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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.
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Stored only when both papers are in the corpus — 14 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.