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Paper short abstract

AI systems in dairy farming promise objective and precise knowledge about animal welfare. Drawing on multispecies ethnography in Swedish dairy farming, this paper reflects on how becoming attentive to cows opens alternative ways of knowing animals beyond algorithmic welfare metrics.

Paper long abstract

What does it mean to produce knowledge about animals when their lives are inevitably interpreted through human concepts, methods, and sensory capacities? This question became central to my fieldwork as I entered dairy farms where cows were central actors yet remained interlocutors I could not interview, their lives becoming knowable only through mediated forms of observation and interpretation. Engaging with this tension, the paper offers a reflexive account of what it means to conduct multispecies research in practice. The paper draws on ongoing multispecies ethnographic fieldwork on AI-driven welfare monitoring in Swedish dairy farming. Precision livestock farming systems promise to render animal lives legible through data derived from sensors and machine-learning models, presenting the animals and their welfare as something that can be continuously measured and managed. As such, these systems privilege a particular way of knowing animals grounded in measurable behavioural indicators and algorithmic interpretation. In response, my research attends to the multiple forms of knowledge that coexist in this space. Through multispecies ethnographic methods (including farm observations and engagement with farmers, animal health and welfare experts, industry actors, engineers, and the cows themselves), I examine how different ways of knowing animals are enacted in practice and how animals make themselves known through their embodied engagements with technological infrastructures and farm environments. Reflecting on my process of learning to notice cows differently, the paper contributes to debates on how STS might cultivate knowledge practices more attuned to more-than-human futures.