"Ethical Review to Support Responsible AI in Policing - A Preliminary Study of West Midlands Police's Specialist Data Ethics Review Committee "

“支持警务中负责任的人工智能的道德审查——西米德兰兹郡警察专家数据道德审查委员会的初步研究”

基本信息

  • 批准号:
    AH/Z505626/1
  • 负责人:
  • 金额:
    $ 29.95万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2024
  • 资助国家:
    英国
  • 起止时间:
    2024 至 无数据
  • 项目状态:
    未结题

项目摘要

The deployment of AI and emerging technologies by the police, while promising more effective use of data for the prevention and detection of crime, brings with it considerable threats of disproportionality and interference with fundamental rights. The West Midlands Police and Crime Commissioner and West Midlands Police data ethics committee aims to bridge the gap between ethical reflection, scientific rigour and a focus on human rights, thus contributing to responsible AI in policing. Democratic legitimacy and public trust around West Midlands Police's use of AI is partly dependent on the ethics governance in place and the public assurances that are made. To avoid any risks of undermining legitimacy and public trust, research can help us understand if the role of the committee is delivering on the assurances being given, as we set out below.This project brings together a diverse team of researchers in Law, Computer Science, Social Innovation, and Policing, with extensive experience of theory and practice of real-world ethical approaches in sensitive contexts. The partnership with West Midlands Police and Crime Commissioner (WMPCC) presents a unique opportunity to analyse operationalisation of AI tools in policing, and the impacts of advice from its data ethics committee. A specific focus is on effects on human rights of marginalised groups, and on deploying an intersectional lens to investigate the impacts of policing AI. The project is designed to address six specific research challenges via four work packages. We will investigate the influence of the data ethics committee upon technology design, identification of human rights concerns and the incorporation of the interests of marginalised groups. We will consider the potential of other frameworks to improve the process, and the challenges that could shape future research. Our methodology will Review, Observe, Understand and Communicate. The outcomes will not only reveal currently unknown and unqualified practices, but will employ state of art analytical methods and thus serve as a valuable test of their fitness to purpose. The project does not address ethics in the abstract, but is grounded in the real challenges of real applications of AI tools in policing. We will focus not only on outcomes but also on processes which may generate trust or fairness by exercising and displaying good governance, and by continually looking, learning, changing and improving.A key output will be an evidence-based typology, which will have wide-ranging implications across policing. Dissemination of all results across the whole policing ecosystem will be possible through the diverse research networks of the project team, which include regulatory bodies.Our team is experienced in integrated interdisciplinary research. We combine the expertise in law, computer science, criminal justice, social innovation and participatory methodology needed to ensure that the research is robust, insightful and impactful. This project is deliberately ambitious and will prepare the groundwork for a full demonstrator project on responsible AI in policing and sensitive contexts.
警方部署人工智能和新兴技术,虽然有望更有效地利用数据来预防和侦查犯罪,但也带来了相当大的非法性威胁和对基本权利的干涉。西米德兰兹郡警察和犯罪专员以及西米德兰兹郡警察数据伦理委员会旨在弥合道德反思、科学严谨性和对人权的关注之间的差距,从而促进警务中负责任的人工智能。西米德兰兹郡警方使用人工智能的民主合法性和公众信任在一定程度上取决于现有的道德治理和公众保证。为了避免任何破坏合法性和公众信任的风险,研究可以帮助我们了解委员会的作用是否兑现了所给予的保证,如下所述。该项目汇集了法律,计算机科学,社会创新和警务的多元化研究人员团队,他们在敏感背景下的现实世界伦理方法的理论和实践方面拥有丰富的经验。与西米德兰兹郡警察和犯罪专员(WMPCC)的合作提供了一个独特的机会,可以分析人工智能工具在警务中的运作,以及其数据道德委员会建议的影响。一个具体的重点是对边缘化群体人权的影响,以及部署一个交叉透镜来调查人工智能警务的影响。该项目旨在通过四个工作包解决六个具体的研究挑战。我们将调查数据伦理委员会对技术设计,人权问题的识别和边缘化群体的利益纳入的影响。我们将考虑其他框架的潜力,以改善这一过程,以及可能塑造未来研究的挑战。我们的方法将审查,观察,理解和沟通。其结果不仅将揭示目前未知和不合格的做法,而且将采用最先进的分析方法,从而作为对其适用性的有价值的测试。该项目并没有抽象地解决道德问题,而是基于人工智能工具在警务中真实的应用所面临的真实的挑战。我们将不仅关注结果,而且关注通过实施和展示良好治理,以及通过不断观察、学习、改变和改进,可能产生信任或公平的过程。一个关键的产出将是以证据为基础的类型学,这将对整个警务工作产生广泛的影响。通过项目团队包括监管机构在内的各种研究网络,可以在整个警务生态系统中传播所有成果。我们的团队在综合跨学科研究方面经验丰富。我们联合收割机结合法律,计算机科学,刑事司法,社会创新和参与式方法所需的专业知识,以确保研究是强大的,有见地和有影响力的。该项目雄心勃勃,将为警务和敏感环境中负责任的人工智能的全面示范项目奠定基础。

项目成果

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专利数量(0)

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Marion Oswald其他文献

Membrane computing and brain modelling
  • DOI:
    10.1007/s10015-008-0619-0
  • 发表时间:
    2009-03
  • 期刊:
  • 影响因子:
    0.9
  • 作者:
    Marion Oswald
  • 通讯作者:
    Marion Oswald
P systems with local graph productions
  • DOI:
    10.1007/bf03037287
  • 发表时间:
    2004-12-01
  • 期刊:
  • 影响因子:
    2.800
  • 作者:
    Rudolf Freund;Marion Oswald
  • 通讯作者:
    Marion Oswald
Independent agents in a globalized world modelled by tissue P systems
  • DOI:
    10.1007/s10015-007-0424-1
  • 发表时间:
    2007-07
  • 期刊:
  • 影响因子:
    0.9
  • 作者:
    Marion Oswald
  • 通讯作者:
    Marion Oswald
Array Insertion and Deletion P Systems
数组插入和删除 P 系统
  • DOI:
    10.1007/978-3-642-39074-6_8
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    H. Fernau;R. Freund;Sergiu Ivanov;Marion Oswald;Markus L. Schmid;K. Subramanian
  • 通讯作者:
    K. Subramanian
Exploring Police Perspectives on Algorithmic Transparency: A Qualitative Analysis of Police Interviews in the UK
探索警方对算法透明度的看法:英国警方访谈的定性分析

Marion Oswald的其他文献

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{{ truncateString('Marion Oswald', 18)}}的其他基金

Observatory for Monitoring Data-Driven Approaches to Covid-19 ("OMDDAC")
Covid-19 数据驱动方法监测观察站(“OMDDAC”)
  • 批准号:
    AH/V012789/1
  • 财政年份:
    2020
  • 资助金额:
    $ 29.95万
  • 项目类别:
    Research Grant

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