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Penn State Develops Algorithm to Assess Substance Abuse Risk in Homeless Youth
Researchers think they’ve come up with a cutting-edge way to predict the likelihood of a given homeless youth running into trouble with substance abuse – and to devise individualized rehab strategies for those who nevertheless develop a disorder.
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.
In New York, A Pointed Debate over Predictive Analytics and Child Welfare
Crunching numbers to help predict human behavior is common practice in insurance, banking, and public policy. We are always looking for the perfect algorithm to help improve decision-making. But when those decisions involve the fate of families, and the potential removal of kids from their parents, data-driven predictions become the subject of intense debate.
Congress Weighs Pilot Program for Predictive Analytics Use in Child Welfare
A new bill introduced by Senator Todd Young (R-Ind.) last month would establish a pilot program to test the use of predictive analytics in identifying and protecting children who are at risk of maltreatment.
Illinois Drops Rapid Safety Feedback, A Predictive Analytics Tool
The Illinois Department of Children and Family Services has ended its use of Rapid Safety Feedback (RSF), a predictive analytics tool that was built in Florida to identify the children reported for maltreatment who are most at risk of serious harm or even death.
Study Suggests Florida Could Use Less Foster Care, More “Light Touch” Help for Families
The number of Florida youth in foster care fell from 29,229 in 2006 to 18,040 in 2013. But the number is on a steady incline again, up to 24,059 as of this summer.
Big Data’s Latest Brainstorm: Target Poor People and Make Parents Suspects If They Ask For Help
Remember the good old days when the one thing almost everyone interested in child welfare could agree on was “home visiting”? Assign a trained worker to help “at-risk” new parents, sometimes even before the child’s birth.
Standard CPS Assessments Dangerously Miss on the Changing Nature of Risk
“Our responsibility is to create foresight about the changing nature of risk before anything goes wrong.” – David Woods
David Woods, one of the pioneers of safety science as applied today in industries such as nuclear power, airlines and health care, offers a critical insight into what continues to be missing from risk and safety analyses in child protective services (CPS).
Rapid Safety Feedback’s Rapid Ascent
In a piece published last week by The Imprint, Casey Family Programs Vice President David Sanders called on federal and state government to “work collaboratively toward realizing our nation’s goal of protecting vulnerable children from abuse and neglect.”
When the Good Guys Ride into the Sunset, Leaving Their Algorithms Behind
The push to embrace “predictive analytics,” an unreliable, racially biased method in which algorithms “inform” the decisions of caseworkers – decisions such as when to tear apart a family – is led largely by the same people who deny the very existence of a racial bias problem in child welfare, want to see far more families torn apart, or both.