A global perspective on data powering responsible AI solutions in health applications

Abstract

Healthcare AI solutions have the potential to transform access, quality of care, and improve outcomes for patients globally. This review suggests consideration of a more global perspective, with a particular focus on marginalized communities, during the development of healthcare AI solutions. The review focuses on one aspect (medical applications) to allow technologists to build solutions in today's environment with an understanding of the challenges they face. The following sections explore and discuss the current challenges in the underlying data and AI technology design on healthcare solutions for global deployment. We highlight some of the factors that lead to gaps in data, gaps around regulations for the healthcare sector, and infrastructural challenges in power and network connectivity, as well as lack of social systems for healthcare and education, which pose challenges to the potential universal impacts of such technologies. We recommend using these considerations in developing prototype healthcare AI solutions to better capture the needs of a global population.; Competing Interests: Conflict of interestThe authors did not receive support from any organization for the submitted work. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. (© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)