Summary

The studio examines the effects of artificial intelligence on architecture and cities. We explore data-driven design processes by the use of algorithmic and parametric tools that take into consideration geographical, economical, personal, image, political, ecological parameters.

Content

Keywords

• Architectural form
• Data-driven design
• Artificial intelligence
• Urban design

Learning Prerequisites

Required courses

N/A

Recommended courses

AR-401(Y) Théorie et critique du projet MA1 (Huang).

Learning Outcomes

By the end of the course, the student must be able to:

• Interpret the morphogenetic parameters and other issues of relevance to the project using drawings and diagrams.
• Critique a specific project brief and a specific context and respond with a meaningful data-driven design concept.
• Translate a data-driven design concept into meaningful architectural propositions at appropriate scales and levels of granularity.
• Produce coherent architectural representations and models at sufficient levels of detail.
• Formulate the morphogenetic narrative and create convincing arguments for the design propositions.
• Develop convincing final diagrams, drawings, renderings, simulations, physical and digital models.
• Interpret the site-specific parameters and other issues of relevance to the project using drawings and diagrams.

Transversal skills

• Design and present a poster.
• Collect data.
• Make an oral presentation.

Teaching methods

• Presentations
• Mapping exercises
• Hands-on design activities
• Design reviews
• Group projects

Expected student activities

• Architectural projects will be developed individually (or exceptionally in groups of 2).
• Some group work may occur in the analysis stages.

Assessment methods

Projects will be reviewed and assessed based on:

(1) their conceptual strength and innovation,

(2) the coherence and resolution of their architectural translation,

(3) their representative clarity and expressive power, and

(4) the persuasiveness of their communication, both orally, and through the physical and digital artifacts. 

Supervision

Resources

Bibliography

Huang, J. (2015), Growth Typologies, Localities and Defamiliarisation: Experiments with Artificial Urbanism in Sichuan, Guangzhou and Beijing. Archit Design, 85: 70¿75. doi: 10.1002/ad.1980.

Ressources en bibliothèque

• Growth typologies, localities and defamiliarisation / Huang

Websites

• http://ldm.epfl.ch