Harnessing Artificial Intelligence to Meet Global Healthcare Challenges: Reparative Algorithmic Impact Assessments in Context

Abstract

Artificial intelligence (AI) has the ability to revolutionize global healthcare delivery, offering opportunities to accelerate progress toward Sustainable Development Goal 3: Good Health and Well-being. This potential is especially significant in the Global South, where resource constraints, infrastructure limitations, and diverse sociocultural approaches to health and healing create complex, or “wicked,” problems. From clinical decision support systems and diagnostic tools to predictive analytics and drug discovery platforms, AI applications are multifold. However, their rapid deployment raises ethical concerns, particularly regarding their potential to perpetuate harm. Current governance mechanisms often fall short in addressing structural inequities or empowering affected communities. These frameworks typically focus narrowly on risk identification/mitigation and technical fairness, neglecting crucial historical and sociocultural realities. This article introduces Reparative Algorithmic Impact Assessments (R-AIAs) as a transformative framework for ensuring ethical and equitable AI deployment in healthcare. Grounded in decolonial and intersectional values, R-AIAs emphasize challenging Western epistemologies, promoting data inclusivity and sovereignty, fostering participatory governance, and redressing systemic biases, inequities, and power imbalances. The framework's ability to center diverse knowledge systems, such as Ubuntu philosophy, emphasizes its catalytic potential. R-AIAs operationalize these principles through six interconnected steps, exemplified by a case study of an AI-powered maternal health system in sub-Saharan Africa. These steps offer actionable strategies for bridging global divides. By embedding reparative practices, R-AIAs elevate impact assessments from compliance exercises to tools for empowerment, challenging colonial legacies and advancing global health equity. The framework underscores that achieving “AI for All” demands a sustained commitment to justice and redress.

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