The Energy Burden of AI Health and Equity Risks for Resource Poor Nations

Artificial Intelligence is undergoing wholesale remodeling of global systems from health, finance, agriculture, and governance. But below this transformative potential lies a largely unexplored but critical challenge an astronomic energy demand. Operating AI models, training them, maintaining them require an enormous amount of computational and other resources, which in turn means more energy consumed and carbon emissions produced; while the AI benefits from an economic and technological standpoint are mostly enjoyed by the Global North, countries with lesser means, especially from the Global South, bear their environmental and health consequences. The paper examines the nexus between AI related energy consumption, environmental degradation, and health inequities in low and middle income countries. Drawing insight from frameworks related to global health, energy justice, and digital equity, the research examines how AI systems further deepen the already existing inequality in access to energy, healthcare service, and environmental resilience. Through key risk pattern analysis and setting forward policy frameworks for the deployment of inclusive and ethical AI, this paper calls upon all nations to act forthwith to prevent the deepening of global inequality in the age of AI.