It’s only a few years on from the release of ChatGPT but the race to plug artificial intelligence into everything has sparked a surge in datacentres, with escalating environmental costs.
Globally, datacentre power demand is growing four times faster than all other sectors, according to the International Energy Agency, and is on track to exceed Japan’s electricity use by 2030.
In Australia, the energy market operator expects datacentre energy demand to triple within five years, surpassing the electricity used by the nation’s fleet of electric vehicles by 2030. Authorities also anticipate significant demand on drinking water supplies.
As the QuitGPT movement – a boycott of AI over its use for surveillance and weapons – gathers steam, should people concerned about AI’s environmental impacts also consider opting out?
How bad is AI for the environment?
There are varying estimates but most studies say generative AI models – which generate text, images and video – consume “orders of magnitude” more energy than traditional computing methods.
Some estimates suggest it’s five times more energy, others say it could be significantly higher. Much depends on the specific model or type of query.
Prof Jeannie Paterson, co-director of the Centre for AI and Digital Ethics at the University of Melbourne, says part of the problem is the limited transparency from tech companies about the energy, water and emissions impacts of AI and datacentres.
“But it’s clear that training models and running datacentres is an energy intensive task”, she says.
“Consumer software that generates text, images and videos are uniquely energy inefficient,” says Ketan Joshi, an Oslo-based climate analyst associated with the Australia Institute, due to the “vast datasets and computational strain of pattern-matching that happens underneath the hood”.
Asking an AI chatbot a question consumes a great deal more energy than finding the answer via simple web search or calculator. It adds extra demand for no good reason, he says, a bit like driving to the shops in an SUV instead of riding your bike.
“You might still get the shopping done, and that single trip alone may not even look all that bad in terms of cost or emissions, but what happens when that’s all of your trips, and when all of society starts doing this?”
One study published in the journal Patterns estimates AI’s global carbon footprint as 32.6 to 79.7m tonnes of CO2 emissions in 2025, and its water use as 312.5 to 764.6bn litres – similar to the global consumption of bottled water.
In Australia, the growth of datacentres for processing and storing AI data is forecast to slow the energy transition, grow emissions and increase power costs for consumers.
“That’s a lot of energy demand for unclear or small societal benefit,”…
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