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Data algorithms may miss ‘at risk’ children

A new report warns that the use of data algorithms to identify ‘at risk’ children may lead to some being missed entirely and other families being subject to unnecessary scrutiny.

The review of the use of "machine learning" in children’s social care, undertaken by the University of Oxford’s Rees Centre and The Alan Turing Institute for What Works for Children’s Social Care, called for the cautious approach as inaccuracies in these systems could lead to "‘false negatives’ that miss children in need of protection".

The report calls for a national standard for design and implementation of machine learning system to be rolled-out across the UK and for local authorities to work to improve data quality and staff understanding of systems through professional development and training.

Read the report here.