Supportive but apprehensive: Ambivalent attitudes towards a Danish public health AI and surveillance-driven project

We explored attitudes among Danes toward a healthcare project under development, which includes artificial intelligence, healthcare surveillance, and big data – aimed to improve the detection of vaccine side effects. Similar to other studies in the field, we found a dual attitude of overall support for the project while being apprehensive about risky elements within it. We expanded on existing literature about such technologies by framing this as “ambivalence” and acknowledging the tension it creates for interviewees. This allows us to detect a variety of ambivalence-reducing strategies used by interviewees to square their support for the project with their awareness of the risks it introduces. Thus, in addition to conditioning the support for the project, interviewees presented attitudes of technological determinism, powerlessness, and reduced personal risks. We conclude by charting the implications of the current and future levels of public support for projects like the one here discussed.

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Publication Details

Journal
Big Data & Society
Published
2025-10-23
DOI
https://doi.org/10.1177/20539517251386035
Primary Topic
Ethics in Clinical Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Supportive but apprehensive: Ambivalent attitudes towards a Danish public health AI and surveillance-driven project

Shaul A. Duke, Sune Holm, Peter Sandøe, Thomas A.M. Skelly
Big Data & Society
Ethics in Clinical Research
article

Supportive but apprehensive: Ambivalent attitudes towards a Danish public health AI and surveillance-driven project

Shaul A. Duke, Sune Holm, Peter Sandøe, Thomas A.M. Skelly
article en

Abstract

We explored attitudes among Danes toward a healthcare project under development, which includes artificial intelligence, healthcare surveillance, and big data – aimed to improve the detection of vaccine side effects. Similar to other studies in the field, we found a dual attitude of overall support for the project while being apprehensive about risky elements within it. We expanded on existing literature about such technologies by framing this as “ambivalence” and acknowledging the tension it creates for interviewees. This allows us to detect a variety of ambivalence-reducing strategies used by interviewees to square their support for the project with their awareness of the risks it introduces. Thus, in addition to conditioning the support for the project, interviewees presented attitudes of technological determinism, powerlessness, and reduced personal risks. We conclude by charting the implications of the current and future levels of public support for projects like the one here discussed.

Big Data & SocietyVol. 12(4)
University of Copenhagen (DK)
Innovationsfonden
Openalex Percentile: Top 60%
Ethics in Clinical Research
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