Document Type

Article

Publication Date

2024

Abstract

Automated traffic enforcement systems disproportionately impact Black communities in the United States. This Essay uncovers a troubling reality: while technologies such as speed cameras and red light cameras are often touted as tools for public safety by the National Highway Safety Transportation Administration, they disproportionately burden Black and Hispanic neighborhoods. The authors coin the term “automated stategraft” to describe this phenomenon—an insidious process that siphons financial resources from already vulnerable groups under the guise of law enforcement. In doing so, it exacerbates economic disparities and erodes trust in legal and governmental institutions.

This Essay delves into the biases inherent in these technologies, particularly in the future of automated traffic enforcement: facial recognition systems. These biases amplify racial and economic injustices, perpetuating inequities. To address this pressing issue, this Essay proposes more just traffic enforcement practices that prioritize community trust and avoid exacerbating racial disparities. It advocates for a critical reevaluation of existing practices, emphasizing equity, justice, and community well-being over financial gain or excessive surveillance. This call to action underscores the urgent need to safeguard public interests in an era marked by increasing surveillance, ensuring that technological advancements in law enforcement serve to protect—rather than oppress—marginalized communities.

Publication Title

Wisconsin Law Review

Volume

2024

Issue

2

First Page

665

Last Page

706

Keywords

Automated traffic enforcement, bias

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