ReviewDigital health
Ethical governance of artificial intelligence in digital health for Indigenous populations: A narrative review and conceptual framework.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) integration into digital health care delivery is rapidly expanding and is increasingly viewed as a promising approach for improving access to care, strengthening diagnostic decision-making, and addressing persistent health inequities experienced by Indigenous populations. Although AI-enabled digital health applications offer potential benefits such as scalability, personalization, and improved clinical decision support, they also raise critical ethical concerns related to equitable implementation, culturally grounded design, representative data usage accountability, privacy protection, and Indigenous data sovereignty. A coherent ethical governance framework is necessary to guide the responsible development, deployment, and evaluation of AI applications implemented in digital health solutions involving Indigenous communities. A narrative review was conducted to critically assess recent literature (2020-2025) addressing ethical considerations in the integration of AI into digital health care delivery for Indigenous populations. Searches were performed in MEDLINE, PubMed, Web of Science, and Scopus using terms related to artificial intelligence, digital health, Indigenous populations, and ethics, with supplementary grey literature searches conducted to identify policy and implementation reports. Studies were selected based on relevance to AI-enabled digital health initiatives implemented in digital health contexts involving Indigenous communities in Canada, the United States, Australia, New Zealand, and the United Kingdom, and were synthesized using thematic narrative analysis. Six themes denoting ethical domains were identified: (1) co-design of AI technologies, (2) culturally grounded implementation, (3) bias and representative data, (4) accountability, transparency, and intelligibility, (5) privacy and Indigenous data sovereignty, and (6) resource accessibility. These domains function as interconnected components of ethical governance, with participatory governance and Indigenous data sovereignty emerging as foundational cross-cutting principles. The proposed framework is not intended as a pan-Indigenous or one-size-fits-all model. Instead, it is conceptualized as a flexible, distinctions-based ethical governance framework that must be adapted to the specific cultural, geographic, and governance contexts of individual Indigenous communities. Based on this analysis, we propose a conceptual ethical governance framework to support policymakers, clinicians, health systems, digital health developers, as well as Indigenous communities in identifying ethically appropriate safeguards across the lifecycle of AI-enabled digital health initiatives planned or implemented in Indigenous communities.
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Registered trials
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.