Årg. 25 Nr. 44 (2026): Kunstig Intelligens og sundhed
Originalartikler

Collective efforts for the introduction of AI in healthcare: An empirical study of two Norwegian initiatives

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  • Mari Serine Kannelønning,
  • Miria Grisot
Mari Serine Kannelønning
Universitetet i Oslo
DOI: https://doi.org/10.7146/tfss.v25i44.156499

Publiceret 2026-06-26

Nøgleord

  • collective effort,
  • AI in healthcare,
  • clinical practice,
  • consensus-based,
  • hybrid knowledge

Citation/Eksport

Kannelønning, M. S., & Grisot, M. (2026). Collective efforts for the introduction of AI in healthcare: An empirical study of two Norwegian initiatives. Tidsskrift for Forskning I Sygdom Og Samfund, 25(44), 100–123. https://doi.org/10.7146/tfss.v25i44.156499

Copyright (c) 2026 Mari Serine Kannelønning, Miria Grisot

Creative Commons License

Dette værk er under følgende licens Creative Commons Navngivelse –Ikke-kommerciel (by-nc).

Resumé

The collective dimension of AI is crucial to ensure sustainable and ethical outcomes of AI implementation in society; accordingly, the introduction of AI in healthcare is a collective concern. In this paper, we examine this collective dimension of AI introduction by drawing on an empirical longitudinal case study of two initiatives aimed at introducing AI into the Norwegian public healthcare services. The first initiative is an inquiry process led by the Norwegian Directorate of Health, as part of a project initiated by a government policy plan outlining a vision for AI in healthcare. The second initiative is a nationwide, informally established network of professionals engaged with AI in healthcare. Drawing on insights on hybrid knowledge production in collective efforts, as well as practice-oriented and relational understandings of technology, our analysis of the two initiatives focuses on how the collective effort was carried out, the role of the orchestrators and the implications of such efforts on their outcomes. Our findings show that the two initiatives, while seeking to produce hybrid knowledge on how to best introduce AI in healthcare, faced different challenges, both in generating such knowledge, in achieving consensus-based results and in enacting visions of AI in healthcare oriented to clinical practice. We suggest that to contribute to a consensus-based and inclusive introduction of AI in healthcare, collective efforts should pay attention to the inclusion of heterogeneous stakeholders and their interaction modes, the politics of agenda settings and modes of orchestration.

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