How AI Consumes Water: The unspoken environmental footprint

Artificial Intelligence (AI) systems, particularly those involving high-performance servers, generate a significant amount of heat and require water for cooling purposes. The concept of a "water footprint" in AI refers to the total volume of water used directly and indirectly during the lifecycle of AI models, including the water used for cooling vast data centers and the water consumed in generating the electricity that powers them. Training a single AI model like GPT-3 could require as much as 700,000 liters of water, which is equivalent to the annual water consumption of several households. Reducing the water footprint of AI models can be done by optimizing algorithms for energy efficiency, developing more sustainable data center designs, and shifting the timing of intensive AI tasks to coincide with periods of lower electricity demand.