Calculative Environments: Audrey Samson
Audrey Samson, The Predictive Gaze
In the face of looming environmental catastrophe, practices of nature conservation, preservation and ecological restoration are increasingly using new systems of measurement and prediction. Each session will consider how such instruments - through competing logics of preservation, conservation, value, and profit - actively shape the environments they seek to protect, with required reading being given out in advance. By reading and discussing the subtleties of how these systems and technologies work, we will work through a range of problems in how everyday distinctions are drawn between nature and culture, human and animal, living and inert. Join discussions and read about issues of biodiversity, extinction, computation, and ecological finance.
In this session, through a close reading of Adrian Mackenzie’s, The Production of Prediction: What Does Machine Learning Want?, we carefully consider how modes of generalisation in machine learning operate to infer predictive values. We also explore how notions of systematisation, standardisation and categorisation, which compose the infrastructural conditions of machine learning, are applied to ‘nature’, specifically with regards to the boreal forest.
Free.
Due to the limited capacity for this session booking is essential. To book please email Mercè at merce@nottinghamcontemporary.org
The current season is programmed by Theo Reeves-Evison, Birmingham City University.
Audrey Samson is Head of the Digital Arts Computing BSc and a lecturer in Fine Arts (Critical Studies) in the Art Department at Goldsmiths, University of London. Resident at the Somerset House Studios, she is a critical technical practitioner in the métis duo FRAUD, which develops forms of art-led inquiry into modes of governmentality and power that flow through physical and cultural spaces, and their entanglements with networked technical objects.
Event:
Calculative Environments: Audrey SamsonDates:
12 Mar 2019, 6.30pm–8.30pmCurator:
Theo Reeves-Evison
Supported by:
