The Opposite of Machine Intelligence

Vishmidt, Marina. 2020. The Opposite of Machine Intelligence. In: Dirk Snauwert, ed. Risquons-Tout: Contemporary Artists Venture Into Risk, Unpredictability and Transgression. Brussels: WIELS. ISBN 9780300257694 [Book Section]

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Abstract or Description

This essay looks at the relationship between artistic labour and abstract labour through an examination of the impact of automation on value production. It should be said at the outset that artistic labour is not the primary concern of automation discourses, which have traditionally been focused on labour ‘in general’, and on standardised processes that can be improved (‘rationalised’) through automation. This is not the case with artistic labour, even if the fascination with factory-like production processes is not unknown in the arts – whether plastic, literary, musical or other. That fascination provides a backdrop to our discussion, but is not its focus. Rather, the goal is offer a structural analysis and not a case study, or a brief survey of the different ways in which art has made automation its own. By ‘structural analysis’, I refer to the systematic conditions of social possibility, examined from a mid-range of abstraction, rather than a micro-reading of a particular practice on the one hand, or a macro-level historical account on the other. Recent exhibitions, including this one, as well as discrete practices, have reflected on automation, digital technologies and transformations in labour as topical and also as formal issues for artmaking. Most have done this discursively, while a small number have taken a more mimetic approach. Instead of examining these instances, we want to explore how we can think about how artistic labour mediates the social and economic shifts signalled by certain hegemonic discourses of automation.

Item Type:

Book Section

Keywords:

value, labour, technology, artificial intelligence, art

Departments, Centres and Research Units:

Media, Communications and Cultural Studies

Dates:

DateEvent
12 June 2020Accepted
9 September 2020Published

Item ID:

29603

Date Deposited:

08 Jan 2021 15:28

Last Modified:

29 Jul 2021 08:23

URI:

https://research.gold.ac.uk/id/eprint/29603

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