Written for Computational Culture (forthcoming, #9, preprint with permission)
Review of Joque, Justin. Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism. London and New York: Verso, 2022.
Datafication has been the hallmark of modern governance, all the way back to the definition of statistics as “science of data about the state” in mid-18th century Prussia. Creating reductionist regularity, abstracting from the infinite complexity of local, embodied experience, enabled a new scale and complexity by which the state could organize the life of its subjects, in pursuit of variable political agendas. In the mid-19th century, the philosopher Auguste Comte (1798-1857) introduced a hierarchy of the sciences, with physics at the top for its mathematics-enabled generality, setting off mathematics envy in the social sciences (which he placed at the bottom of the ladder). This was most consequential in economics, but its reverberations are still felt in the recent creation of the “digital humanities”, quantifying the remaining, previously staunchly qualitative fields of knowledge. At the end of the 19th century, rapidly growing corporations, encountering their own need to extend the scale and complexity of governance practices, also turned to large-scale datafication (and automated data processing) to stave off the impending “control crisis” .