Assessing the impact of student-led advocacy initiatives on Canadian undergraduate students' knowledge of and attitudes toward organ donation: a cross-sectional survey from Western University.

Over recent years Artificial intelligence (AI) has emerged as a highly promising innovation in various sectors including global health. It has been well documented that it has potential to enhance diagnostics, streamline clinical decision-making [,]. However, the extent to which AI meaningfully expands constrained health resources in low- and middle-income settings remains insufficiently understood. AI systems depend on large, high-quality datasets for training and validation. Yet most health datasets used to train algorithms are sourced from high-income countries, leading to limited representation of African populations and health conditions []. Moreso, the ethical and normative foundations of AI governance are predominantly shaped by frameworks developed in Western contexts []. As such, this mismatch can lead to governance mechanisms that fail to protect marginalised populations or to confront historical and structural forms of exclusion embedded in health systems in Sub-Saharan Africa. Across Africa, emerging empirical research highlights both optimism about AI’s capacity to improve health service delivery and deep concerns about fairness, bias, and implementation barriers. Studies find that while general populations may express trust in AI, experts raise concerns about ethical implications, fairness indicators, and systemic obstacles to equitable integration and governance []. Policy analyses and stakeholder reports further emphasise that without proactive, equity-focused policy measures AI risks reinforcing ‘digital colonialism’ where technologies developed outside local contexts are imposed in ways that undermine local priorities and marginalised groups’ access to care []. Artificial intelligence (AI) is increasingly presented as a transformative technology capable of improving healthcare delivery and strengthening health systems. However, the implications of these technologies for marginalised populations within Sub-Saharan Africa remain insufficiently understood. Artificial intelligence has the potential to increase access to healthcare and improve disease surveillance, but there are concerns that the use of technology may reproduce or exacerbate existing social and structural inequalities if data representation, infrastructure, and governance are not addressed. This scoping review, therefore, aimed to synthesise existing evidence on the role of artificial intelligence in shaping health equity in African health systems. To guide this review, the following research questions were developed: