Machine learning predictive algorithms and the policing of future crimes: governance and oversight

Alexander Babuta, Marion Oswald

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)

Abstract

This chapter focuses upon machine learning algorithms within police decision-making in England and Wales, specifically in relation to predictive analytics. It first reviews the state of the art regarding the implementation of algorithmic tools underpinned by machine learning to aid police decision-making, and notes the impact of austerity as a driver for the development of such tools. We discuss how what could be called ‘Austerity AI’ is often linked to the prevention and public protection common law duties and functions of the police, a broad and imprecise legal base that the ECtHR in Catt found less than satisfactory. The potential implications of these tools for appropriate application of discretion within policing, as well as their potential impact on individual rights are then considered. Finally, existing and recommended governance and oversight processes, including those designed to facilitate trials of emerging technologies, are reviewed, and proposals made for statutory clarification of policing functions and duties, thus providing a clearer framework against which proposals for new AI development can be assessed.
Original languageEnglish
Title of host publicationPredictive Policing and Artificial Intelligence
EditorsJohn L.M. McDaniel, Ken Pease
Place of PublicationLondon
PublisherTaylor & Francis
Chapter8
Pages214-236
Number of pages23
Edition1st
ISBN (Electronic)9780429265365
ISBN (Print)9780367210984
DOIs
Publication statusPublished - 26 Feb 2021

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