Green, Harriet (2024) Consciousness over Code: How Judicial Review can Address Algorithmic Decision-Making in Policing. York Law Review, 5.
Abstract
Algorithmic decision-making (ADM) systems have the potential to improve operational efficiency in policing by streamlining decision-making, swiftly analysing intelligence, and maximising the effective allocation of resources. However, integration of these systems into the discretionary decision-making process raises concerns regarding their compatibility with lawful decision-making practices. Discretionary decision-makers must exercise their statutory powers themselves, 1 and integrating an ADM system (ADMS) into the discretionary decisionmaking process risks potential interference with human discretion.2 Currently, there is no legal framework that specifically governs the use and regulation of ADMS.3 This article explores how the courts could step in to help embed high standards and issue guidance so that police discretionary decision-makers may use these systems lawfully. It examines how the courts, through judicial review, could apply the non-fettering and non-delegation principles to shape the legal framework for ADMS use in policing contexts in England and Wales. It critically applies these principles to real-life examples of police using ADMS in discretionary decisionmaking contexts to investigate how these principles can be adapted to guide lawful machineassisted decision-making. The article concludes that the application of these principles reveals important questions for the courts to address, including: if, and how, machines can occupy an advisory role, how human decision-makers can evidence independent judgement when using ADMS, the impact of bias in ADM processes, how ADM outcomes can be interpreted, and how strictly ADM outcomes may be applied.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > The York Law School |
Depositing User: | Repository Administrator York |
Date Deposited: | 26 Feb 2025 15:08 |
Last Modified: | 26 Feb 2025 16:17 |
Status: | Published |
Publisher: | University of York |
Identification Number: | 10.15124/yao-pj4b-em40 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:223827 |