Master's Degree in Artificial Intelligence for Architecture & Design
After what it was called “the first digital era in architectural design”, (1990-2005), the discipline has started a general debate about how the “second digital era in design” should be defined.
The appearance of Big Data, breakthroughs in Artificial Intelligence making that type of algorithms ubiquitous and, also, the exponential increase of robotic technology and its access easiness for non experts, has provoked a debate about a shift in the Architectural paradigm that is attacking the main definition of what an architect is.
Architects are obliged to work as/or with computational experts for the new transdisciplinar design methodologies.
Lack of these types of skills in new designers’ generations can cause a very dangerous situation: our discipline design methodologies will be led by architecture non-experts.
Architects arrive late to the Artificial intelligence era, and it can be considered innocent to think that such a shift in humanity will be not affecting our discipline enough to have to train our future architects with basic AI related skills. It is precisely within the Architectonic field were a more disconnected and disjointed debate is taking place.
This course intends to contribute to the improvement of this disconnection through the general improvement of an Artificial Intelligence background, customized for architect, so they can be future leaders in the future transdisciplinary work environments.
Overview
Nowadays, the next step within the Digital Architectural Era has been stepped forward. This first digital era “formal” approach has been discarded to step into new Artificial Intelligent based design methodologies.
In that sense architects are trying to understand and investigate the messy description of nature discarding the 90’s digital aesthetics based on the new AI based possibilities.
With a clearly interdisciplinary approach, the program proposes to deepen in the relationship between Architecture and Computation within the methodological process of design through the study of Artificial Intelligence and its algorithm. Deep Learning (DL), Machine Learning (ML), Multi-Agent System Design (MAS), Person-centered Ambient Intelligence (AAL), Evolutionary Computation (EC), Shape Grammar (SG) or Linear and Logistic Regression (LR) become part of the architectural design from the nano-scale to the territorial scale, both in the data analysis process, Data Mining, as in theoretical discourse as well as in the language consolidation process.
New digital approaches, intelligent system finding based, started to be proposed 10 years ago. The idea of complex systems with intelligent components with emergent behaviors was proposed as the basis for design developments. Design of buildings as dynamical systems based on their continuous variation caused by the intelligence of their components interacting with each other, is proposed as the cause for the emergent properties that will configure in the future architectonic design.
Objectives
The main aim of the program is to provide designers with a wide knowledge of the field and to abilitate them to be able to work in transdisciplinar environments in the future.
As Artificial Intelligence is widely affecting all layers of human society and research disciplines it is considered to be of fundamental importance to create a program that will prepare designers for that future situation.
It is proposed a full-time intensive training in Artificial Intelligence techniques applicable to several types of designers’ processes.
One of the main focus of the program structure will be flexibility, allowing the contents to be updated annually depending on the last Artificial Intelligence breakthroughs. According to that idea, it is proposed Research Informed Teaching as the basis for teaching methodologies.
Topics in depth studios 2020-21
Artificial Intelligence based teaching must have the flexibility for updating content regularly. Artificial
Intelligence is a discipline that is exponentially growing in content, making previous algorithmics obsolete even monthly.
As an example, we can take for example the obsolescence op perceptron based algorithms with the appearance of Deep Learning Techniques.
Proposed topics for the first edition of the Master design by research subjects are:
● Optimization procedures for fabrication
● Interaction & Reflection; human-computer interaction and responsive spaces
● Space Syntax; self organized multi-agent environments
Skills and learning outcomes to be acquired by the student
As so, the learning process will be clearly divided in two main aims
● Obtaining a general knowledge about the Artificial Intelligence discipline as a whole, being able to understand its main aims, contents and research current interest for society.
● Developing the skills, mathematical and computational , for being able to apply along the practical
exercises the algorithmic processes that will be studied.
Student competences
● Up to date Architects regarding key concepts on nowadays theoretical/technological debate
● Embedded Technologies | Calm Technologies Skills Artificial Intelligence based
● Collaborative practise | Inter & Transdisciplinar Architects
● Understanding of Research based Design
● Research skills development
● Holistic training regarding Artificial Intelligence for having competitive architects in future
work environments
● Understanding rigour and Method Shift on the “traditional” Architectural Practise
● Capabilities for managing Interaction-Participation-processing designs

