Fysh Matthew C, Bindemann Markus
School of Psychology, University of Kent.
Cogn Sci. 2018 Jun 28;42(5):1714-32. doi: 10.1111/cogs.12633.
Automatic facial recognition is becoming increasingly ubiquitous in security contexts such as passport control. Currently, Automated Border Crossing (ABC) systems in the United Kingdom (UK) and the European Union (EU) require supervision from a human operator who validates correct identity judgments and overrules incorrect decisions. As the accuracy of this human-computer interaction remains unknown, this research investigated how human validation is impacted by a priori face-matching decisions such as those made by automated face recognition software. Observers matched pairs of faces that were already labeled onscreen as depicting the same identity or two different identities. The majority of these labels provided information that was consistent with the stimuli presented, but some were also inconsistent or provided "unresolved" information. Across three experiments, accuracy consistently deteriorated on trials that were inconsistently labeled, indicating that observers' face-matching decisions are biased by external information such as that provided by ABCs.
自动面部识别在诸如护照检查等安全环境中变得越来越普遍。目前，英国（UK）和欧盟（EU）的自动边境通关（ABC）系统需要人工操作员进行监督，该操作员会验证正确的身份判断并推翻错误的决定。由于这种人机交互的准确性仍然未知，本研究调查了先验面部匹配决策（如自动面部识别软件所做的决策）如何影响人工验证。观察者对屏幕上已标记为描绘相同身份或两个不同身份的成对面孔进行匹配。这些标签中的大多数提供了与呈现的刺激一致的信息，但也有一些不一致或提供了“未解决”的信息。在三个实验中，在标签不一致的试验中，准确性持续下降，这表明观察者的面部匹配决策受到诸如ABC提供的外部信息的影响。
