Title: Spaces That Learn

Description:

Submitted for the Spaces That Learn Competition 2020.

The drawings envision a near future where architecture schools are AI-augmented.

The drawing challenges the methods in production of architectural knowledge and the role of tutors in the current context. In an AI-augmented architecture school, professors and teaching staffs will be required to do double work of teaching people and training AI. The role could entire shift to just training AI, especially for subjects such as History and Theory.

In such a school, learning will be highly interactive. Students and tutors will be able to gain access to high level, curated information in any topics they are curious about in real time feedback loops. If it took past students 5-years to graduate with a vague sense of what architecture is or graduate with some understanding of architectural history, it will take an AI-assisted architecture student, a few days to months to gain a broad overview of popular architectural knowledge. Topics with greatest available data or topics that provoke mass interaction will be the most reinforced knowledge in an AI learning environment. In such an environment, finding messy or obscure bits of information, histories, figures, drawings and concepts will be increasingly challenging. But in the messy bits, real learning and production of new architectural knowledge will take place.