ABSTRACT

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.

摘要

面部识别技术 (FRT) 因其种族化影响及其在少数族裔社区过度监管中的作用而受到广泛研究和批评。然而，面部识别技术的一个关键方面是用于训练和测试的面部数据集。在本文中，我们将 FRT 视为一种基础设施组合，并关注四个面部识别数据集的历史：WW Bledsoe 及其团队在 1963 年在全景研究所创建的原始数据集；陆军研究实验室于 1995 年收集的 FERET 数据集；MEDS-I (2009) 和 MEDS-II (2011)，包含死亡被捕者的数据集，由 MITRE 公司策划；以及由 IBM 于 2019 年创建的 Diversity in Faces 数据集。通过这四个示例性数据集，