New Working Paper: How Algorithms Can Improve Social Services’ Decisions
A new SOFI Working Paper in Labour Economics shows that algorithms, when used as support rather than as a replacement, can improve decision-making within child and family social services.
Authors: Marie-Pascale Grimon (SOFI) och Christopher Mills (University of Notre Dame)
Abstract
Algorithm tools have the potential to improve public service efficiency, but our understanding of how experts use algorithms is limited, and concerns about resulting bias are widespread. We randomize access to algorithm support for workers allocating Child Protective Services (CPS) investigations. Access to the algorithm reduced maltreatment-related hospitalizations, especially for disadvantaged groups, while reducing CPS surveillance of Black children. Child injuries fell by 29 percent. Workers improved their scrutiny of complementary information emphasized by the algorithm, and targeted investigations to children at greater risk of harm irrespective of algorithm-predicted risk. Algorithm-only counterfactuals confirm human-algorithm complementarity for both efficiency and equity.
Labour economics is a very broad research field. In addition to research on labour market outcomes, such as wages and employment, the AME unit studies both elementary and higher education, health, taxes and income transfers, politics, crime and punishment, and gender equality.
