This talk introduces a new history of machine visuality. The stakes are multiple. In the spirit of histories of visuality (e.g. Jonathan Crary), the recent history of electro-optical media (and specifically machine vision) might tell us something about the dominant modes of thinking about vision over the last century or so. We might also want to learn something about the scopic regimes of machine vision systems because of their use in surveillance, automation, scientific research etc. More broadly, however, I want to argue that discourses and practices of visuality (and thus a set of only partially explicit theories about seeing) have been absolutely central to the invention and development of neural networks, and thus to contemporary AI more broadly (including the superficially non-visual, from chat-bots to audio systems). Where might look for evidence of machine visuality? So far, we have largely focused on “training sets” from the past decade or two - following an anthropocentric dichotomy between nature (our common neural wiring) and nurture (the individual visual culture to which we are exposed). This already uncomfortable distinction completely collapses in the case of machine vision, where the wiring is itself a socially and historically embedded technology. I will attempt to partially redress this imbalance by focusing primarily on the wiring. I’ll investigate some basic building-blocks of today’s neural architectures, largely developed from the 1960s to the 1980s.