This article examines augmented reality filters applied to users’ faces, or ARFaces, a visual technology that has spread with increasing success since 2015, mainly through social media. In the first part, the article highlights four significant issues that have emerged about ARFaces: the risks of Body Dysmorphic Disorders linked to beautification filters; the new personal and immediate relationships with brands linked to branded ARFaces; the adoption of filters by a new generation of artists and creatives; and the risks of surveillance related to the face recognition technology on which they are based. The second part of the article argues that ARFaces represent a symptomatic example of ‘algorithmic images’. This type of image modifies the logic of ‘technical images’ that characterised previous media as it shifts the centre of gravity of the processes of the visual constitution from the remote transfer of information to the automated extraction and processing of data. In its conclusions, the article outlines some conceptual tools for dealing with algorithmic images: the author proposes developing a political economy of light and analysing its transformation from a support infrastructure for a political economy of the visual to a supply structure for a data economy.
Eugeni, R., A scanner darkly: augmented reality face filters as algorithmic images, <<VISUAL COMMUNICATION>>, 2024; 23 (3): 498-512. [doi:10.1177/14703572241235286] [https://hdl.handle.net/10807/300363]
A scanner darkly: augmented reality face filters as algorithmic images
Eugeni, Ruggero
2024
Abstract
This article examines augmented reality filters applied to users’ faces, or ARFaces, a visual technology that has spread with increasing success since 2015, mainly through social media. In the first part, the article highlights four significant issues that have emerged about ARFaces: the risks of Body Dysmorphic Disorders linked to beautification filters; the new personal and immediate relationships with brands linked to branded ARFaces; the adoption of filters by a new generation of artists and creatives; and the risks of surveillance related to the face recognition technology on which they are based. The second part of the article argues that ARFaces represent a symptomatic example of ‘algorithmic images’. This type of image modifies the logic of ‘technical images’ that characterised previous media as it shifts the centre of gravity of the processes of the visual constitution from the remote transfer of information to the automated extraction and processing of data. In its conclusions, the article outlines some conceptual tools for dealing with algorithmic images: the author proposes developing a political economy of light and analysing its transformation from a support infrastructure for a political economy of the visual to a supply structure for a data economy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.