1. Optimal resource allocation to minimize errors when detecting human trafficking.
- Author
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Ray, Abhishek, Arora, Viplove, Maass, Kayse, and Ventresca, Mario
- Subjects
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HUMAN trafficking , *RESOURCE allocation , *CIVIL rights , *ERROR rates , *OPERATIONAL definitions - Abstract
Accurately detecting human trafficking is particularly challenging due to its covert nature, difficulty in distinguishing trafficking from non-trafficking exploitative conditions, and varying operational definitions. Typically, detecting human trafficking requires resource-intensive efforts from resource-constrained anti-trafficking stakeholders. Such measures may need personnel training or machine learning-based identification technologies that suffer from detection errors. Repeated usage of such measures risks biasing detection efforts and reducing detection effectiveness. Such problems raise the question: "How should imperfect detection resources be allocated to most effectively identify human trafficking?" As an answer, we construct a class of resource allocation models that considers various optimal allocation scenarios. These scenarios range from optimal location selection for monitoring to optimal allocation of a finite set of imperfect resources, given error rates. We illustrate the applicability of these models across both human and technology-facilitated detection contexts at the India–Nepal border and in the global seafood industry. Insights from our models help inform operational strategies for allocating limited anti-human trafficking resources in a way that effectively preserves human rights and dignity. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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