Five ethical challenges facing data-driven policing

被引:0
作者
Jeremy Davis
Duncan Purves
Juan Gilbert
Schuyler Sturm
机构
[1] University of Florida,Department of Philosophy
[2] University of Florida,Computer and Information Science and Engineering Department
来源
AI and Ethics | 2022年 / 2卷 / 1期
关键词
Big data; Policing; Algorithms; Bias; Transparency; Accountability;
D O I
10.1007/s43681-021-00105-9
中图分类号
学科分类号
摘要
This paper synthesizes scholarship from several academic disciplines to identify and analyze five major ethical challenges facing data-driven policing. Because the term “data-driven policing” encompasses a broad swath of technologies, we first outline several data-driven policing initiatives currently in use in the United States. We then lay out the five ethical challenges. Certain of these challenges have received considerable attention already, while others have been largely overlooked. In many cases, the challenges have been articulated in the context of related discussions, but their distinctively ethical dimensions have not been explored in much detail. Our goal here is to articulate and clarify these ethical challenges, while also highlighting areas where these issues intersect and overlap. Ultimately, responsible data-driven policing requires collaboration between communities, academics, technology developers, police departments, and policy makers to confront and address these challenges. And as we will see, it may also require critically reexamining the role and value of police in society.
引用
收藏
页码:185 / 198
页数:13
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