Recently, philosophers and social scientists have turned their attention to the epistemological shifts provoked in established sciences by their incorporation of big data techniques. There has been less focus on the forms of epistemology proper to the investigation of algorithms themselves, understood as scientific objects in their own right. This article, based upon 12 months of ethnographic fieldwork with Russian data scientists, addresses this lack through an investigation of the specific forms of epistemic attention paid to algorithms by data scientists. On the one hand, algorithms are unlike other mathematical objects in that they are not subject to disputation through deductive proof. On the other hand, unlike concrete things in the world such as particles or organisms, algorithms cannot be installed as the objects of experimental systems directly. They can only be evaluated in their functioning as components of extended computational assemblages; on their own, they are inert. As a consequence, the epistemological coding proper to this evaluation does not turn on truth and falsehood but rather on the efficiency of a given algorithmic assemblage. This article suggests that understanding the forms of algorithmic rationality employed in such inquiry is crucial for charting the place of data science within the contemporary academy and knowledge economy more generally.

Our world is densely populated by ubiquitous processors, capacious storage, and vigilant sensors. Networks of such machines are constantly measuring, packaging, storing, circulating, and operating on the world. They are busy assembling and being assembled, sharing information, and distributing their processing loads as they make decisions and enact plans. At the same time, they are refusing connections, maintaining their immune systems, performing network security, managing their boundaries, and controlling access. Human bodies move among this flexible, securitized meshwork of silicon, electricity, code, fiber optics, and data: building, maintaining, and restructuring. Their activity ensures that aesthetic, epistemological, economic, and political structures are thoroughly woven into these computational networks, tightly coupling the technical to the social as they experiment with new forms of work and life. Yet many of those who are building these systems do not seem particularly concerned with ensuring that our computational futures remain within the control, or even comprehension, of fleshy and cultural human beings. On the contrary: as they craft and maintain the

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