Published in

2022 ACM Conference on Fairness, Accountability, and Transparency, 2022

DOI: 10.1145/3531146.3533155

SAGE Publications, Big Data and Society, 1(10), p. 205395172311710, 2023

DOI: 10.1177/20539517231171053

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Prediction as extraction of discretion

Journal article published in 2023 by Sun-Ha Hong ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
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Published version: policy unknown

Abstract

I argue that prediction is not primarily a technological means for knowing future outcomes, but a social model for extracting and concentrating discretionary power. Prediction is a ‘relational grammar’ that governs this allocation of discretion: the everyday ability to define one's situation. This extractive dynamic extends a long historical pattern, in which new methods for producing knowledge entail a redistribution of decision-making power. I focus on two contemporary domains: (1) crime and policing are emblematic of how predictive systems are extractive by design, with pre-existing interests governing what is measured and what persistently goes unmeasured. (2) The prediction of productivity demonstrates the long tradition of extracting discretion as a means to extract labour power. Time after time, making human behaviour more predictable for the client of prediction (the manager, the police officer) often means making life and work more unpredictable for the target of prediction (the employee, the urban citizen).