Malgorzata Starzynska

Ever since Brunelleschi used mathematical perspective to translate space into its subdimensional representation, the western ocular experience has been expanding upon this visual concept. But what seemed to have been a consistent development of the dominant Florentian paradigm has now come to a halt. In today’s digital era modes of visual perception are shifting and subsequently changing the way reality is observed. In the words of the Italian philosopher Matteo Pasquinelli, twenty-first-century visual perception no longer belongs to the observer. Attention is replaced by a selective filter, vision by pattern recognition and anomaly detection. In today’s algorithmic reality, perception is no longer an anthropocentric domain.

The current abundance of Big Data will make machine learning an inevitable part of the design process, however, this new algorithmic vision offers more than just an opportunity for generative design. It opens up an opportunity for a fully integrated methodology where artificial neural networks, if appreciated for their perceptual capability, can contribute to the critical analysis of contemporary culture.

The quantity of data has resulted in the unavoidable: a crisis of representation. It will be impossible to address this problem until the need for “new epistemic eye” has been resolved. The proposal aspires to develop an alternative cognitive perspective for this new digital landscape. Informed by works of theoreticians and philosophers concerned with cybernetics and technosphere as well as the theory of semiotics, this project focuses on a tangible proposition; spaces generated by a self-taught AI.

Machine learning will be considered as a tool as well as a vehicle for the critique. A trained algorithm will classify digital models of architectural spaces by looking for pattern commonalities. After classification, the network will be “reversed” to produce generative designs that reflect the learning mechanism behind classification. This process will be based around the premise of second-order cybernetics, where the observer is observing a system in which he himself is participating. In this process, architectural space will become conceptualised into its pure, mathematical form; an abstraction of data. This digital experience of reality will then be examined in an effort to identify the differences between the traditional reading of architectural form and emerging patterns identified by a cognitive algorithm.