人类参与决策的案例：存在错误评分的决策
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
摘要：
算法预测在敏感领域的使用越来越多，这带来了热情和关注。要了解这些技术的机会和风险，关键是研究专家在使用这些工具时如何改变他们的决策。在本文中，我们研究了采用一种算法工具，用于协助儿童虐待热线筛选决策。我们关注的问题是：人类是否有能力识别机器错误的情况，并推翻这些建议？我们首先表明，人类在部署工具时确实会改变他们的行为。然后，我们表明，当显示的分数是对风险的错误估计时，人类不太可能遵守机器的建议，即使推翻建议需要监督批准。这些结果凸显了完全自动化的风险，以及设计为人类提供自主权的决策管道的重要性。
英文摘要：
The increased use of algorithmic predictions in sensitive domains has been accompanied by both enthusiasm and concern. To understand the opportunities and risks of these technologies, it is key to study how experts alter their decisions when using such tools. In this paper, we study the adoption of an algorithmic tool used to assist child maltreatment hotline screening decisions. We focus on the question: Are humans capable of identifying cases in which the machine is wrong, and of overriding those recommendations? We first show that humans do alter their behavior when the tool is deployed. Then, we show that humans are less likely to adhere to the machine's recommendation when the score displayed is an incorrect estimate of risk, even when overriding the recommendation requires supervisory approval. These results highlight the risks of full automation and the importance of designing decision pipelines that provide humans with autonomy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
