Artificial Intelligence has become the most powerful and sought-after technology in today’s digital world. Some of the biggest tech giants across the globe are on a race to invest in AI, with each of them determined to develop models that are bigger, better and stronger than before.
However, what is the true cost of this sensational new technology?
Numerous reports over the past few months have shed a worrying new light on the hidden impact of AI on our planet and environment that may make some re-evaluate the usefulness and benefits of AI when weighed against their unexpected effects.
In March, an article by The New Yorker revealed the staggering amount of electricity used by AI when analyzing OpenAI’s ChatGPT:
“It’s been estimated that ChatGPT is responding to something like two hundred million requests per day, and, in so doing, is consuming more than half a million kilowatt-hours of electricity. (For comparison’s sake, the average U.S. household consumes twenty-nine kilowatt-hours a day.)”
This would translate to approximately 17,000 times more electricity than the average US household. In India, which has also witnessed a rising investment in AI, a similarly large comparison can be expected.
Could a wider adoption of AI lead to an even bigger energy drain?
A study by Alex de Vries, a data scientist for the Dutch National Bank, published in the journal Joule, has revealed even more mind-boggling figures.
It suggests that if Google integrates AI into every search, it could consume an alarming 29 billion kilowatt-hours daily. That surpasses the yearly energy consumption of entire countries like Kenya, Croatia and Guatemala.
Just a few days ago, The Wired published an article titled, “AI’s Energy Demands Are Out of Control. Welcome to the Internet’s Hyper-Consumption Era” that further emphasized the dangerous usage of water required to power AI.
“In addition to high levels of energy usage, the data centers that train and operate generative AI models consume millions of gallons of water,” it wrote.
One of the experts quoted was Shaolei Ren, a responsible AI researcher at UC Riverside and coauthor of “Making AI Less ‘Thirsty’: Uncovering and Addressing the Secret Water Footprint of AI Models.” He highlighted the difference between the environmental impact of companies operating in giant data centers from residents who occasionally leave the faucet running while they brush their teeth.
“They’re different from normal, residential users. When we get the water from the utility, and then we discharge the water back to the sewage immediately, we are just withdrawing water—we’re not consuming water. A data center takes the water from this utility, and they evaporate the water into the sky, into the atmosphere,” Ren said.
What does this mean?
The rise of AI has already provoked numerous ethical concerns, particularly regarding plagiarism and the disregard for consent when it comes to training new models. This environmental impact introduces yet another worrying dimension to the growing demand for artificial intelligence. While these figures perhaps cannot generalize the impact of all AI devices across various countries, they do indicate AI’s increasing appetite for energy is a concern that must be addressed and dealt with in the present and the future.
