Design (SD) to … Read more
AI in AEC is often pitched as a design generator or a shortcut to faster output. We pushed a more real definition: AI’s purpose is decision support, helping teams see risk earlier and choose better options, while humans remain accountable. AEC is a chain of high-stakes decisions made under pressure: feasibility, coordination, procurement, construction risk, … Read more
AI in intelligent architecture enhances design efficiency, sustainability, and user‑centric spaces. Key benefits include automation, data‑driven insights, and optimized building performance. Challenges involve data privacy, high implementation costs, and skill gaps. The future promises adaptive buildings, predictive systems, and seamless human‑AI collaboration shaping more resilient, responsive, and sustainable built environments. 1. AI-Driven Design Innovation Generative … Read more
Introduction: More Than a Robot in a Hard Hat The buzz around Artificial Intelligence in the Architecture, Engineering, and Construction (AEC) industry is impossible to ignore. Every conference seems to feature a new tool promising to revolutionize everything from design to demolition. You might be forgiven for picturing an AI as a robot in a … Read more
The Starting Point: AI as a Faster Pencil When I first began this journey on October 9th, I approached AI tools primarily through the lens of efficiency. My initial focus was on faster modeling, optimization, and the ability to test more options in less time. To me, AI was a high-powered calculator—a tool applied after … Read more
In the early stages of learning, artificial intelligence was perceived primarily as a digital aid tools created to improve efficiency, accuracy, and coordination across different stages of a project. AI was largely understood as a decision-support system, particularly valuable during the early design phases, yet always positioned as secondary to human expertise and judgment. However, … Read more
Initial Perspective: AI as an Efficiency Tool At the beginning of the course, I viewed AI primarily as a means to enhance productivity. It appeared to be a practical instrument for automating routine tasks, such as refining designs or performing structural calculations. By minimizing errors, reducing time requirements, and lowering costs, AI could expedite project … Read more
What Is the Purpose of AI in the AEC Industry? Artificial intelligence is not only a technology aimed at automating tasks; insights shared during this course demonstrate that AI plays a far broader and more strategic role in the Architecture, Engineering, and Construction (AEC) industry. Through real-world applications and practical case studies, AI emerges as … Read more
Introduction: The Wrong Question We Were Asking For years, the question sounded simple: What is the purpose of AI in AEC? The answers were predictable speed, automation, productivity. Faster drawings. Fewer errors. Leaner workflows. That definition collapsed the moment we confronted Jakarta. Through our studio project Floating Grounds, developed in the flood-prone Penjaringan District, and … Read more
Design via Experimentation with the Black Box When I started my MaCAD program this semester, AI felt like a threat. As an industrial designer, I saw it as this incomprehensible pattern-finding machine that could somehow analyze thousands of products simultaneously, finding relationships I’d spend years trying to notice. The black-box nature terrified me—I couldn’t trace … Read more
The purpose of artificial intelligence in architecture, engineering, and construction (AEC) is not to replace architects or engineers, but to support better decisions in an increasingly complex field. Today, the built environment is shaped by overlapping layers of constraints and ambitions: environmental performance, structural behavior, material systems, costs, timelines, regulations, and social impact. Managing this … Read more
The conversation around Artificial Intelligence in Architecture, Engineering, and Construction (AEC) often begins and ends with the concept of “efficiency”. We discuss doing things faster, reducing man-hours, and automating mundane tasks. But as the industry faces unprecedented challenges, the true purpose of AI is shifting. It is no longer just about speed; it is about … Read more
In AEC, the purpose of AI is not to replace architects or engineers. The purpose is to improve decision-making and coordination, while keeping clear responsibility. In AEC, the purpose of AI is not to replace architects or engineers. The purpose is to improve decision-making and coordination, while keeping clear responsibility.AI can be seen as a … Read more
Middle east, 1067 AC scene 1: Long before the word algorithm existed, a woman draws lines in the send. She is not an architect. The word does not exist yet either. She is simply someone who must decide where people sleep when the river floods. She draws, erases, redraws.She listens to the wind.While She remembers … Read more
