Facial recognition, emotion and race in animated social media

Luke Stark

Abstract


Facial recognition systems are increasingly common components of commercial smart phones such as the iPhone X and the Samsung Galaxy S9. These technologies are also increasingly being put to use in consumer-facing social media video-sharing applications, such as Apple’s animoji and memoji, Facebook Messenger’s masks and filters and Samsung’s AR Emoji. These animations serve as technical phenomena translating moments of affective and emotional expression into mediated socially legible forms. Through an analysis of these objects and the broader literature on digital animation, this paper critiques the ways these facial recognition systems classify and categorize racial identities in human faces. The paper considers the potential both for racializing logics as part of these systems of classification, and how data regarding emotional expression gathered through these systems might interact with identity-based forms of classification.


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DOI: https://doi.org/10.5210/fm.v23i9.9406



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