This special issue will bring together interdisciplinary scholarship that engages critically with the evolving, recursive interrelations between machine vision and photography.
The heightened capacities of machines to ‘see’ and visually categorize the world have been the subject of numerous recent journalistic exposés and public outcry. Whether critiquing the role that machine vision plays in efforts to track, detain, and penalize targeted communities, or charting the incorporation of similar technologies into urban infrastructures, self-driving cars and ‘smart’ appliances, there is a growing awareness that it is reshaping what is seen and what counts as seeing. Online, recognition algorithms increasingly automate the tasks of tagging, categorizing and extracting meaning from the “unmanageable and unassimilable” accumulation of images circulating across networked environments (Henning 2018). Within this context of volume, scale, and distributed production, the photographic image appears to have receded from the realm of human perception (Zylinska 2017), working instead as an ‘operative’ agent (Hoelzl & Marie 2015) that drives and draws together the constellation of hard and soft platforms that comprise the contemporary mediascape (Dvořák and Parikka 2021; Mackenzie & Munster 2019). Images and their audiences are being ‘put to work,’ as the solicitation and generation of metadata as well as the non-human recognition of pixel- and user-based patterns facilitates the improvement and expansion of computerized vision (Sluis 2020).