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Today, a significant amount of computer vision algorithms rely on techniques of machine learning which require large amounts of data assembled in collections, or named data sets. To build these data sets a large population of precarious workers label and classify photographs around the clock at high speed. For computers to learn how to see, a scale articulates macro and micro dimensions: the millions of images culled from the internet with the few milliseconds given to the workers to perform a task for which they are paid a few cents. This paper engages in details with the production of this scale and the labour it relies on: its elaboration. This elaboration does not only require hands and retinas, it also crucially zes mobilises the photographic apparatus. To understand the specific character of the scale created by computer vision scientists, the paper compares it with a previous enterprise of scaling, Malraux\u2019s <jats:italic>Le Mus\u00e9e Imaginaire<\/jats:italic>, where photography was used as a device to undo the boundaries of the museum\u2019s collection and open it to an unlimited access to the world\u2019s visual production. Drawing on Douglas Crimp\u2019s argument that the \u201cmus\u00e9e imaginaire\u201d, a hyperbole of the museum, relied simultaneously on the active role of the photographic apparatus for its existence and on its negation, the paper identifies a similar problem in computer vision\u2019s understanding of photography. The double dismissal of the role played by the workers and the agency of the photographic apparatus in the elaboration of computer vision foreground the inherent fragility of the edifice of machine vision and a necessary rethinking of its scale.<\/jats:p>","DOI":"10.1007\/s00146-020-01093-w","type":"journal-article","created":{"date-parts":[[2020,11,11]],"date-time":"2020-11-11T18:02:41Z","timestamp":1605117761000},"page":"1117-1131","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["On the data set\u2019s ruins"],"prefix":"10.1007","volume":"36","author":[{"given":"Nicolas","family":"Malev\u00e9","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,11]]},"reference":[{"key":"1093_CR1","unstructured":"Beheshti S-M-R, Tabebordbar A, Benatallah B, Nouri R (2016) Data curation APIs. 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