RUDI: An evidence-based police-centric guide for approaching the development of algorithmic models in policing

Police are increasingly adopting or considering machine learning algorithms (MLAs) to enhance their processes, appealing for their ability to process large volumes of information and predictive capabilities. Lack of national guidance on developing and implementing algorithms means police forge ahead in an exploratory manner. To address this, we developed a practical police-centric framework and guide: RUDI (Rationale, Unification, Development, Implementation), a framework designed to mitigate concerns raised regarding the use of algorithms in policing. This report outlines our work with two police forces to develop RUDI, highlighting the challenges of algorithmic policing and how RUDI can mitigate these concerns.

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Publication Details

Journal
The Police Journal Theory Practice and Principles
Published
2025-08-29
DOI
https://doi.org/10.1177/0032258x251372357
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

RUDI: An evidence-based police-centric guide for approaching the development of algorithmic models in policing

Hazel Sayer, Tamara Polajnar, Ruth Spence
The Police Journal Theory Practice and Principles
Ethics and Social Impacts of AI
article

RUDI: An evidence-based police-centric guide for approaching the development of algorithmic models in policing

Hazel Sayer, Tamara Polajnar, Ruth Spence
article en

Abstract

Police are increasingly adopting or considering machine learning algorithms (MLAs) to enhance their processes, appealing for their ability to process large volumes of information and predictive capabilities. Lack of national guidance on developing and implementing algorithms means police forge ahead in an exploratory manner. To address this, we developed a practical police-centric framework and guide: RUDI (Rationale, Unification, Development, Implementation), a framework designed to mitigate concerns raised regarding the use of algorithms in policing. This report outlines our work with two police forces to develop RUDI, highlighting the challenges of algorithmic policing and how RUDI can mitigate these concerns.

The Police Journal Theory Practice and Principles
Oldham Council (GB), Middlesex University London (GB), Bournemouth University (GB)
Openalex Percentile: Top 77%
Ethics and Social Impacts of AI
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RUDI: An evidence-based police-centric guide for approaching the development of algorithmic models in policing — Hazel Sayer, Tamara Polajnar, et al. · The Police Journal Theory Practice and Principles (2025) | TGRS Research Map | TGRS