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Social Injustice in Surveillance Capitalism
Surveillance & Society ( IF 1.6 ) Pub Date : 2017-12-05 , DOI: 10.24908/ss.v15i5.6433
Jonathan Cinnamon

A rapidly accelerating phase of capitalism based on asymmetrical personal data accumulation poses significant concerns for democratic societies, yet the concepts used to understand and challenge practices of dataveillance are insufficient or poorly elaborated. Against a backdrop of growing corporate power enabled by legal lethargy and the secrecy of the personal data industry, this paper makes explicit how the practices inherent to what Shoshana Zuboff calls ‘surveillance capitalism’ are threats to social justice, based on the normative principle that they prevent parity of participation in social life. This paper draws on Nancy Fraser’s theory of ‘abnormal justice’ to characterize the separation of people from their personal data and its accumulation by corporations as an economic injustice of maldistribution. This initial injustice is also the key mechanism by which further opaque but significant forms of injustice are enabled in surveillance capitalism—sociocultural misrecognition which occurs when personal data are algorithmically processed and subject to categorization, and political misrepresentation which renders people democratically voiceless, unable to challenge misuses of their data. In situating corporate dataveillance practices as a threat to social justice, this paper calls for more explicit conceptual development of the social harms of asymmetrical personal data accumulation and analytics, and more hopefully, attention to the requirements needed to recast personal data as an agent of equality rather than oppression.

中文翻译:

监视资本主义中的社会不公

基于不对称个人数据积累的资本主义快速加速阶段引起了民主社会的极大关注,但是用于理解和挑战数据监视实践的概念却不足或阐述不充分。在法律嗜睡和个人数据行业保密的推动下,企业实力不断增强的背景下,本文基于规范性原则,明确阐明了Shoshana Zuboff所谓的“监视资本主义”所固有的实践对社会正义的威胁。防止平等参与社会生活。本文借鉴南希·弗雷泽(Nancy Fraser)的“反常正义”理论,将人们与个人数据的分离以及企业对个人数据的收集描述为分配不当的经济不公。这种最初的不公正现象也是在监视资本主义中进一步使不透明但重要形式的不公正现象成为可能的关键机制:社会文化误认是在对个人数据进行算法处理并进行归类时发生的,政治失实则使人们民主地变得清白,无法挑战滥用其数据。在将公司数据监视实践视为对社会正义的威胁时,本文呼吁对非对称个人数据积累和分析的社会危害进行更明确的概念发展,更希望的是,关注将个人数据重铸为平等代理人所需的要求而不是压迫。
更新日期:2017-12-05
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