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Paper short abstract:

This contribution draws on a visual ethnography of a computer science lab in Romania, and argues that the stories, or fables (Haraway 2016), that are told both, in the lab and about the lab are key in understanding algorithmic decisions making and their inherent societal and political consequences.

Paper long abstract:

With the increased role of machine learning, questions around the interpretability of AI are also gaining center stage in both computer and social sciences. This contribution draws on a visual ethnography of a computer science lab in Romania, where software engineers work on the interpretability of image recognition algorithms. It argues that the stories, or fables (Haraway 2016), that are told both, in the lab and about the lab are key in understanding algorithmic decisions making and their inherent societal and political consequences. In the lab, tinkering with deep neural network models, introducing additional layers into the learning process, and creating “visualisations”, for instance in the form of heat maps, is not only a technical process, but, at every stage, relies on and incorporates storytelling. Computer scientists often use stories and metaphors where fabulation is entangled with the material and technical practices of “making”. In addition, fabulation is also entangled with the practices of “knowledge creation” about such practices within anthropology. Through an innovative methodological approach, this paper draws on a collaboration and co-laboration between an anthropologist and a computer scientist and mobilises ethnographic filmmaking as a multimodal fabulation to argue that different modes of storytelling might enhance our understanding of how “black boxed” image recognition algorithms work (or in certain cases fail) in practice.