AI in medicine: Systemic integration of data, ethics, and equity for global health transformation
Original framing: “Artificial intelligence and biology: AI’s potential for launching a novel era for health and medicine” — The Conversation - Global
Scientific validation of AI in medicine is growing, particularly in diagnostics and drug discovery. However, the evidence base often lacks diversity in training datasets, which can lead to biased outcomes and reduced efficacy in underrepresented populations.
AI's role in medicine is not merely a technological shift but a systemic transformation that must be guided by ethical, cultural, and structural considerations.
By integrating indigenous knowledge, historical awareness, and cross-cultural insights, AI can become a tool for health equity rather than a mechanism of exclusion. The future of AI in health care depends on inclusive governance, equitable data practices, and a commitment to addressing the root causes of health disparities. Drawing from historical precedents and global models, a reimagined AI health ecosystem can support holistic, community-centered care that aligns with both scientific rigor and human dignity.