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‘Assisted’ facial recognition and the reinvention of suspicion and discretion in digital policing
[‘Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification’]

Author

Listed:
  • Pete Fussey
  • Bethan Davies
  • Martin Innes

Abstract

Automated facial recognition (AFR) has emerged as one of the most controversial policing innovations of recent years. Drawing on empirical data collected during the United Kingdom’s two major police trials of AFR deployments—and building on insights from the sociology of policing, surveillance studies and science and technology studies—this article advances several arguments. Tracing a lineage from early sociologies of policing that accented the importance of police discretion and suspicion formation, the analysis illuminates how technological capability is conditioned by police discretion, but police discretion itself is also contingent on affordances brought by the operational and technical environment. These, in turn, frame and ‘legitimate’ subjects of a reinvented and digitally mediated ‘bureaucratic suspicion’.

Suggested Citation

  • Pete Fussey & Bethan Davies & Martin Innes, 2021. "‘Assisted’ facial recognition and the reinvention of suspicion and discretion in digital policing [‘Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification’]," The British Journal of Criminology, Centre for Crime and Justice Studies, vol. 61(2), pages 325-344.
  • Handle: RePEc:oup:crimin:v:61:y:2021:i:2:p:325-344.
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    File URL: http://hdl.handle.net/10.1093/bjc/azaa068
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    Cited by:

    1. Nessa Lynch, 2024. "Facial Recognition Technology in Policing and Security—Case Studies in Regulation," Laws, MDPI, vol. 13(3), pages 1-14, June.

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