论文标题
生物识别技术中的人口偏见：有关新兴挑战的调查
Demographic Bias in Biometrics: A Survey on an Emerging Challenge
论文作者
论文摘要
结合生物识别技术的系统已在个人，商业和政府身份管理应用程序中变得无处不在。合作社（例如访问控制）和非合件（例如监视和取证）系统都受益于生物识别技术。这样的系统依赖于人类某些生物学或行为特征的独特性，这使得个人可以使用自动化算法可靠地识别。 然而，最近，关于自动化决策系统（包括生物识别技术）中系统性偏见的存在，有很多公共和学术问题。最突出的是，面部识别算法经常被媒体，非政府组织和研究人员都标记为“种族主义”或“偏见”。 本文的主要贡献是：（1）在生物识别方面概述算法偏见的话题，（2）对现有的有关生物偏见估计和缓解现有文献的全面调查，（3）讨论相关的技术和社会事务，以及（4）（4）挑战和未来的项目和社会的概述，从技术和社会上进行了挑战和社会的概述。
Systems incorporating biometric technologies have become ubiquitous in personal, commercial, and governmental identity management applications. Both cooperative (e.g. access control) and non-cooperative (e.g. surveillance and forensics) systems have benefited from biometrics. Such systems rely on the uniqueness of certain biological or behavioural characteristics of human beings, which enable for individuals to be reliably recognised using automated algorithms. Recently, however, there has been a wave of public and academic concerns regarding the existence of systemic bias in automated decision systems (including biometrics). Most prominently, face recognition algorithms have often been labelled as "racist" or "biased" by the media, non-governmental organisations, and researchers alike. The main contributions of this article are: (1) an overview of the topic of algorithmic bias in the context of biometrics, (2) a comprehensive survey of the existing literature on biometric bias estimation and mitigation, (3) a discussion of the pertinent technical and social matters, and (4) an outline of the remaining challenges and future work items, both from technological and social points of view.
