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Working For, Against, and Alongside Formalization

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

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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.

Acknowledgements

We are tremendously grateful to advisors, reviewers and friends, past and present, including Jacqueline Wernimont, David Ribes, Adam Hyland, Kate Crawford, Danya Glabau, Anna Lauren Hoffman—and each other. Our thanks further go to the editors for their precise and painstaking work in putting together this special edition.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partially supported by an Ada Lovelace Fellowship, funded by Microsoft Research.

Notes on contributors

Nikki Stevens

Nikki Stevens is a PhD candidate at Arizona State University and a research associate at Dartmouth College. Their background as a software engineer informs their research on proxy surveillance, corporate data collection and the affective power of data.

Os Keyes

Os Keyes is a researcher and writer at the University of Washington, where they study gender, technology and (counter)power. They are a frequently-published essayist on data, gender and infrastructures of control, and a winner of the inaugural Ada Lovelace Fellowship.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

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