Online child sexual abuse material (CSAM) offending is a challenge for law enforcement, policy-makers and child welfare organisations alike. To address this, the authors of this report use a case study to analyse the actions individuals and organisations within the technology, government, non-government and private sectors could take to implement warning messages.

Predicting the locations and times of elevated crime risk is of great interest to law enforcement agencies around the world. Based on the published literature, the authors of this report suggest there are four conditions required if predictive policing is to be effective.

Remote biometric technologies – in particular, facial recognition – have gained a lot of traction in the security sector in recent years. This report presents a set of proposed principles for the use of facial recognition in law enforcement investigations, along with a self-assessment questionnaire intended to support law enforcement agencies to design policies surrounding...

This report analyses limitations, both technical and implementation, of artificial intelligence (AI) algorithms, and the implications of those limitations on the safe, reliable and ethical use of AI in policing and law enforcement scenarios.

The nature of offending by outlaw motorcycle gangs (OMCGs), and policing responses, requires a novel approach to risk assessment. This study uses machine learning methods to develop a risk assessment tool to predict recorded high-harm offending. Results are compared with those of a model predicting any recorded offending.