CYP Now - Machine learning in children’s services: does it work?

What Works for Children’s Social Care worked with four local authorities to develop models to predict eight outcomes for individual cases. The predictions all focused on a point within the children’s journey where the social worker would be making a decision about whether to intervene in a case or not and the level of intervention required, and looked ahead to see whether the case would escalate at a later point.

There are good reasons to be skeptical about the value of any predictive analytics tool currently. Picture: Adobe Stock

Natural language processing techniques were used to turn reports and assessments into information that can be used as input to a model. Machine learning techniques were then used to learn patterns in historical data associated with risks and protective factors, and examine whether those factors were present in unseen cases. The study aimed to understand whether machine learning models, applied in this way, correctly identify the cases at risk of the outcome and those that are not. Four different ways of designing the models were assessed.

About the project:

Practitioners in the four local authorities identified two outcomes to predict for their own authority and in total we predicted eight outcomes:

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