The sky has always represented a territory of uncertainty, a zone of limited human influence. Once, we rationalised this uncertainty through mythic thinking. Early cosmological diagrams and post-Enlightenment meteorological instruments were an attempt to measure and order the uncertain. In 1946, the ENIAC computer ran the first ever single day’s weather forecast. ENIAC ‘proved’ that it was not merely possible to predict the weather, but also to rationalise uncertainty through computation. At each layer of the sky, computation has attempted to eradicate uncertainty, replacing mythic with technical thinking: a new form of deriving meaning.
In information theory, ‘noise’ is an index of unpredictability, the term given to the difference between a predicted and observed outcome. The project takes the form of a quasi-scientific ‘investigation’ which attempts to measure this innate unmeasurable aspect of the world: ‘noise’.
Rather than measuring the sky, the investigation attempts to generate meaning from a series of randomly generated computational ‘noise’ maps, employing a process of apophenia: the human tendency to mistakenly perceive meaning between unrelated things. The investigation is described through a series of instruments which calibrate one another, a cyclical loop that at each stage tries to eliminate uncertainty error but ultimately generates distorted ‘views’ of the world that lie between ‘reality’ and myth.
School of Architecture
MA Architecture, 2019
- MA Architecture, University of Cambridge, 2012