[Commlist] CFP Machine Vision in Context: Politics and Practices of Computational Seeing

CFP /- photographies /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)


Abstract Deadline: July 7th, 2021

Full Paper Deadline: May 1st, 2022



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 ) 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 7^th 2021; Papers due May 1st 2022.

Abstracts and papers will have the benefit of full peer review before 
acceptance.

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