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arXiv · 2401.06162

A debiasing technique for place-based algorithmic patrol management

Alexander Einarsson·Simen Oestmo·Lester Wollman·Duncan Purves·Ryan Jenkins
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Abstract

In recent years, there has been a revolution in data-driven policing. With that has come scrutiny on how bias in historical data affects algorithmic decision making. In this exploratory work, we introduce a debiasing technique for place-based algorithmic patrol management systems. We show that the technique efficiently eliminates racially biased features while retaining high accuracy in the models. Finally, we provide a lengthy list of potential future research in the realm of fairness and data-driven policing which this work uncovered.

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Alexander Einarsson, Simen Oestmo, Lester Wollman, Duncan Purves, Ryan Jenkins. 2023-12-22. A debiasing technique for place-based algorithmic patrol management. https://arxiv.org/abs/2401.06162

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