Ethical Challenges of Artificial Intelligence in Medicine in African Settings: Application to Ophthalmology
Les Défis Éthiques de l'Intelligence Artificielle en Médecine en Milieu Africain : Application à l'Ophtalmologie
DOI:
https://doi.org/10.5281/zenodo.19510667Keywords:
Artificial intelligence, Ophthalmology, Medical ethics, Africa, Algorithmic bias, Health equity, Diabetic RetinopathyAbstract
RÉSUMÉ
L'intégration de l'intelligence artificielle (IA) en ophtalmologie marque un changement de paradigme, passant de la promesse expérimentale à une réalité clinique tangible. Cependant, son déploiement en Afrique présente des défis éthiques uniques liés aux disparités de ressources, aux biais algorithmiques et aux contextes socioculturels spécifiques. Cette revue examine le paysage actuel des applications de l'IA en ophtalmologie et analyse de façon critique les défis éthiques, pratiques et humanistes associés à son implémentation dans les contextes africains. Nous avons réalisé une analyse narrative de la littérature récente (2018-2025) sur l'IA en ophtalmologie, avec un focus particulier sur les études concernant les pays à revenu faible et intermédiaire et les contextes africains. L'IA, en particulier le machine learning et le deep learning, a démontré des performances diagnostiques comparables ou supérieures à celles des experts humains pour la rétinopathie diabétique, la dégénérescence maculaire liée à l'âge et le glaucome. Cependant, les algorithmes entraînés principalement sur des populations européennes ou est-asiatiques présentent une précision réduite pour les patients d'ascendance africaine [25,36]. Les défis infrastructurels, le manque de données représentatives et l'absence de cadres réglementaires adaptés constituent des obstacles majeurs. L'avenir réside non pas dans le remplacement de l'ophtalmologue par l'IA, mais dans l'augmentation de son expertise clinique à travers un modèle centré sur l'humain. Une mise en œuvre responsable nécessite des stratégies proactives incluant la formation des cliniciens, la surveillance des résultats, une communication transparente avec les patients et l'élaboration de cadres de gouvernance adaptés aux contextes africains.
ABSTRACT
The integration of artificial intelligence (AI) in ophthalmology marks a paradigm shift from experimental promise to tangible clinical reality. However, its deployment in Africa presents unique ethical challenges related to resource disparities, algorithmic biases, and specific sociocultural contexts: This review examines the current landscape of AI applications in ophthalmology and critically analyzes the ethical, practical, and humanistic challenges associated with its implementation in African settings. We conducted a narrative analysis of recent literature (2018-2025) on AI in ophthalmology, with particular focus on studies concerning low- and middle-income countries and African contexts. AI, particularly machine learning and deep learning, has demonstrated diagnostic performance comparable or superior to human experts for diabetic retinopathy, age-related macular degeneration, and glaucoma. However, algorithms trained primarily on European or East Asian populations show reduced accuracy for patients of African ancestry. Infrastructure challenges, lack of representative data, and absence of adapted regulatory frameworks constitute major barriers . The future lies not in replacing ophthalmologists with AI, but in augmenting their clinical expertise through a human-centered model. Responsible implementation requires proactive strategies including clinician training, outcome monitoring, transparent patient communication, and development of governance frameworks adapted to African contexts.
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