Can Predictive Analytics Root Out the Social Workers Most Likely to Break up Black Families?
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.
Five Lessons for Implementing Predictive Analytics in Child Welfare
Predictive risk modeling (PRM) offers new and exciting chances to solve big, entrenched problems. In child welfare, one of those problems is accurately identifying children at risk of maltreatment, work that requires a gauge of not only immediate risk, but also the future likelihood of harm.
Pennsylvania County Leads in Use of Big Data to Stem Child Abuse, Probes Ethics First
Computer algorithms guide our decisions in big ways and small. They nudge us to buy a particular blender on Amazon and tailor ads to our interests on our Facebook pages, but also seek to reduce repeat domestic violence arrests and assess risk during criminal sentence proceedings.