This article argues that critical AI studies should make a methodological investment in “thick description” to counteract the tendency both within computational design and business settings to presume (or, in the case of start-ups, hope for) a seamless and inevitable journey from data to monetizable domain knowledge and useful services. Perhaps the classic application of that critical data-studies framework is Marion Fourcade and Kevin Healy's influential 2017 essay, “Seeing Like a Market,” which advances a comprehensive account of how value is extracted from data-collection processes. As important as these critiques have been, the apparent inevitability of this assemblage of power, knowledge, and profit arises in part through the metaphor of “sight.” Thick description—especially when combined with a feminist and queer attention to embodiment, materiality, and multisensory experience—can in this respect supplement Fourcade and Healey's critique by revealing unexpected imaginative possibilities built out of social materialities.

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