Listening to the Body: Responsible AI and Public Health in Africa
In an increasingly algorithm-driven world, the question “What does it mean to be well?” resonates deeply—particularly within Africa’s rapidly evolving health landscape. Artificial intelligence (AI) offers transformative potential for public health, but it also raises ethical challenges. Amid resource constraints and urgent health needs, Africa stands at a crossroads: How can AI respond to the continent’s diverse communities, values, and lived experiences, rather than impose external standards of efficiency?
The Promise of AI in African Health Systems
AI is reshaping global health systems—enhancing diagnostics, disease surveillance, and administrative efficiency. Africa faces persistent challenges, including workforce shortages and fragmented infrastructure. Yet, with over 80% of adults owning mobile phones and rising smartphone adoption, AI-powered tools—delivered through mobile applications , SMS, and chatbots—offer opportunities to improve care access, quality, and continuity.
Across the continent, AI is already making a difference. In South Africa, hospitals are using AI-assisted radiology to detect tuberculosis and cancer at earlier stages. Chatbots provide triage and counselling in local languages, while mobile apps support chronic disease management in underserved areas. In Senegal, the AI4PEP initiative employs community-centred platforms for zoonotic disease monitoring, demonstrating ethically grounded, locally led innovation.
One such initiative is StoryRx, led by Prof. Lynn Hendricks, Prof. Simone Titus-Dawson, Dr Karolien Perold, Dr Annibale Cois, and me as research manager. This project uses AI to generate personalised visual stories grounded in patient symptoms and experiences—enhancing understanding of diabetes management and promoting treatment adherence. Projects like StoryRx reflect how AI, when ethically governed and culturally grounded, can support relational, context-sensitive care.
Expanding this landscape, the StoryRx project—led by Prof. Lynn Hendricks, Prof. Simone Titus-Dawson, Dr. Karolien Perold, Dr. Annibale Cois at Stellenbosch University, and myself as research manager—reflects a significant shift toward culturally sensitive, AI-driven visual storytelling tools for patients diagnosed with non-communicable diseases. By generating personalised digital health stories grounded in patient experiences, symptoms, and treatments, StoryRx enhances understanding of diabetes management, boosting adherence and self-care. These initiatives demonstrate how AI can support relational care rooted in cultural and contextual realities. However, the success of such programs depends on ethical governance, relational data ethics, community engagement, and strong regulatory oversight.
Beyond Efficiency: Trust and Equity
Public health demands are about more than efficiency—it demands health equity. Health outcomes are deeply intertwined with social and political realities shaped by historical and systemic injustices. As Nutbeam and Milat note, the promise of AI caution that AI’s benefits have often come accompanied by hype that outweighs evidence, and without safeguards, raising concerns that unregulated AI could reinforce existing disparities by privileging digitally connected populations.
Ethicists caution that AI systems built on biased or incomplete data can risk perpetuating colonial patterns of knowledge extraction, and deepening health inequities. Protecting privacy, ensuring transparency, accountability, and fostering trustworthiness in AI-driven decisions are foundational. Clinicians also stress that explainability is crucial for building confidence and trust in AI-driven recommendations.
Ethicists and Technologists: Complementary Roles
While ethicists and technologists often view AI development from different perspectives, their viewpoints can be seen as complementary rather than opposing, as illustrated in the comparison table below.
Ethicists advocate embedding social justice and community values into AI design and governance. Technologists acknowledge infrastructure challenges but highlight AI’s transformative potential when applied responsibly. Both perspectives affirm the importance of privacy protection, participatory governance, and ethical transparency.
Public Health Workers: Bridges Between Innovation and Community
Public health workers serve as crucial connectors between AI innovation and community health realities. As Almyranti et al. note, they are central to participatory AI development—embedding safeguards, engaging communities, and ensuring tools reflect local needs. They advocate for ethical AI design, secure data infrastructure, and responsible use aligned with human rights and public welfare. Ongoing education in AI ethics and regulation is vital for sustainable integration.
Grounding AI Governance in African Philosophies beyond Ubuntu
In a rather compelling critique of mainstream algorithmic ethics through an African lens, Ilo noted that while ubuntu—emphasising relationality and shared humanity—has often guided ethical discourse, the author warns that overly simplistic applications may obscure the real complexities of AI governance. Instead, ubuntu should be viewed as a practice of moral responsibility. This requires designers and users to be accountable for technology’s societal impacts and to remain vigilant against deepening injustice. Participatory governance models must actively involve diverse and often marginalised voices—including not only patients, but also rural and indigenous communities, gender minorities, persons with disabilities, and linguistic groups often excluded from global AI frameworks.
Furthermore, Ilo stresses the importance of addressing epistemic exclusion—the neglect of alternative knowledge systems and lived experiences outside dominant Western or techno-centric paradigms. Community health workers, traditional healers, and grassroots organisers offer critical insights into local realities. Their inclusion is essential to ensure AI systems respect plural values and power dynamics. Such engagement builds trust, fosters accountability, and reinforces moral responsibility.
Data, Capacity, and African-Led Innovation
Africa faces serious challenges in data quality and availability. Fragmented information systems and historical legacies result in biased or incomplete datasets. Without diverse, locally generated data, AI models risk inaccuracy and inequity. As Alaran et al. argue, investments in interoperable electronic health records and culturally attuned data governance are vital to uphold African data sovereignty. Simultaneously, building local AI expertise through interdisciplinary training and African-led innovation is essential. Sustainable AI depends on integration with existing health systems, long-term support, and inclusive funding mechanisms.
Governance, Trust, and Ethical Innovation
Ethics and informatics have long evolved together. As Goodman reminds us, ethics is not an obstacle but a partner in innovation. Transparent algorithms, clinical accountability, and respect for patient autonomy are foundational to building public trust. In South Africa, policymakers, clinicians, and technologists are already collaborating to build ethical, transparent, patient-centred AI aligned with national health priorities and law.
Shaping an Ethical AI Future Together
AI holds immense promise for public health in Africa. But realising that promise requires more than technology—it demands partnership. With communities, health workers, ethicists, technologists, and policymakers co-designing AI systems that listen. If Africa leads in this way, it can pioneer not only innovation, but also AI that sees, hears, and heals—uplifting all voices and honouring everybody it is meant to serve.
Author: Gabriela Carolus
Articles in the “Ideas from the Palaver Tree” collection were co-edited by Selamawit Engida Abdella and Dr. Fola Adeleke
