Critical Algorithms for Architectural Data


As architectural production has gone digital, databases and archives of various sorts have become a focus of design experimentation. The field of critical algorithm studies offers crucial methods for seeing the biases, assumptions, stereotypes, and injustices that lurk within digital practices. This course examines the techniques, theories, and historical resonances of a particular branch of contemporary architecture that is obsessed with collecting, scanning, aggregating, sampling, mining, hoarding, searching, sorting, assembling, recombining, and heaping (among other things). Throughout the course, students will explore current theories, relevant historical genealogies, and cases studies of recent practices, and they will engage in workshops on relevant computational techniques. A final project will ask students to produce and evaluate their own assemblages, heaps, and aggregations. 

Theory. A theoretical basis will be provided from (1) thing theory and speculative realism; (2) big data and digital preservation; (3) critical algorithm studies; and (3) classics of avant-garde experimentation, medium specificity, and post-structuralism. History. Students will learn about the history of architectural collecting, dada assemblages, algorithmics and organization theory, the computational turn in abstract art and formalist architecture in the mid-twentieth century, and the more recent digital and post-digital culture in architecture. These topics will be situated in their cultural contexts of global architectural practices. Practice. Techniques will be presented beginning with early-twentieth century formalism, proceeding through mid-century serial/algorithmic art, and into contemporary workflows involving programming and software. Unusual data and algorithms will be sought out and treated as found objects for architectural design. These databases of elements may be digital or physical; algorithmic techniques may be computational or analog. Computational hardware matters less than the mindset involved. 

Class sessions will feature presentations by the instructor, group case study presentations, tutorials of design techniques using databases and algorithms, and guided discussions. The case study may be either an in-depth presentation of a technique or project and its context OR a re-enactment of a design technique using digital methods. The final project will be a design project (in the form of a proposal for a building, space, or sculpture) based on techniques learned through the semester, which will be accompanied by a report presenting its historical precedents, theoretical context, and design rationale.