论文标题
解决增强业务决策系统中的认知偏见
Addressing Cognitive Biases in Augmented Business Decision Systems
论文作者
论文摘要
业务决策过程中引入的算法决策辅助工具如何影响任务绩效？在第一个实验中，我们研究有效的合作。面对决定，仅受试者的成功率为72％；在成功率75％的推荐人的帮助下，其成功率达到了76％。因此，人类系统的合作的成功率要比单独进行的更高。但是，我们指出了一种自满/权威的偏见，当推荐人错误时，决策质量降低了5％。这表明任何挥之不去的算法偏见都可能被决策辅助工具放大。在第二个实验中，我们评估了5种呈现变体在减少自满偏差方面的有效性。我们发现，可选的演示增加了受试者对错误建议的抵抗力。我们结论说，在实际使用方案中，我们的指标将决策辅助工具嵌入为业务流程管理软件中的全系统功能，可以带来增强的收益。
How do algorithmic decision aids introduced in business decision processes affect task performance? In a first experiment, we study effective collaboration. Faced with a decision, subjects alone have a success rate of 72%; Aided by a recommender that has a 75% success rate, their success rate reaches 76%. The human-system collaboration had thus a greater success rate than each taken alone. However, we noted a complacency/authority bias that degraded the quality of decisions by 5% when the recommender was wrong. This suggests that any lingering algorithmic bias may be amplified by decision aids. In a second experiment, we evaluated the effectiveness of 5 presentation variants in reducing complacency bias. We found that optional presentation increases subjects' resistance to wrong recommendations. We conclude by arguing that our metrics, in real usage scenarios, where decision aids are embedded as system-wide features in Business Process Management software, can lead to enhanced benefits.
