Hossein Akbarialiabad, M.D., M.Sc., H.M.B.A., Najmeh Sadeghian, M.D., Sara Haghighat, D.D.S., Ayman Grada, M.D., M.S., Shahram Paydar, M.D., M.S., Alireza Haghighi, M.D., D.Phil., Joseph C. Kvedar, M.D., and Nelson K. Sewankambo, M.B.Ch.B., MSc., M.Med.
Achieving the United Nations’ Sustainable Development Goals remains challenging for many low- and middle-income countries (LMICs). Generative artificial intelligence (AI) offers the potential to improve health care delivery access and quality in LMICs. Generative AI applications in health care include individualizing decision support systems for personalized diagnosis and treatment, predicting and managing epidemics, improving medical image interpretation, enhancing telemedicine, and accelerating drug discovery. In addition, generative AI can translate medical information into local languages, boosting health literacy and treatment adherence. However, potential challenges and barriers exist in integrating generative AI into the health systems of LMICs. Ethical dilemmas include the possible negative impacts on climate, limited human expertise and technological infrastructure, undermining the local health workforce, introducing potential biases, compromising data privacy, and increasing liability for faults or inaccurate decisions. The barriers and challenges that impede the increased uptake of generative AI in LMICs need urgent global attention, careful thought, and deliberate action to address them. AI centers of excellence based in LMICs can serve as focal points, providing guidance and stewardship on how to address the challenges while harvesting the benefits of generative AI.