Facing Identity: The Formation and Performance of Identity via Face-Based Artificial Intelligence Technologies

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Authors: Wells Lucas Santo

Published: 2024-10-16 01:14:04+00:00

AI Summary

This literature review analyzes how face-based AI technologies influence the construction and performance of identity in the digital space. It argues for a shift from focusing solely on bias and fairness in AI to a broader sociocultural perspective, proposing an interview study with VTubers to explore the lived experiences of users of "post-facial" technologies.

Abstract

How is identity constructed and performed in the digital via face-based artificial intelligence technologies? While questions of identity on the textual Internet have been thoroughly explored, the Internet has progressed to a multimedia form that not only centers the visual, but specifically the face. At the same time, a wealth of scholarship has and continues to center the topics of surveillance and control through facial recognition technologies (FRTs), which have extended the logics of the racist pseudoscience of physiognomy. Much less work has been devoted to understanding how such face-based artificial intelligence technologies have influenced the formation and performance of identity. This literature review considers how such technologies interact with faciality, which entails the construction of what a face may represent or signify, along axes of identity such as race, gender, and sexuality. In grappling with recent advances in AI such as image generation and deepfakes, I propose that we are now in an era of post-facial technologies that build off our existing culture of facility while eschewing the analog face, complicating our relationship with identity vis-a-vis the face. Drawing from previous frameworks of identity play in the digital, as well as trans practices that have historically played with or transgressed the boundaries of identity classification, we can develop concepts adequate for analyzing digital faciality and identity given the current landscape of post-facial artificial intelligence technologies that allow users to interface with the digital in an entirely novel manner. To ground this framework of transgression, I conclude by proposing an interview study with VTubers -- online streamers who perform using motion-captured avatars instead of their real-life faces -- to gain qualitative insight on how these sociotechnical experiences.

Key findings

The review highlights the inadequacy of current AI analysis focusing solely on bias and fairness in addressing the complexities of post-facial technologies. It emphasizes the need for a sociocultural perspective, highlighting the potential for both liberation and continued oppression in the use of these technologies. The study proposes exploring the use of VTubing as a case study in identity performance and potential transgressions of identity classification.

Approach

The paper conducts a literature review synthesizing existing scholarship on digital identity, face-based technologies, and trans studies. It proposes a qualitative study using semi-structured interviews with VTubers to gather empirical data on identity performance with post-facial technologies.

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