Evidence map›Paper›PMID 41971282›Full record

ArticleFrontiers in public health2026

Cognitive sovereignty and decolonial public health: reclaiming epistemic authority in the global AI era.

Samuel Kakraba, Edmund Fosu Agyemang, Sudesh K Srivastav

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Samuel KakrabaDepartment of Biostatistics and Data Science, Celia Scott Weatherhead School of Public Health and Tropical Medicine at Tulane University, New Orleans, LA, United States.
Edmund Fosu AgyemangDepartment of Biostatistics and Data Science, Celia Scott Weatherhead School of Public Health and Tropical Medicine at Tulane University, New Orleans, LA, United States.
Sudesh K SrivastavDepartment of Biostatistics and Data Science, Celia Scott Weatherhead School of Public Health and Tropical Medicine at Tulane University, New Orleans, LA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As artificial intelligence (AI) becomes critical infrastructure for global health, it reproduces colonial patterns of extraction, mining data from the Global South to train models owned by the Global North. While international bodies like the WHO emphasize "ethical AI," they often overlook the structural violence of this digital colonialism. This perspective argues that true health equity requires more than bias mitigation; it demands cognitive sovereignty: the right of communities to govern not just their data but also the epistemic logic, interpretive frameworks, and algorithmic reasoning of the systems that analyze it. Drawing from Indigenous data governance principles (OCAP/CARE) and concrete implementation cases from Kenya, Nigeria, Rwanda, and Latin America, we demonstrate how cognitive sovereignty extends beyond data sovereignty to encompass control over knowledge production itself. By anchoring this political vision in specific technical architectures, federated learning, and community-led surveillance, we can move from extractive "AI for good" to a decolonial future of autonomous health intelligence. Recent cases from Kenya's AI health deployments and pathogen genomics illustrate both the urgency and feasibility of this transformation.

Indexed as

Artificial IntelligenceColonialismGlobal HealthPublic HealthHumansartificial intelligence ethicscognitive sovereigntydecolonizationdigital colonialismglobal public health equityGlobal Southhealth data governanceindigenous data sovereignty

Identifiers

PMID41971282
PMCPMC13062185

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.