Vol. 25 No. 44 (2026): Artificial Intelligence and health
Originalartikler

AI as collective effort: an empirical study on the introduction of AI in the Norwegian public healthcare services: 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

Published 2026-06-26

Keywords

  • Artificial Intelligence,
  • Healthcare,
  • Collective efforts,
  • Technology introductions

How to Cite

Kannelønning, M. S., & Grisot, M. (2026). AI as collective effort: an empirical study on the introduction of AI in the Norwegian public healthcare services: An empirical study of two Norwegian initiatives. Tidsskrift for Forskning I Sygdom Og Samfund - Journal of Research in Sickness and Society, 25(44), 100–123. https://doi.org/10.7146/tfss.v25i44.156499

Copyright (c) 2026 Mari Serine Kannelønning, Miria Grisot

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Abstract

The introduction of AI in healthcare is usually portrayed as technology- and vendor-driven, focusing on AI tools’ technological performance, often in experimental contexts. Differently, some research has suggested that 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 are interested in understanding the collective dimension of AI introduction. Based on an empirical longitudinal case study approach, including data from interviews, observations and documents, we examine two initiatives to facilitate the introduction of AI in the Norwegian public healthcare sector. The first initiative is an inquiry process led by the Norwegian Directorate of Health and 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 in the area of AI in healthcare. We seek to understand the collective work of enabling the introduction of AI in the two initiatives and the implications of such work. Our findings show that the two initiatives striving to produce hybrid knowledge on crucial challenges of AI in healthcare faced different challenges both in terms of producing such hybrid knowledge and results reflecting the outcome of inclusive collective efforts. We contribute to understanding how the collective dimension of AI plays out, and our findings have implications for future initiatives aiming to gather heterogeneous stakeholders to gain knowledge and a better understanding of challenges related to technology development in society.

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