Case—Racial Bias in Automated Traffic Law Enforcement and the Price of Unjustness

Chrysafis Vogiatzis () and Eleftheria Kontou ()
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Chrysafis Vogiatzis: Industrial and Enterprise Systems Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801
Eleftheria Kontou: Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801

INFORMS Transactions on Education, 2025, vol. 25, issue 2, 128-135

Abstract: This case study has been developed for students to practice their data analysis and optimization skills in a contemporary societal issue: that of injustice in automated traffic law enforcement. Specifically, this case study is for students of modern data analysis and statistical modeling courses that focus on hypothesis testing; it also has a component for students in optimization and mathematical modeling courses that focus on linear and network optimization. The case study has been used since Spring 2023 in a combination of two courses from the Industrial Engineering (Analysis of Data, an introduction to probability and statistics) and Civil Engineering (Transportation Systems, an introduction to mathematical modeling and optimization for civil engineers with a focus on transportation) curricula.

Keywords: cases; developing critical thinking skills; teaching optimization; teaching statistics; racial bias (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orited:v:25:y:2025:i:2:p:128-135

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