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Ambiguous animals, ambivalent carers and arbitrary care collectives: Re-theorizing resistance to social robots in healthcare

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  • Ahlin, Tanja
  • Mann, Anna

Abstract

Many countries are under pressure because of lack of healthcare staff to provide care to an increasingly aged population. Potential solutions are often sought through technological innovation, including social robots to cater to the patients' emotional needs. Despite significant financial investments in social robots, they have not been implemented at a larger scale. One reason commonly cited for this is the resistance of healthcare staff. Drawing on an ethnographic case study of a social robot Paro in an Austrian hospital, we nuance resistance to robots through the heuristic of ambivalence. We argue that the ontological ambiguity of an animal-looking robot provokes highly ambivalent reactions among healthcare staff. Additionally, these reactions are shaped by how the social robot interferes with different professions and the forms of care that they provide. Finally, we show that non-significant others, such as fellow patients, can importantly impact the (dis)use of social robots, an influence which occurs through what we call ‘arbitrary care collectives.’

Suggested Citation

  • Ahlin, Tanja & Mann, Anna, 2025. "Ambiguous animals, ambivalent carers and arbitrary care collectives: Re-theorizing resistance to social robots in healthcare," Social Science & Medicine, Elsevier, vol. 365(C).
    • Handle: RePEc:eee:socmed:v:365:y:2025:i:c:s0277953624010414
    DOI: 10.1016/j.socscimed.2024.117587
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    1. Dympna Casey & Eva Barrett & Tanja Kovacic & Daniele Sancarlo & Francesco Ricciardi & Kathy Murphy & Adamantios Koumpis & Adam Santorelli & Niamh Gallagher & Sally Whelan, 2020. "The Perceptions of People with Dementia and Key Stakeholders Regarding the Use and Impact of the Social Robot MARIO," IJERPH, MDPI, vol. 17(22), pages 1-19, November.
    2. Blake E. Ashforth & Kristie M. Rogers & Michael G. Pratt & Camille Pradies, 2014. "Ambivalence in Organizations: A Multilevel Approach," Organization Science, INFORMS, vol. 25(5), pages 1453-1478, October.
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