Seeing infrastructure: race, facial recognition and the politics of data

被引:17
|
作者
Stevens, Nikki [1 ]
Keyes, Os [2 ]
机构
[1] Arizona State Univ, Human & Social Dimens Sci & Technol, Tempe, AZ USA
[2] Univ Washington, Human Ctr Design & Engn, Seattle, WA 98195 USA
关键词
Facial recognition; datasets; surveillance; racialization; critical biometric consciousness; infrastructure; FACE RECOGNITION;
D O I
10.1080/09502386.2021.1895252
中图分类号
Q98 [人类学];
学科分类号
030303 ;
摘要
Facial recognition technology (FRT) has been widely studied and criticized for its racialising impacts and its role in the overpolicing of minoritised communities. However, a key aspect of facial recognition technologies is the dataset of faces used for training and testing. In this article, we situate FRT as an infrastructural assemblage and focus on the history of four facial recognition datasets: the original dataset created by W.W. Bledsoe and his team at the Panoramic Research Institute in 1963; the FERET dataset collected by the Army Research Laboratory in 1995; MEDS-I (2009) and MEDS-II (2011), the datasets containing dead arrestees, curated by the MITRE Corporation; and the Diversity in Faces dataset, created in 2019 by IBM. Through these four exemplary datasets, we suggest that the politics of race in facial recognition are about far more than simply representation, raising questions about the potential side-effects and limitations of efforts to simply 'de-bias' data.
引用
收藏
页码:833 / 853
页数:21
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