论文标题
改善儿童福利中的人类伙伴关系：了解工人实践，挑战和对算法的决策支持
Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support
论文作者
论文摘要
基于AI的决策支持工具（AD）越来越多地用于增强在高风险和社会环境中的人类决策。随着公共部门机构开始采用广告，至关重要的是，我们在实践中了解工人对这些系统的经验。在本文中，我们从儿童福利机构的一系列访谈和上下文查询中介绍了发现，以了解他们目前如何做出AI辅助儿童虐待筛查决定。 Overall, we observe how workers' reliance upon the ADS is guided by (1) their knowledge of rich, contextual information beyond what the AI model captures, (2) their beliefs about the ADS's capabilities and limitations relative to their own, (3) organizational pressures and incentives around the use of the ADS, and (4) awareness of misalignments between algorithmic predictions and their own decision-making objectives.根据这些发现，我们讨论了支持更有效的人类AI决策的设计含义。
AI-based decision support tools (ADS) are increasingly used to augment human decision-making in high-stakes, social contexts. As public sector agencies begin to adopt ADS, it is critical that we understand workers' experiences with these systems in practice. In this paper, we present findings from a series of interviews and contextual inquiries at a child welfare agency, to understand how they currently make AI-assisted child maltreatment screening decisions. Overall, we observe how workers' reliance upon the ADS is guided by (1) their knowledge of rich, contextual information beyond what the AI model captures, (2) their beliefs about the ADS's capabilities and limitations relative to their own, (3) organizational pressures and incentives around the use of the ADS, and (4) awareness of misalignments between algorithmic predictions and their own decision-making objectives. Drawing upon these findings, we discuss design implications towards supporting more effective human-AI decision-making.
