Contrary to popular beliefs, artificial intelligence could double its electricity consumption by 2030 to about 3 per cent of the world’s power use and produce greenhouse gas emissions equivalent to the United Kingdom, a report has said
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NEW DELHI — Contrary to popular beliefs, artificial intelligence could double its electricity consumption by 2030 to about 3 per cent of the world’s power use and produce greenhouse gas emissions equivalent to the United Kingdom, a report has said.
The report from the United Nations also warned that AI could deplete more water for cooling than the annual drinking water needs of the global population.
It mentioned that the use of AI will lead to “Jevons paradox”, which entails that as technological improvements increase the efficiency of a resource, the total consumption of that resource will only surge rather than fall.
Economist William Stanley Jevons, observed this effect with the use of coal in 19th-century England when efficiency gains lowered costs resulting in expanded use and higher overall demand for coal.
Similarly new use cases and higher volumes of usage will emerge as AI models become cheaper and more attractive, eroding any savings from efficiency advances, the report stated.
To stay clear of this trap, the report laid out a roadmap for responsible AI use based on guiding principles of transparency, efficiency by design, equity and justice, lifecycle responsibility, global cooperation, and sustainable use.
Data centres consumed as much electricity as Saudi Arabia last year and that, if electricity use doubles by 2030, the associated carbon footprint would require 6.7 billion trees grown over ten years to offset the demand.
It estimated data centres would require about 9.3 trillion litres of water and land nearly ten times the size of Mexico City to support that growth.
The report also warned of an emerging digital and environmental divide as only 32 nations host AI-specific cloud infrastructure with 90 per cent of that capacity located in the US and China.
The nations that consume AI services would bear a disproportionate environmental burden caused by mineral extraction and e-waste.
It urged routine environmental disclosures at both the model and task level adding that responsible AI requires full value-chain governance, from mineral sourcing to recycling and safe disposal.