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arXiv · 2007.14361

Assessing Risks of Biases in Cognitive Decision Support Systems

Kenneth Lai·Helder C. R. Oliveira·Ming Hou·Svetlana N. Yanushkevich·Vlad Shmerko
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Abstract

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.

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Kenneth Lai, Helder C. R. Oliveira, Ming Hou, Svetlana N. Yanushkevich, Vlad Shmerko. 2020-07-28. Assessing Risks of Biases in Cognitive Decision Support Systems. https://doi.org/10.23919/eusipco47968.2020.9287384

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