The Youth Justice Service in Hillingdon is one of London’s most innovative services, a multi-agency service dedicated to supporting young people caught in the criminal justice system. Trilateral collaborated with Hillington Youth Justice Service as a result of our work with Avon and Somerset Office for Data Analytics. Here we worked to enhance their data mapping tools for their award-winning AXIS project that focused on early identification of young people at risk of criminal exploitation.
Our goal was to create advanced tools to draw actionable insights out of a large amount of data to enable the development of positive interventions to support young people at a crossroads in their lives.
Effective intervention by local services depends on talking to the right people at the right time. The AXIS project at the Youth Justice Service adopted an innovative approach by gathering and collating data to identify young people in Hillingdon at risk of being exposed to drug dealing, youth violence, child sexual exploitation or going missing from home or care.
However, a successful approach relied on effective distribution of resources: knowing where and when to deploy the agency effort is crucial.
Large datasets can become too overwhelming, new technologies can enable the correlation of dispersing data to gain crucial insights to support evidence-based intervention measures.
Trilateral enriched the available datasets in the project and supported the management of big data assets by using STRIAD® methodologies, including advanced data mapping and visualisation tools. This added more granularity and depth to the data analytics and improved data-driven decision making regarding designing positive interventions. Our contribution focused on three aspects of the project:
Our experiences of assessing the ethical impact in the use of AI and new technologies helped us to clearly illustrate how machine learning works and how to recognise risks of bias in data, thus, achieving transparency in our processes by being able to explain how algorithms make their decisions. Our work in algorithmic transparency has been instrumental in our technology development, for example such approach has led the CESIUM application development and has been leveraged in all STRIAD® Solutions.
The advanced mapping and visualisation tools such as network graphs allow decision-makers to optimise the allocation of resources and enables efficient evidence-based decision making on prevention measures for youth at risk of criminal exploitation. The automated risk labelling component helped data analysts to manage big data assets while keeping the risk of human error low. Enhanced data analytics abilities can contribute to the development and introduction of early safeguarding interventions to support young people in their journey away from criminality.