How We've Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis
How We've Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis
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DOI：
10.1145/3392866
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发表时间：
2020-05
影响因子：
--
通讯作者：
M. Scheuerman;Kandrea Wade;Caitlin Lustig;Jed R. Brubaker
中科院分区：
文献类型：
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作者：
M. Scheuerman;Kandrea Wade;Caitlin Lustig;Jed R. Brubaker
种族和性别在技术基础设施--从护照到社交媒体--中有着长期的社会政治分类历史。面部分析技术与理解身份如何在新的技术系统中运作特别相关。面部分析技术能做什么取决于可用来训练和评估它们的数据。在这项研究中，我们特别关注这些数据，通过检查种族和性别是如何在用于面部分析的图像数据库中定义和注释的。我们发现，大多数图像数据库很少包含如何定义这些身份的潜在原始材料。此外，当用种族和性别信息对它们进行注释时，数据库作者很少描述注释过程。相反，种族和性别的分类被描绘成无关紧要、无可争辩和非政治性的。鉴于种族和性别的社会历史性质，我们讨论了这些方法的局限性。我们假设，缺乏对这一性质的批判性参与会使数据库变得不透明和不那么可信。最后，我们鼓励数据库作者处理固有地嵌入到种族和性别中的分类历史，以及他们在嵌入这种分类时的位置。
Race and gender have long sociopolitical histories of classification in technical infrastructures-from the passport to social media. Facial analysis technologies are particularly pertinent to understanding how identity is operationalized in new technical systems. What facial analysis technologies can do is determined by the data available to train and evaluate them with. In this study, we specifically focus on this data by examining how race and gender are defined and annotated in image databases used for facial analysis. We found that the majority of image databases rarely contain underlying source material for how those identities are defined. Further, when they are annotated with race and gender information, database authors rarely describe the process of annotation. Instead, classifications of race and gender are portrayed as insignificant, indisputable, and apolitical. We discuss the limitations of these approaches given the sociohistorical nature of race and gender. We posit that the lack of critical engagement with this nature renders databases opaque and less trustworthy. We conclude by encouraging database authors to address both the histories of classification inherently embedded into race and gender, as well as their positionality in embedding such classifications.