Don’t trust algorithms to predict child-abuse risk

Your are right to highlight councils’ use of data about adults and children without their permission, alongside the warped stereotypes that inevitably shape the way families are categorised (Council algorithms use family data to predict child-abuse risk, 17 September). But the problems are more wide-ranging. In policy debates shaped by the Climbié and Baby P scandals, pre-emptive interventions sound attractive, but ethical debates about what level of intervention in family life, on what basis, and how pre-emptively, still need to take place. Such debates would be necessary with accurate predictions but become absolutely crucial when, as with any risk screening programme, false positives are unavoidable. In a given population where the base rate of abuse is low, these errors will be drastically higher than commonly believed.

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