Year: 2023
Type: article
Abstract: Machine vision is one the most consequential applications of artificial intelligence (AI) in contemporary society. This article analyzes how companies that produce machine vision technology articulate what it means for machines to “see.” Through a thematic analysis of more than 200 corporately produced documents, we examine the companies’ product offerings and identify three discursive techniques that entwine basic explanations of emerging technology with the ideologies of AI producers: dismantling sight into technical action, expanding the parameters of sight, and seeing through data. These recurring corporate narratives organize perceptions of automation, educating outsiders how to value computational outcomes and support them through rearranging the real-world conditions of labor. We argue that the social power of machine vision is not only in how it detects objects, but also in how it arbitrates what work is visible in visions of the industry’s future.
Source: New Media & Society
Authors: Wei-Jie Hsiao, Samantha Shorey
Institution: The University of Texas at Austin
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
Funder: National Science Foundation
OpenAlex ID: W4381853826