Responsible AI in policing

Webb, Helena; Fitzroy-Dale, Nicholas; Aqeel, Saamiya; Piskopani, Anna-Maria; Stafford-Fraser, Quentin; Dowthwaite, Liz; McAuley, Derek; Hargreaves, Christopher

Abstract

The deployment of AI-driven technologies in policing is often welcomed as an opportunity to enhance efficiency in dealing with crime. At the same time, however, these technologies pose risks around data bias, data protection, accuracy and privacy. In addition, socio-organisational factors present challenges to their deployment. In this short paper we provide an overview of the opportunities and risks associated with AI in policing, focusing on current developments in the UK. We discuss what is necessary for a responsible approach to deployment and highlight some of our own project work in this context. The Trustworthy and Useful Tools for Mobile Phone Extraction project shows that tools for the analysis of mobile phone data can include AI-driven features that are both useful and trustworthy. However, tools alone cannot address all the tensions and constraints that police work under. Therefore, an essential component of responsibility is to avoid overstating what AI can achieve.

Citation

Webb, H., Fitzroy-Dale, N., Aqeel, S., Piskopani, A.-M., Stafford-Fraser, Q., Dowthwaite, L., McAuley, D., & Hargreaves, C. (2024, September). Responsible AI in policing. Presented at Second International Symposium on Trustworthy Autonomous Systems (TAS '24), Austin, Texas, USA

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Second International Symposium on Trustworthy Autonomous Systems (TAS '24)
• Start Date: Sep 16, 2024
• End Date: Sep 18, 2024
• Acceptance Date: Aug 15, 2024
• Online Publication Date: Sep 16, 2024
• Publication Date: Sep 16, 2024
• Deposit Date: Sep 17, 2024
• Publicly Available Date: Sep 24, 2024
• Publisher: Association for Computing Machinery (ACM)
• Peer Reviewed: Peer Reviewed
• Issue: 35
• Pages: 1-5
• Book Title: TAS '24: Proceedings of the Second International Symposium on Trustworthy Autonomous Systems
• ISBN: 9798400709890
• DOI: https://doi.org/10.1145/3686038.3686070
• Public URL: https://nottingham-repository.worktribe.com/output/39720101
• Publisher URL: https://dl.acm.org/doi/10.1145/3686038.3686070