Evidence map›Paper›PMID 42649346›Full record

ArticleScience and engineering ethics2026

Beyond the Algorithm: Artificial Intelligence, Clinical Decision-Making, and the Moral Ecology of Care in Africa.

Kirubel Manyazewal Mussie

Abstract read
In one paragraph

Article in Science and engineering ethics, 2026. 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.

Kirubel Manyazewal MussieOxford Institute of Population Ageing, University of Oxford, Oxford, UK. manyazewalkirubel@yahoo.com.ORCID http://orcid.org/0000-0002-9313-1186

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung P500PM_225259
6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly promoted as a tool to enhance clinical decision-making and thus improve the quality of healthcare. While much of the emerging scholarship on AI and healthcare in Africa has focused broadly on opportunities and systemic challenges, what remains underexplored is the specific application of AI to clinical decision-making. This paper contributes to addressing this gap by offering a conceptual and critical analysis of AI-based clinical decision support systems (AI-CDSS) in African contexts. Drawing on philosophical accounts of medical reasoning and relational moral frameworks such as Ubuntu, the paper draws on the moral ecology of care and shows that algorithmic systems can reconfigure epistemic authority, redistribute responsibility, and risk marginalising context-sensitive and relational dimensions of care. The paper further argues that AI systems are better understood as socio-technical mirrors that reflect and amplify existing human values, institutional arrangements, and power asymmetries. Moving beyond the algorithm, it proposes a shift toward relational and context-sensitive AI governance, including the development of relational impact assessments, the redistribution of responsibility across the AI lifecycle, and the co-production of knowledge with local stakeholders. While focusing on African clinical contexts, the analysis offers broader insights for global debates on AI ethics and clinical decision-making.

Indexed as

Artificial IntelligenceClinical Decision-MakingDecision Support Systems, ClinicalDelivery of Health CareMoralsAfricaAlgorithmsHumansSocial ResponsibilityArtificial intelligence (AI)Clinical decision-makingEthical challengesRelational impact assessmentThe moral ecology of care

Identifiers

PMID42649346
PMCPMC13518529

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.