论文标题
评估认知决策支持系统中偏见的风险
Assessing Risks of Biases in Cognitive Decision Support Systems
论文作者
论文摘要
识别，评估，反驳和减轻与异质来源不同性质的偏见是设计认知决策支持系统（DSS）的关键问题。这种系统的一个示例是认知生物特征识别的安全检查点。有偏见的算法以不可预测的方式影响决策过程，例如不同人口组的面部识别可能会严重影响检查站的风险评估。本文讨论了一个充满挑战的研究问题，即如何管理偏见集合？我们从偏见方面提供了DSS操作局势的性能预测。概率推理技术用于评估这种偏见的风险。我们还使用检查点系统的面部生物识别组件提供了一个动机实验，该实验突出了发现偏见的集合和评估其风险的技术。
Recognizing, assessing, countering, and mitigating the biases of different nature from heterogeneous sources is a critical problem in designing a cognitive Decision Support System (DSS). An example of such a system is a cognitive biometric-enabled security checkpoint. Biased algorithms affect the decision-making process in an unpredictable way, e.g. face recognition for different demographic groups may severely impact the risk assessment at a checkpoint. This paper addresses a challenging research question on how to manage an ensemble of biases? We provide performance projections of the DSS operational landscape in terms of biases. A probabilistic reasoning technique is used for assessment of the risk of such biases. We also provide a motivational experiment using face biometric component of the checkpoint system which highlights the discovery of an ensemble of biases and the techniques to assess their risks.
