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Accepted Paper:
Paper Short Abstract:
This paper examines the mobilization of differing notions of community and patienthood in the creation and maintenance of digital infrastructures for hearing aids. I critically examine the sensual character of extractive economies and their alternatives in the day-to-day life of hearing aid users.
Paper Abstract:
In the wake of the datafication of audiology and medical hearing devices, new forms of community and patienthood are being evoked: Newly emerging AI-based hearing aid applications allow users to impact the configurations of their hearing aids more actively and in a time-sensitive manner. So far, this task has largely been reserved for audiologists, who relied on a mix of auditory listening tests as well as listening to their patients’ experiences. This practice is now being accompanied - and in some cases replaced - by machine learning-based recommender systems. These ML-based hearing aids promise to expand and automate forms of medical listening and decision-making by drawing on a multitude of data streams derived from overlapping forms of senses and sensing devices (Lupton 2017, Maslen 2017). This ranges from the reading of geo- and bio-data, as well as the collection of user input, to data collected from hearing aid users worldwide. These data streams are being understood as a form of algorithmically mediated production of community. In addition, they are staning in contrast to pre-existing forms of knowledge-creation and data management of not only healthcare professionals but also of activists and users.
Drawing on six months of ethnographic fieldwork in Austria, Germany, and Denmark, this paper critically examines competing notions of solidarity, community, and well-being that are being mobilized by healthcare companies, Big Data’s extractive economies, as well as hearing aid users and activists. I especially highlight the sensual character of data production and data infrastructures and ask how these narratives produce different types of digital infrastructures (Larkin 2013; Donovan 2015), imbued with and mobilized by differing politics and understandings of “good” patients – individually and collectively.
Number politics: ethnographies of composing, sensing, and being with data
Session 2 Wednesday 24 July, 2024, -