[Air-L] Call for Papers - Machine Vision in Context: politics and practices of computational seeing - photographies
handm at queensu.ca
Fri Jun 4 06:43:10 PDT 2021
photographies – Call for Papers
Special Issue: Machine Vision in Context: Politics and Practices of Computational Seeing
Issue Editors: Martin Hand (Queen’s University) and Ashley Scarlett (Alberta University of the Arts)
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).
At stake is an unprecedented automation of visual culture, through the infrastructural dimensions of platforms and image economies, corporate and political efforts to harness these ‘structures of seeing’, and multi-faceted configurations of technologies such as facial recognition, wearable cameras, drones, locative media, and so forth (McCosker and Wilson 2020; Mackenzie 2017). This transforms or perhaps further reveals the radically contingent spatial and temporal dynamics of photography, its experimental forms (Gerling 2018), and tensions between its expanding role in expressive human sociability (Henning 2021) and the aims of computational interpretation to determine visual meaning (Geboers & Van De Wiele 2020; Zylinska 2021). We are at a critical juncture where the distinctive categories of the networked image, image processing, machine vision and the like, appear conjoined in ways that require critical engagement to properly understand their implications for contemporary photographic practices. Correspondingly, grounded examinations of how photographic images and practices are being used to advance the aims and applications of machine vision also present an opportunity for greater insight into the politics and practices of computerized seeing.
This special issue will thus be concerned with examining the multiple challenges this suite of evolving technologies poses for the continued salience of the photographic, the contemporary politics of image making, distribution, ordering and interpretation, and the practices of personal and artistic photography. How are different forms of machine vision shaping practices of looking, seeing, sensing, and witnessing associated with photography? What are the historical continuities and discontinuities between imaginaries and technical aspects of machine vision in photographic practices? How and in what ways are historically embedded forms of visual inequalities being replicated or disrupted by computerized modes of seeing? How is machine vision being appropriated for social justice? How have artists developed critiques of machine vision? What roles are artistic interventions playing in the public understanding of machine vision?
We seek substantial contributions (4,000-6,000 words) that engage with these issues and questions. Particular topics of interest include but are not limited to:
* Genealogical histories and prehistories of machine vision in photography
* The roles of photographic images in training A.I. systems
* Ethnographic examinations of visual content moderation or image-based microwork
* Photographic expertise and literacies in machine learning
* Categorizations and classifications that emerge in response to machine vision
* Embodied and affective experiences of automation in vernacular photography
* Changes in visual perception associated with machine learning
* Everyday and mundane expressions of machine vision applications and techniques (e.g., filter apps; tagging practices)
* Vision and seeing in ‘smart’ technologies and environments
* Role of the photographic in multi-sensory applications
* Computerized vision in professional domains (e.g., medicine; manufacturing; urban planning; etc.)
* Use of automated images in track and trace surveillance
* Evidential paradigms in machine vision
* Artistic and activist exposures, critiques, and appropriations of computerized vision
* The grounds of the image in computerized vision
Please submit abstracts (350-500 words max ) and queries to: handm at queensu.ca<mailto:handm at queensu.ca> and ashley.scarlett at auarts.ca<mailto:ashley.scarlett at auarts.ca>
Deadline: Abstracts due July 7th, 2021; Papers due May 1st, 2022.
Abstracts and papers will have the benefit of full peer review before acceptance.
Department of Sociology
handm at queensu.ca
Queen’s University sits on the traditional lands of the Haudenosaunee and Anishinaabe peoples.
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