Researchers harness AI to study family involvement with child protection systems
AI-driven research is helping reveal the full picture of families in the child welfare system, paving the way for more comprehensive and compassionate interventions
Traditionally, child welfare research has been narrow in scope, “primarily focused on individual children without fully considering the broader context of family dynamics,” said Eunhye Ahn, an assistant professor at the Brown School. But what if we could study a more complete picture of children involved in the child welfare system to ensure the best possible outcomes for them and their families?
Ahn’s current research project, titled ‘AI for Examining and Predicting Family Involvement with Child Protection Systems,’ aims to develop simulation models that provide invaluable insights into the multifaceted dynamics of families involved in child protection systems. “AI-driven simulation modeling helps us understand various factors and how they interact,” said Ahn, “Such as older siblings’ involvement with the system and their association with the younger child’s experiences.”
With funding from the Digital Transformation priority area of the Here and Next seed grant program, the interdisciplinary team is co-led by Ahn and Yevgeniy Vorobeychik, a professor of computer science and engineering at WashU’s McKelvey School of Engineering. By combining their expertise, the team aims to eventually develop more comprehensive and effective interventions for families and children.
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