Evidence map›Paper›PMID 41312253›Full record

ArticleFrontiers in public health2025

WHO and artificial intelligence: contesting global health futures through foresight.

Jason Tucker

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Jason TuckerInstitutet for Framtidsstudier, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The article examines the World Health Organization's (WHO) discourse on artificial intelligence (AI) in their foresight exercises, doing so by drawing on the analytical framework of strong and weak AI narratives. The analysis finds that strong AI narratives (those which depict AI as human-like or even super-intelligent, emphasising existential risks and transformative power) are rarely found. In contrast, the exercises produce a broad range of weak AI narratives (those that emphasise the technical limitations, ethical concerns, and practical governance of specific AI applications in healthcare). The findings reveal how certain AI technologies are foregrounded by WHO, how these are framed as in isolation from other emerging technologies, how this isolation is strategically blurred, and the role of expert participation in legitimising WHO's policy on AI. Situated within WHO's broader policy discourse on AI, the paper draws out how the foresight exercises strategically construct and validate particular trajectories aligned with WHO's existing priorities. Through selective narrative framing, expert input, and methodological design, WHO reinforces its epistemic authority by guiding the discourse on AI in global health toward context-sensitive and manageable use cases of the technology. Ultimately, these foresight exercises serve as a site of contestation, where competing visions of AI in global health are negotiated, and WHO's influence over future governance in the area is actively shaped.

Indexed as

Artificial IntelligenceGlobal HealthWorld Health OrganizationForecastingHumansAIartificial intelligenceforesightfuturesglobal healthnarrativespolicy discourseWHO

Identifiers

PMID41312253
PMCPMC12649817

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.