Using a Machine Learning Tool to Support High-Stakes Decisions in Child Protection
While machine learning tools are becoming more widely used to support decisions in social domains, including child welfare, these tools need to be designed in a way that considers the interactions between the tools and humans. In this AI Magazine article the authors argue that human-centred design is key to the successful deployment and impact of machine learning tools. The Allegheny Family Screening Tool (AFST), a decision support tools used in Allegheny County (PA, United States) since 2016 to support child welfare call screening, is used as an example of human-centred design. The authors explain aspects of human-centred design that contributed to its successful deployment, including agency leadership and ownership, transparency by design, ethical oversight, community engagement, and social license. The authors conclude with potential next-steps for human-centred design in the development and implementation of machine learning decision support tools.
Vaithianathan, R., Benavides-Prado, D., Dalton, E., Chouldechova, A., & Putnam-Hornstein, E. (2021). Using a Machine Learning Tool to Support High-Stakes Decisions in Child Protection. AI Magazine, 42(1), 53-60.