The Biases Behind Predictive Algorithms for Child Welfare Tracking




The Takeaway show

Summary: <p>Eleven states in the country are currently using child welfare tracking algorithms to better identify children at risk. According to research conducted by Carnegie Mellon University, the algorithms target a disproportionate number of Black and low-income families. We discuss the implementation of child welfare tracking algorithms with <a href="https://twitter.com/samtheant">Anjana Samant</a>, senior attorney at the ACLU and <a href="https://twitter.com/nicolee_biddle/media">Nico’Lee Biddle</a>, Senior Program Manager at the Center for the Study of Social Policy.</p>