From Making Automated Decision Making Visible to Mapping the Unknowable Human: Counter-Mapping Automated Decision Making in Social Services in Australia

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Sleep, Lyndal Naomi
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2022
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Abstract

Automated decision-making (ADM) technologies, like artificial intelligence and machine learning, are increasingly being used by governments. Researchers have attempted to map the deployment of these technologies. However, mapping is an inherently political act, reinforcing dominant discourses and imaginings of technological futures. In this article, I engage with critical cartography to outline the potential of counter-mapping for researching automation in decision making, with the purpose of mapping, to quote from Hodgson and Schroeder in 2002, “against dominant power structures, to further seemingly progressive goals.” Drawing on the case of ADM in Australian social services, I reflexively account for how counter-mapping can provide a method for moving beyond dominant discourses of efficiency, cost cutting, and industriousness, to allow the alternative voices of service users’ experiences of ADM to be heard. I argue that future ADM mapping needs to focus on making visible those who are subject to the decisions of automated systems, but are usually made unknowable by the over-confident calculability of dominant ADM discourses.

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Qualitative Inquiry

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28

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7

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This publication has been entered as an advanced online version in Griffith Research Online.

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Social work

Social Sciences

Social Sciences, Interdisciplinary

Social Sciences - Other Topics

counter-mapping

automated decision making

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Sleep, LN, From Making Automated Decision Making Visible to Mapping the Unknowable Human: Counter-Mapping Automated Decision Making in Social Services in Australia, Qualitative Inquiry, 2022, 28 (7), pp. 848-858

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