MaCAD – Artificial Intelligence in Architecture – Studio
Senior Faculty: Angelos Chronis
Faculty Assistant: Lea Khairallah
That artificial intelligence will fundamentally change our lives is not any more a matter of debate. It’s a reality. What is also a reality is that the very same concepts that led to the coinage of the term have been around for more than a century. Still, it is the combination of vast computational power and data that has led to the explosive development of these concepts today.
Although that explosive development is obvious in big tech and its applications in our daily lives, it is not that obvious in all other fields. For many, the architecture, engineering and construction (AEC) industry is at the right moment for an equally explosive development that may transcend all aspects of our urban environment. The constantly growing development of AI-related generative design methods, construction processes and data driven analyses are resembling the fertile ground of the early computational design days.
However, this promising development of novel digital tectonics also brings with it similar pitfalls to that early computational design era. The imposition of an overly complex methodology of design that fails to address fundamental real challenges of our urban condition today. Climate change, pandemics, growing inequalities are just a few of the challenges that would greatly benefit from AI-driven design processes right now and as researchers, designers and evangelists of an augmented intelligence architecture, we are here to discover the ways.
In the “Artificial Intelligence in Architecture” studio we aim to explore the ways that the state of the art AI advancements can help us design and construct more efficient, sustainable and liveable urban environments.
Learning Objectives
At course completion the student will:
- Identify, review and evaluate current challenges of the AEC industry that require AI processes
- Design an applicable methodology for developing an AI design process
- Source or develop appropriate data sets of design intelligence
- Train, apply and evaluate AI models
- Develop a replicable and generalizable AI method and integrate it in a publishable tool
- Disseminate the developed tool