Send message to Authors

Paper short abstract:

AI futures emerge in the “hinge” between techno-ideologies and the everyday failings of algorithmic systems. For anthropologists to engage with these, they must attend to this convergence. In addition, to intervene ethnographically they must build interdisciplinary and participatory collaborations.

Paper long abstract:

Despite repeated non-fulfillments and disappointments, AI remains a field surrounded by myth in which past and futures converge. Algorithmic systems are written through a layering over of prior code and the preexisting techno-social infrastructures which help to realize and convey them. Possibilities for code then are channeled by previous iterations, scaffolded onto what came before. Yet, algorithmic systems conjoin temporalities which are working in reverse and contingent fields of tension, acting in effect within a “trans-temporal hinge”—one vector “anticipatory,” the other, “protospective” (Pedersen/Nielsen 2013). In this presentation we argue that the first is an ideological movement towards a future where social myths are always in a state of becoming. For algorithmic systems, these anticipatory futures are guided by three foundational techno-idealizations: the myth of operability, neutrality and unfetteredness. The second vector is the “present” moment where these same myths are revealed to be, in practice, continually negotiated, layered on, and breaking down in relation to what came before. Typically, this second temporality is the moment of ethnographic intervention, where everyday unravelings become the etic evidence of ideological power. Building on our experiences with algorithmic systems as ethnographers in the field of bioscience and human computation, we argue that ethnographers need to better attend to the “hinge”—this intersection of ideological momentum and the protospective grounding of its inverse failure, out of which the future emerges. We argue further that anthropologists should intervene within and alongside algorithmic practices and form interdisciplinary collaborations to engage with AI and futures in real-time.