Critical Issues in Urban Development and Architecture: AI’s Hidden Material Footprint
| Lecturer (assistant) | |
|---|---|
| Type | seminar |
| Duration | 2 SWS |
| Term | Wintersemester 2025/26 |
| Language of instruction | English |
| Position within curricula | See TUMonline |
| Dates | See TUMonline |
- 13.10.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 20.10.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 03.11.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 10.11.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 17.11.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 24.11.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 01.12.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 08.12.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 15.12.2025 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 12.01.2026 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 19.01.2026 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 26.01.2026 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
- 02.02.2026 15:00-16:30 4157, Arbeitsraum/mit Besp.Grp.
Admission information
Objectives
After successful participation in the module, students are able to
- Recognize that AI’s “cloud” is not immaterial, but a heavy, resource‑intensive, geographically fixed infrastructure.
- Understand the planetary metabolism of the cloud as a complex geo-political and socio-technical assemblage with unequal environmental and social impacts.
- Apply critical urban theory to analyze the socio-spatial production process of AI’s cloud and its related territories (mines, energy grids, data centers, and labor markets).
- Analyze the immediate and embodied resources an everyday AI query consumes and relate this consumption to patterns of extended urbanization.
- Evaluate interconnected environmental and social costs of AI usage and argue for more responsible digital practices.
- Recognize that AI’s “cloud” is not immaterial, but a heavy, resource‑intensive, geographically fixed infrastructure.
- Understand the planetary metabolism of the cloud as a complex geo-political and socio-technical assemblage with unequal environmental and social impacts.
- Apply critical urban theory to analyze the socio-spatial production process of AI’s cloud and its related territories (mines, energy grids, data centers, and labor markets).
- Analyze the immediate and embodied resources an everyday AI query consumes and relate this consumption to patterns of extended urbanization.
- Evaluate interconnected environmental and social costs of AI usage and argue for more responsible digital practices.
Description
The course deals with critical current issues in urban development and architecture. For each implementation, scientific staff at the Chair of Urban Development select different topics from their research and/or practical experience.
In this semester the seminar addresses AI’s Hidden Material Footprint. The course examines the material and social dimensions of AI’s “cloud,” revealing it as a resource-intensive, geographically situated infrastructure. Students will explore its planetary metabolism, tracing connections across mines, energy grids, data centers, and labor markets. Using critical urban theory, the course analyzes how AI’s everyday operations consume resources, extend urbanization, and produce uneven environmental and social impacts, while encouraging more responsible digital practices.
In this semester the seminar addresses AI’s Hidden Material Footprint. The course examines the material and social dimensions of AI’s “cloud,” revealing it as a resource-intensive, geographically situated infrastructure. Students will explore its planetary metabolism, tracing connections across mines, energy grids, data centers, and labor markets. Using critical urban theory, the course analyzes how AI’s everyday operations consume resources, extend urbanization, and produce uneven environmental and social impacts, while encouraging more responsible digital practices.
Prerequisites
Das Forschungsseminar richtet sich an StudentInnen des Masterstudiengangs Architektur und Urbanistik.
Teaching and learning methods
Refer to English version.
Examination
Presentation and short report
Recommended literature
specified in syllabus on moodle