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 language | English |
|---|---|
| Article number | 106065 |
| Journal | International Journal of Medical Informatics |
| Volume | 204 |
| Pages (from-to) | 106065 |
| Number of pages | 1 |
| ISSN | 1386-5056 |
| DOIs | |
| Publication status | Published - 12.2025 |
Funding
| Funders | Funder 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)
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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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