Leveraging 'Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South' (REL-AI4GS): Implications for Policies and Lessons Learned from the 'Africa-Canada Artificial Intelligence and Data Innovation Consortium' (ACADIC) Project

Abstract

“Clinical public health” can be defined as an interdisciplinary field, at the intersection of clinical medicine and public health, whilst “clinical global health” is the practice of clinical public health with a special focus on health issue management in resource-limited settings and contexts, including the Global South. As such, clinical public and global health represent vital approaches, instrumental in i) applying a community/population perspective to clinical practice as well as a clinical lens to community/population health, ii) identifying health needs both at the individual and community/population levels, iii) systematically addressing the determinants of health, including the social and structural ones, iv) reaching the goals of population’s health and well-being, especially of socially vulnerable, underserved communities, v) better coordinating and integrating the delivery of healthcare provisions, vi) strengthening health promotion, health protection, and health equity, and vii) closing gender inequality and other (ethnic and socio-economic) disparities and gaps. Clinical public and global health are called to respond to the more pressing healthcare needs and challenges of our contemporary society, for which artificial intelligence (AI) and big data analytics (BDA) can help unlock new options and perspectives. In the aftermath of the still ongoing COVID-19 pandemic, the future trend of AI and BDA in the healthcare field will be devoted to building a more healthy, resilient society, able to face several challenges arising from globally networked hyper-risks, including ageing, multimorbidity, chronic disease accumulation, and climate change. In the present paper, we will explore how AI and BDA can help address clinical public and global health needs in the Global South, leveraging and capitalizing on our experience with our “Africa-Canada Artificial Intelligence and Data Innovation Consortium” (ACADIC) Project in the Global South, and focusing on the ethical and regulatory challenges we had to face.