Ohio Gets $600K Federal Grant to Test AI-Driven Child Welfare Decisions
Ohio is among 10 states across the country to receive federal money to pilot new predictive analytics tools to help make better decisions in child welfare services.
The Administration for Children and Families (ACF) will provide $6 million through grants to Ohio and nine other jurisdictions, each receiving approximately $600,000 for a three-year pilot program that is anticipated to commence September 30.
The project will explore the value of predictive analytics to help child welfare workers make better, quicker decisions that impact children and families. The technology can be applied to evaluate reports from the hotline, to enhance foster care placement, to assist with permanency decisions and/or to streamline caseworker paperwork.
In Ohio, the pilot may be an opportunity to learn how data-driven tools can build on the child welfare system and help caseworkers make decisions about the safety and care of children.
ACF Assistant Secretary Alex Adams emphasised the technology would be used to complement, not replace, professionals’ judgment. Predictive models should fill in the gaps for caseworkers and leave critical decisions to trained professionals, he said.
The federal investment is coming as child welfare agencies are increasingly interested in predictive risk modelling, and as concerns grow about the inaccuracies, algorithmic bias and the impact it can have on families.
The funded jurisdictions will have to develop governance and quality assurance processes, train personnel, involve communities and assess the outcomes of their project.
The pilots will provide feedback on what’s effective and what’s not, which could offer lessons for other child welfare agencies in the United States, ACF said.
The project may be a pivotal moment for Ohio on the issue of how the emerging technology can enhance child protection and ensure children and child wellbeing are the focus of decision-making.
