According to Clifford Geertz, the purpose of anthropology is not to explain culture but to explicate it. That should cause us to rethink our relationship with machine learning. It is, we contend, perfectly possible that machine learning algorithms, which are unable to explain, and could even be unexplainable themselves, can still be of critical use in a process of explication. Thus, we report on an experiment with anthropological AI. From a dataset of 175K Facebook comments, we trained a neural network (...) to predict the emoji reaction associated with a comment and asked a group of human players to compete against the machine. We show that a) the machine can reach the same accuracy as the players, b) it fails in roughly the same ways as the players, and c) easily predictable emoji reactions tend to reflect unambiguous situations where interpretation is easy. We therefore repurpose the failures of the neural network to point us to deeper and more ambiguous situations where interpretation is hard and explication becomes both necessary and interesting. We use this experiment as a point of departure for discussing how experiences from anthropology, and in particular the tension between formalist ethnoscience and interpretive thick description, might contribute to debates about explainable AI. (shrink)

Making publics visible through digital traces has recently generated interest by practitioners of public engagement and scholars within the field of digital methods. This paper presents an experiment in moving such methods into critical proximity with political practice and discusses how digital visualizations of topical debates become appropriated by actors and hardwired into existing ecologies of publics and politics. Through an experiment in rendering a specific data-public visible, it shows how the interplay between diverse conceptions of the public as well (...) as the specific platforms and data invoked, resulted in a situated affordance-space that allowed specific renderings take shape, while disadvantaging others. Furthermore, it argues that several accepted tropes in the literatures of digital methods ended up being problematic guidelines in this space. Among these is the prescription to shown heterogeneity by pushing back at established media logics. (shrink)