predictive risk modeling

As Los Angeles County becomes the latest child welfare system to turn to big data and algorithms, critics worry these tools will exacerbate inequalities.

The idea of using predictive analytics in child welfare easily conjures images of child abuse investigators targeting parents a machine deems most likely to harm their children. Because black families are so disproportionately likely to be involved with the child protection system, critics credibly argue that predictive risk modeling will only exacerbate existing racial bias.

In the race to dominate the child abuse prediction market, the world’s largest data analytics firm has its eye on what it calls “perpetrator” networks. SAS, with a global workforce of 14,000 and $3.16 billion in revenue in 2015, delivered Florida’s Department of Children and Families a lengthy technical report in August of last year.