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Short abstract

This paper develops further an understanding of biometric surveillance data as ‘proxy data’ for categorical (or group-relevant) attribution and sets out some of the risks arising from this transformational process in biometric data collection, analysis, and use.

Long abstract

Biometric technologies are increasingly central to arguments made around justice and security in society, thus impacting policies, practices, public life, and people. Biometrics is about producing, defining, prioritising, and ignoring certain knowledge about humans. As part of surveillance technologies, they collect data from individuals, but aggregate and analyse these data, creating group categories of characteristics that are deployed in risk assessments. These abstracted data are then re-applied to individuals to assess potential risk levels and either grant or deny access to services. A further element in this process is the increasing desire to implement automated decision-making in such processes. This can lead to discriminatory effects that are not of justice and security value. Therefore, there is urgent need for critical conceptualisation of knowledge processes in biometric surveillance for identification.

This paper grapples with some of the theoretical background against which we may understand biometric surveillance. It develops further an understanding of biometric surveillance data as ‘proxy data’ for categorical (or group-relevant) attribution and sets out some of the risks arising from this transformational process in biometric data collection, analysis, and use. The paper considers some of the efforts to understand and engage with biometric data collection and uses for surveillance purposes. The discussion here aims to inform thinking around how we may be able to imagine mitigation strategies and needs for knowledge-producing processes in surveillance assessments.