Seeing like an algorithm: operative images and emergent subjects
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ORIGINAL ARTICLE
Seeing like an algorithm: operative images and emergent subjects Rebecca Uliasz1 Received: 29 July 2019 / Accepted: 18 August 2020 © Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Algorithmic vision, the computational process of making meaning from digital images or visual information, has changed the relationship between the image and the human subject. In this paper, I explicate on the role of algorithmic vision as a technique of algorithmic governance, the organization of a population by algorithmic means. With its roots in the United States post-war cybernetic sciences, the ontological status of the computational image undergoes a shift, giving way to the hegemonic use of automated facial recognition technologies towards predatory policing and profiling practices. By way of example, I argue that algorithmic vision reconfigures the philosophical links between vision, image, and truth, paradigmatically changing the way a human subject is represented through imagistic data. With algorithmic vision, the relationship between subject and representation challenges the humanistic discourse around images, calling for a critical displacement of the human subject from the center of an analysis of how computational images make meaning. I will explore the relationship between the operative image, the image that acts but is not seen by human eyes, and what Louise Amoore calls an “emergent subject,” a subject that is made visible through algorithmic techniques (2013). Algorithmic vision reveals subjects to power in a mode that requires a new approach towards analyzing the entanglement and invisiblization of the human in automated decision-making systems. Keywords Algorithmic vision · Big data · Operational image · Machine learning · Algorithms Portraiture, the act of making a portrait of one’s self or someone else, has a multifaceted meaning in an era of mass social media amidst a swell of digital images that ubiquitously flood our everyday sensorium. A portrait, especially a self-portrait, a representation of the self, has relations to the term “profile” in its colloquial use. I take a photo of my face, I post it to my Instagram story. I am adding to my profile, myself as data, an outline of myself sketched through a series of loosely connected points. My portrait dissolves into an abstract contour composed from the lines between likes, clicks, status updates, my depiction in datafied form. In contemporary discourse, computation has retooled the digital image, with the repercussion that images are not representational, but have an active capacity to perceive and produce new information through 21st-century data analytic practices.
* Rebecca Uliasz [email protected] 1
Computational Media, Arts & Cultures, Duke University, Durham, NC, USA
1 Does one have a right to an image of one’s face? I kept coming back to this question last spring when I learned about the controversy surrounding a data set created by the Duke University Computer Science. DukeMTMC (Multi-Target, Multi-Ca
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