Théorie et critique du projet MA1 (Huang)

Summary

The studio examines the effects of artificial intelligence on architecture and cities. Generative tools are approached as cultural and political instruments, shaping design through data grounded in territory, economy, identity, imagery, and ecology.

Content

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Keywords

• Architectural form
• New Typologies
• Data-driven design
• Artificial intelligence
• Vibecoding
• Urban Design

 

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 AI-driven design concept.
• Translate an AI-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.

Transversal skills

• Design and present a poster.
• Collect data.
• Set objectives and design an action plan to reach those objectives.
• Make an oral presentation.

Teaching methods

• Presentations
• Mapping exercises
• Hands-on design activities
• Design reviews
• Individual and/or Group projects

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.

Resources

Virtual desktop infrastructure (VDI)

No

Bibliography

1. Huang, Jeffrey, Mikhael Johanes, Frederick Chando Kim, Christina Doumpioti, and Georg-Christoph Holz. On GANs, NLP and Architecture: Combining Human and Machine Intelligences for the Generation and Evaluation of Meaningful Designs. Technology | Architecture + Design 5, no. 2 (2021): 207-224. https://doi.org/10.1080/24751448.2021.1967060.
2. Huang, Jeffrey, Dieter Dietz, Laura Trazic, and Korinna Zinovia Weber, eds. Transcalar Prospects in Climate Crisis: Architectural Research in re/Action. Zurich: Lars Müller Publishers, 2024.
3. Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Margaret Mitchell. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21),  610-623. New York: ACM, 2021. https://doi.org/10.1145/3442188.3445922.
4. Carpo, Mario. Beyond Digital: Design and Automation at the End of Modernity. Cambridge, MA: MIT Press, 2023.
5. Crawford, Kate. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press, 2021.
6. Del Campo, Matias, Stefan Manninger, and Andre Carlson. Archiitectural Hallucinations: Diffusion Models and New Aesthetics. International Journal of Architectural Computing 20, no. 4 (2022): 493-509. https://doi.org/10.1177/14780771221135036.
7. Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, et al. Generative Adversarial Nets. In Advances in Neural Information Processing Systems 27 (NeurIPS 2014). https://papers.nips.cc/paper/2014/hash/5ca3e9b122f61f8f06494c97b1afccf3-Abstract.html.
8. Mattern, Shannon. A City Is Not a Computer: Other Urban Intelligences. Princeton, NJ: Princeton University Press, 2021.
9. Zuboff, Shoshana. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York: PublicAffairs, 2019.

Websites

• https://www.instagram.com/mxd_epfl/
• https://epfl-pavilions.ch/en/exhibitions/artificial-architecture
• https://www.epfl.ch/labs/ldm/
• https://livingarchives.epfl.ch/projects/?type=Project&year=2021&year=2020&unit=LDM&sort=date

Moodle Link

• https://go.epfl.ch/AR-401_k