Triaging online child abuse material: testing a decision support tool to enhance law enforcement and investigative prioritisation

Abstract

PurposeOnline production and transmission of child abuse material (CAM) is a complex and growing global problem. The exponential increase in the volume of CyberTips of CAM offending is placing information processing and decision-making strains on law enforcement. This paper presents the outcomes of a project that reviewed an existing risk assessment tool and then developed a new tool for CAM triaging and investigative prioritisation.Design/methodology/approachUsing a mixed method approach, the authors first explored the capacity of an existing risk assessment tool for predicting a police action. The authors then used these findings to design and implement a replacement CAM decision support tool. Using a random sample of CyberTip alert cases from 2018, the authors then tested the efficiency of the new tool.FindingsThe existing risk assessment tool was not fit for CAM triaging purposes. Just six questions from the old tool were found to be statistically and significantly associated with law enforcement agents achieving a police action. The authors found that an immediate threat of abuse/endangering a child, potential case solvability, CAM image assessment, chat assessment, criticality and some weighting for professional judgement were significant in being associated with a police action. The new decision support tool is more efficient to complete and achieved a 93.6% convergence of risk ratings with the old tool using 2018 case data.Originality/valueThis research is unique in its development of an evidence-based decision support tool that enhances the ability of law enforcement agents to objectively and efficiently triage and prioritise increasing numbers of CyberTip alerts.

The Algorithmic Moderation of Sexual Expression: Pornhub, Payment Processors and Csam

“…Human moderators remain essential, but workers lack appropriate training or resources to manage traumatising content (Mount et al 2021). Best practices in CSAM reduction require robust structural support focused on prevention, education and legal interventions, generally not offered by employers seeking cost-cutting efficiency through the promise of automation (Kloess et al 2019;.…”

Guest editorial

“…These tools improve departments' return on investment from investigations by prioritizing cases for investigation that are more likely to result in a positive outcome. In the first study, Mount et al . (2021) present the results of a study they conducted with the Australian Federal Police to develop a better assessment tool for prioritizing child abuse material tips for investigation.…”

“…Although detectives must work hard to investigate every crime they can, and law enforcement agencies must problem solve when resources are limited, for some offenses, departments receive too many tips and crime reports to thoroughly investigate. In these instances, the research conducted by Mount and colleagues (2021) and McFadzien and Sherman (2021) provides important guidance to law enforcement about how to work with scientists to develop assessment tools to guide agency decision-making.…”

“…These tools improve departments' return on investment from investigations by prioritizing cases for investigation that are more likely to result in a positive outcome. In the first study, Mount et al (2021) present the results of a study they conducted with the Australian Federal Police to develop a better assessment tool for prioritizing child abuse material tips for investigation. Similarly, in the next study, McFadzien and Sherman (2021) describe the effectiveness of an assessment tool that they developed with the Kent Police to prioritize more solvable minor assault and public order crimes for investigation.…”