Service: Predicting youth problems - Identifying youth problems and providing support

In June 2018, Eksote announced that it had developed, in collaboration with the Finnish IT firm, Avaintec, an AI model to predict problems experienced by children and the youth. The aim was to identify problems early on, so that an intervention could be made and support provided to families sooner rather than later. Much like in the 2019 project on young adults and social exclusion, this model was based on explicitly defined undesired “endpoints”: low-grade averages, disciplinary interventions at school, high-class non-attendance figures, being taken into custody, acceptance into psychiatric care, and substance abuse. The model made use of data gathered from the IT systems of maternity clinics, kindergartens, schools, healthcare, and mental healthcare providers, as well as social services – e.g., it combined data from different administrative branches, namely social care, healthcare, and education. The outcome was the identification of a total of 1340 risk factors, ranging from bad teeth in children, to parents missing maternity clinic appointments, to the child’s siblings bullying others at school. These examples also give an idea of the kinds of data that were employed when making predictions. Ideally, the model would make it possible to continuously keep track of risk factors of individual children.