Toward Environmentally Equitable AI

The growing adoption of artificial intelligence (AI) has been accelerating across all parts of society, boosting productivity and addressing pressing global challenges such as climate change. Nonetheless, the technological advancement of AI relies on computationally intensive calculations and thus has led to a surge in resource usage and energy consumption. Even putting aside the environmental toll of server manufacturing and supply chains, AI systems can create a huge environmental cost to communities and regions where they are deployed, including air/thermal pollution due to fossil fuel-based electricity generation and further stressed water resources due to AI's staggering water footprint.12,25 To make AI more environmentally friendly and ensure that its overall impacts on climate change are positive, recent studies have pursued multifaceted approaches, including efficient training and inference,5 energy-efficient GPU and accelerator designs,19 carbon forecasting,14 carbon-aware task scheduling,1,21 green cloud infrastructures,2 sustainable AI policies,10,18 and more. Additionally, datacenter operators have also increasingly adopted carbon-free energy (such as solar and wind power) and climate-conscious cooling systems, lowering carbon footprint and direct water consumption.8