Machine Learning Predictive Algorithms and the Policing of Future Crimes: Governance and Oversight

M. Oswald, A. Babuta
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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.
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机器学习预测算法和未来犯罪的监管:治理和监督
本章重点介绍英格兰和威尔士警察决策中的机器学习算法,特别是与预测分析有关的算法。它首先回顾了以机器学习为基础的算法工具的实施现状,以帮助警察决策,并指出紧缩政策对此类工具开发的驱动作用。我们讨论了所谓的“紧缩人工智能”如何经常与警察的预防和公共保护普通法职责和职能联系在一起,这是一个广泛而不精确的法律基础,欧洲人权法院在Catt中发现这一点并不令人满意。然后考虑这些工具对在警务中适当运用自由裁量权的潜在影响,以及它们对个人权利的潜在影响。最后,对现有的和建议的治理和监督流程(包括旨在促进新兴技术试验的流程)进行了审查,并提出了对警务职能和职责进行法定澄清的建议,从而提供了一个更清晰的框架,可以根据该框架评估新人工智能发展的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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