Racial Justice Data Change Collaborative: Meeting 3

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In this Racial Justice Data Change Collaborative meeting, participants heard from an exciting lineup of presenters on considerations for machine learning, predictive analytics, and family engagement strategies and accessibility in child welfare. Many states and communities are using or are considering using algorithms for automated decision-making in child welfare, and many more people have questions about them. Dr. Shion Guha, Assistant Professor in the Faculty of Information at University of Toronto talked about human-centered algorithm design in Childe Welfare systems and shared result from current research. Dr. Rhema Vaithianathan, Professor of Social Data Analytics at the Institute for Social Science Research at the University of Queensland, and Dr. Emily Putnam-Hornstein, John A. Tate Distinguished Professor for Children in Need, shared about their work in predictive risk modeling. Joe Homlar, Director, and Jessica Starr, Research, Analysis, & Data Unit Manager, Division of Child Welfare, Colorado Department of Human Services, talked about best practices for data integrity and client engagement.

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