One argument often used to quell concerns about the rising energy and resource demand of data centres is that artificial intelligence (AI) models will need less in the future as they improve and become more efficient.
But this seemingly logical thinking is a trap, according to a new United Nations report that quantifies the environmental costs of AI.
The report estimates that by 2030, AI’s energy use could double to consume 3% of the world’s electricity, produce emissions to equal the UK and deplete more water for cooling than the annual drinking water need of the global population.
It also anticipates the use of AI will follow an economic principle known as the “Jevons paradox”, which predicts that when technological improvements increase the efficiency of a resource, it leads to a rise, rather than a fall, in the total consumption of that resource.
The paradox is named after economist William Stanley Jevons who observed this effect with the use of coal in 19th-century England. Efficiency gains did not reduce overall consumption. Instead, the lower costs resulted in expanded use and higher overall demand.
