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Ethics in Danish healthcare AI policy: A document analysis

Victor Vadmand Jensen*, Marianne Johansson Jørgensen, Rikke Hagensby Jensen, Jeppe Lange, Jan Wolff, Mette Terp Høybye

*Corresponding author for this work

Abstract

Introduction: Nations are increasingly turning towards artificial intelligence (AI) systems to support healthcare settings. While nations must then contend with ethical considerations surrounding healthcare AI, they do so in a variety of ways, emphasizing different ethical considerations in different ways. However, there is still limited knowledge on how Scandinavian healthcare AI policy emphasizes ethics. In this paper, we investigate ethics in Danish healthcare AI policy to highlight underlying policy preferences. Methods: We present a document analysis of Danish policy documents relating to AI. We view policy documents' contents as expectations that signal and frame what is perceived as a desirable future with healthcare AI. From 210 policy documents, we extracted data of text snippets related to categories of ethical principles and pipeline stages, as well as articulated reasons for considering ethics. We analyzed the proportions of ethical principles and pipeline stages quantitatively and reasons for considering ethics inductively. Results: The most frequently cited ethical principle was prevention of harm (n = 177), while the most commonly referenced pipeline stage was implementation, evaluation, and oversight (n = 189). Both ethical principles and pipeline stages significantly deviated from equal proportions (p<0.001). Additionally, five primary reasons for addressing ethics emerged in the documents: fit of AI with existing healthcare structures, the potential consequences of AI, its marketability, associated uncertainties, and the perceived inevitability of its adoption. These findings indicate that Danish healthcare AI policy predominantly frames ethical considerations based on the potential consequences of AI deployment. Conclusions: Our study suggests the need for steering Danish, and more broadly Scandinavian, healthcare AI policy toward other views of ethics that integrate non-potentiality.

Original languageEnglish
Article number106065
JournalInternational Journal of Medical Informatics
Volume204
Pages (from-to)106065
Number of pages1
ISSN1386-5056
DOIs
Publication statusPublished - 12.2025

Funding

FundersFunder number
Helsefonden
Region Midtjylland
Aarhus Universitet, Department of Clinical Medicine
Regional Hospital Silkeborg

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Research Areas and Centers

    • Centers: Center for Artificial Intelligence Luebeck (ZKIL)

    DFG Research Classification Scheme

    • 2.22-02 Public Health, Healthcare Research, Social and Occupational Medicine
    • 4.43-04 Artificial Intelligence and Machine Learning Methods

    KDSF Research Field Classification Scheme

    • 073 - Artificial intelligence and big data

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