HHS wants states to use more predictive analytics in child welfare
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By
Natalie Alms
The artificial intelligence push is part of the Trump administration’s agenda to modernize the child welfare system and address the shortage of foster homes across the U.S.
The Department of Health and Human Services is offering state child welfare agencies $6 million to pilot predictive analytics to assess children's risk of abuse and neglect in the child welfare system, the Administration for Children and Families announced last week.
The artificial intelligence push is part of the Trump administration’s agenda to modernize the child welfare system and address the shortage of foster homes across the U.S. Although the hope is that the tools improve decisionmaking in the system, they’ve also been the subject of critiques about surveillance and bias.
ACF says that predictive analytics can help agencies identify low-risk families that don’t need to be in the welfare system, as well as high-risk cases that need more immediate attention, in the hopes of improving the ratio of foster homes to children.
Although some child welfare agencies have already begun using more data tools and predictive analytics in their work, many still depend on assessment tools to calculate a child’s risk of abuse and neglect by walking employees through a standard set of weighted questions. The process can be prone to error and bias.
The hope is that predictive risk models can help analyze the full administrative records in child welfare case management systems, update in real time and be trained locally — but these models can also introduce bias, too.
In 2023, The Justice Department was reportedly scrutinizing one early adopter of AI in child welfare — Allegheny County, Pennsylvania — after the Associated Press in 2022 found potential issues with bias and transparency in the tool. The county said at the time that evidence suggested that the tool had actually reduced racial disparities in screening decisions and that staff make ultimate decisions.
Others have raised concerns about the potential for surveillance with these tools.
The potential benefits to modernizing risk assessment practices with more data outweigh the risks, says an internal ACF report. The tools aren’t, however, a substitute for a strong workforce, the same report cautions. They require feedback loops to ensure that they work and transparency into how they work.
“This is a tool. It can be useful,” said Linda Spears, president and CEO of the Child Welfare League of America, a membership-based child welfare coalition. Spears added, however, “it will not fix all of the things that contribute to poor decisionmaking,” especially as the field is suffering from an ongoing workforce crisis.