This third-level critical course is designed to initiate, in our Institution, a broad and multidisciplinary discussion on the influence of Artificial Intelligence (AI) in architectural design research and practice. It examines the emergence of AI as a pivotal concept in contemporary architectural design and aims to serve as a playground where various fronts of AI’s impact on the field can be explored and tested. By integrating diverse knowledge, the course promotes a holistic approach that bridges theory and practice, research and application. The main objectives are: - Explore the interactions between AI and architecture; - Stimulate critical discussion on the implications and potential of AI in architecture; - Create a platform for theorists, researchers, and PhD students to exchange knowledge. The course will be structured into thematic modules, each addressing specific questions related to AI in architecture. Key themes include: the architect-machine relationship and the creative process; the ontology and politics of archives; the temporal dynamics of AI and the acceleration-obsolescence duality of AI tools; the levels of competencies required to access and use AI tools; the role of AI in architectural aesthetics; machine learning algorithms and the computational optimization, modeling, simulation, validation processes.

not requested

The course will start and end with a plenary session seminar. The first introductory seminar will present the actual discussion on Artificial Intelligence in Architectural Practice through a dialogue between two theorists: a philosopher and a computer scientist. Afterwards, PhD Candidates will have the chance to explore, through four thematic lectures led by four international guests, the potentialities of artificial intelligence in the architectural fields and test how it may have a transformative impact on their research attitude. Each lecture will be followed by a discussion session to delve into the covered topics. The final seminar will focus on PhD students' contribution to the topic through an exercise that will ask them to position themselves critically through a short essay in relation to the addressed topics. The schematic schedule of the course will be: - Opening Seminar (4 h): Philosopher perspective + Data scientist perspective - Lecture 1 (3,5 h) - Lecture 2 (3,5 h) - Lecture 3 (3,5 h) - Lecture 4 (3,5 h) - Closing Seminar (2 h)

Modalità mista

Presentazione report scritto

P.D.2-2 - Aprile