论文标题
对“儿童福利工人如何减少算法决定中的种族差异”的扩展分析
Extended Analysis of "How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions"
论文作者
论文摘要
这是对我们的论文“儿童福利工人如何减少算法决策中的种族差异”的扩展分析，该论文着眼于Allegheny家庭筛查工具中的种族差异，用于帮助儿童福利工人决定哪些家庭的算法应调查。 2022年4月27日，阿勒格尼县CYF向我们发送了更新的数据集和预处理步骤。在对论文的扩展分析中，我们通过这些新数据和预处理进行了本文中所有定量分析的重新运行的结果。我们发现，我们论文中的主要发现对数据和预处理的变化具有鲁棒性。特别是，阿勒格尼家庭筛查工具本身将比工人做出更多的种族决定，而工人使用该工具来减少这些算法差异。一些较小的结果发生了变化，包括从前到实施后的筛选率略有提高，报告了我们的论文。
This is an extended analysis of our paper "How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions," which looks at racial disparities in the Allegheny Family Screening Tool, an algorithm used to help child welfare workers decide which families the Allegheny County child welfare agency (CYF) should investigate. On April 27, 2022, Allegheny County CYF sent us an updated dataset and pre-processing steps. In this extended analysis of our paper, we show the results from re-running all quantitative analyses in our paper with this new data and pre-processing. We find that our main findings in our paper were robust to changes in data and pre-processing. Particularly, the Allegheny Family Screening Tool on its own would have made more racially disparate decisions than workers, and workers used the tool to decrease those algorithmic disparities. Some minor results changed, including a slight increase in the screen-in rate from before to after the implementation of the AFST reported our paper.
