Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.684182
Title: Economies of character (or, character in the age of big data)
Author: Rosamond, Emily
ISNI:       0000 0004 5920 3742
Awarding Body: Goldsmiths, University of London
Current Institution: Goldsmiths College (University of London)
Date of Award: 2016
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Abstract:
In the age of big data, character becomes a newly foregrounded object – and product – of scrutiny. New credit scoring methods, which draw on big data analytics, claim to paint rich, nuanced pictures of prospective borrowers’ “true characters.” Micro-entrepreneurs, such as hosts on Airbnb, trade in reputation-images, seeking the best possible ratings and reviews in an online marketplace built on highly visible metrics. Surveillance apparatuses (both governmental and corporate) place ever more emphasis on propensity, analyzing not what a person has done so much as what she might do in future. In doing this, such apparatuses construct, enforce and enact new ways to hold people accountable for their represented, future selves – and to the characters understood to link their present selves to those futures. How might artists best respond to new social and economic pressures placed on character (as a concept governing representations of particularity and propensity) in the age of big data? What can be learned from contemporary art about the new economies of character, given art’s long-standing, privileged relationship to the production and circulation of its artists’ and subjects’ (perceived and represented) “characters”? Examining a wide range of artworks – including some recent works that respond directly to big data, but also many more that, more broadly, anticipate its perceptual politics – I argue that a significant response to such problems can be found in works that disturb the distinction between embedded, first person perspectives and so-called objective, external viewpoints on their subjects. Representations that trouble the distinction between shared and first-person perspectives enact the tension between privacy and sharing that has become increasingly vital to speculative market logics linking character to finance. The shared/private space of the disturbed first-person view lends perceptual logic to the personalization of prediction afforded by big data, and stages contemporary conflicts between privacy and sharing, quantities of data and qualitative perception.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.684182  DOI: Not available
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