On Wednesday, June 5, AEI hosted the panel Big data, little kids: How technology is changing child welfare to inform participants about the lagging technology used in the child welfare system and present some ways to utilize technology to make the system more effective. The panel consisted of Thea Ramirez, Founder and CEO of Adoption-Share; Gian Gonzaga, senior consultant of research and data analytics at Adoption-Share; Emily Putnam-Hornstein, the director of the Children’s Data Network; and Rhema Vaithianathan, co-director of the Centre for Social Data Analytics.

Thea discussed the mission of Adoption-Share: to help connect families who want to adopt foster youth with children that will successfully be supported by the family. Currently, there is a problem with matching potential families with children given the child-centric approach to finding permanency. Gian then explained the algorithm for Adoption-Share utilizes centralized data showing what makes families successful, such as attributes of the child and the family, the family situation, and match compatibility. Adoption-Share can then screen for “dealbreakers” in the families and children, score compatibility, and optimize solutions for all children, especially those who have fewer ideal match situations. Thea continued by discussing their pilots of Adoption-Share in Virginia and Florida and the successful placements that have been made. Based off of the pilots, Thea looks forward hopefully that solving the connection problem is possible.

Rhema discussed problems faced by screening CPS calls and the need for a way to make screening more effective. She conducted a study in Allegheny County Pennsylvania, where there is an integrated data system that allows for an algorithm to determine the likelihood that a child referral will be in a foster home placement in 2 years. At the end of the study, no adverse effects were found in using the algorithm, there were moderate increases the accuracy of screening in calls, and there was a reduced racial disparities in case openings.

Emily described what implication of a program like this in California has looked like in the last two years, where there is not an integrated data system. Using the data they did have, they created a decile system based on the probability of system involvement. The panel discussed some barriers to using new innovations, such as agencies having a fear of using new technology that could fail, current monopolies of technology in the field, distrust of the current system and therefore distrust in technology based off of the data collected by the system, and the need for these systems to make social workers’ jobs easier to incentivize their use. With the passage of the Family First Prevention Services Act, there is potential that further technology could be used to determine the risk of foster care for children and to determine their eligibility for services.