Language technologies like generative artificial intelligence (AI) hold significant potential for public health. From outbreak detection systems that scan global news in real time, to chatbots providing mental health support and conversational diagnostic tools improving access to primary care, these innovations are helping address health challenges.
At the heart of these developments is natural language processing, an interdisciplinary field within AI research. It enables computers to interpret, understand and generate human language, bridging the gap between humans and machines. Natural language processing can process and analyse enormous volumes of health data, far more than humans could ever handle manually. This is especially valuable in regions with a stretched healthcare workforce or limited public health surveillance infrastructure, because it enables faster, data-driven responses to public health needs.
Recently, our interdisciplinary team, combining expertise from computer science, human geography and health sciences, conducted a review of studies on how language AI is being used for public health in African countries. Almost a decade’s worth of academic research was analysed, to understand how this powerful technology is being applied to pressing human needs.
