Five experimentations in computer vision: seeing (through) images from Large Scale Vision Datasets

Using images from large-scale vision datasets (LSVDs), five practice-based studies – experimentations – were carried out to shed light on the visual content, replications of historical continuities, and precarious human labour behind computer vision. First, I focus my analysis on the dominant ideolo...

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Bibliographic Details
Published in:BJHS Themes 2023, Vol.8, p.171-187
Main Author: Moreschi, Bruno
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Critics
Datasets
Information literacy
SECTION 3: Seeing through computer vision, historically
Citations: Items that this one cites
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Summary:Using images from large-scale vision datasets (LSVDs), five practice-based studies – experimentations – were carried out to shed light on the visual content, replications of historical continuities, and precarious human labour behind computer vision. First, I focus my analysis on the dominant ideologies coming from a colonial mindset and modern taxonomy present in the visual content of the images. Then, in an exchange with microworkers, I highlight the decontextualized practices that these images undergo during their tagging and/or description, so that they become data for machine learning. Finally, using as reference two counterhegemonic initiatives from Latin America in the 1960s, I present a pedagogical experience constituting a dataset for computer vision based on works of art at a historical museum. The results offered by these experimentations serve to help speculate on more radical ways of seeing the world through machines.
ISSN:2058-850X
2056-354X
2056-354X
DOI:10.1017/bjt.2023.6