Fragmented Futures? A Systematic Mapping of Probabilistic AI Tools in Policing Across England and Wales

The rapid adoption of artificial intelligence (AI) tools in policing across England and Wales is a notable development, yet it proceeds without clear national coordination. While the National Police Chiefs’ Council and other key bodies have issued extensive guidance, operational autonomy remains with individual forces. This decentralised approach has resulted in uneven uptake, potential duplication of effort, and varying standards of oversight and ethical practice. This paper presents initial findings from the PROBabLE Futures project, an interdisciplinary initiative that includes a systematic mapping of probabilistic AI tools currently in use by police forces in England and Wales. The mapping covers a wide range of technologies—from predictive policing and facial recognition to data infrastructure and analytics—and categorises them by function, implementation stage, and point of use within the criminal justice process. The primary aim is to provide a coherent and accessible overview of a fragmented and rapidly evolving landscape. Focusing on the methodological and conceptual design of this mapping exercise, the paper explores the challenges of achieving clarity and comparability across diverse, often opaque, AI implementations. It identifies risks associated with decentralised innovation in policing, including inconsistencies in practice, contested evidentiary value (particularly where generative AI is used in high-stakes contexts such as report writing and statement creation), and accountability gaps. Ultimately, the paper argues that systematic mapping can support more structured governance, enable informed public debate, and foster ethically grounded innovation in the criminal justice system.