WASHINGTON (AP) 鈥� The environmental footprint of data centers already rivals some of the world’s largest countries, according to a United Nations University report, which also predicts their water and energy use and pollution will double in just four years as use of artificial intelligence grows.
Last year, global data centers used 448 trillion watt-hours of electricity, more than all but 10 countries of the world, said the report issued Wednesday. That electricity use produced about 208 million tons (189 million metric tons) of carbon dioxide, about the same amount as Argentina, and producing that much energy consumed about 1.2 trillion gallons (4.5 trillion liters) of water, according to the report on the environmental consequences of AI’s energy use.
By 2030, data centers will account for nearly 3% of the world’s projected electricity use, with 935 trillion watt-hours. If data centers were a country, the country would be projected to rank sixth-highest in power use in 2030. That would produce nearly 440 million tons (399 million metric tons) of carbon dioxide, the report said. The study focused on energy use and didn鈥檛 examine the massive amount of water used to cool data centers.
鈥淚f you look at these numbers, we’re seeing scales comparable to nations,鈥� said study co-author Kaveh Madani, a water scientist and director of the United Nations University Institute for Water, Environment and Health in Canada. 鈥淭he demand is enormous.鈥�
Much of the growth of data centers is being driven by AI. About 20% of data centers鈥� energy is currently due to AI, but that should grow to 40% by 2030, the report said.
First global look at ecological impact
The report is significant because of the credibility and authority of the U.N., not just because of any one set of eye-popping numbers, said Fengqi You, a Cornell University energy engineering professor who directs the college鈥檚 AI sustainability issues.
鈥淚ts value is that a U.N. institution is putting carbon, water, land, life-cycle impacts and environmental justice into one frame鈥� for an issue that is often shrouded in secrecy and partial disclosures, said You, who was not part of the report.
鈥淭he general public should be concerned, but not panicked,鈥� he added.
Jean Su, director of the Energy Justice Program at the Center for Biological Diversity, said the report is important because it is the first U.N., or even global, report 鈥渢hat shines a light on the environmental harms of AI.鈥�
National Artificial Intelligence Association President Caleb Max emphasized how his industry is becoming more efficient and how it benefits the public: 鈥淎I is rapidly becoming part of our everyday lives and adding benefits that improve safety, live longer, work more efficiently, enhance food production, and reduce poverty. The evidence is growing daily that the energy return on investment of AI development is transformative for our world and therefore more than worth it.鈥�
Josh Levi, president the Data Center Coalition, said the industry takes its environmental impact seriously.
鈥淲e remain committed to working with policymakers, local communities, and industry partners to ensure that as data centers grow, they do so responsibly, transparently, and in ways that reflect the best available practices,鈥� he said in a statement.
How much energy your query uses and how to trim it
Madani, also the winner of the most recent of the Stockholm Water Prize, said the numbers show the environmental cost of AI, which may seem cleaner at first glance than other mechanical devices, such as cars and furnaces, that have visible pollution.
“AI is not just a virtual thing. We鈥檙e talking about something that has physics, something that has real impacts. There is infrastructure there. There is energy that is being used,鈥� Madani said. 鈥淎 lot of hardware is behind all these operations that to us seem very, very clean because we don鈥檛 see smoke out of our devices. On our cellphone, there is no visible smoke or out of our computer or something. But somewhere else someone is suffering.鈥�
People can reduce AI鈥檚 massive energy appetite by being less polite and more concise in their queries, Madani said. The report found that cutting word use in requests by 30% can reduce energy used by AI by 25%. That would save about the same amount of electricity as what about 700,000 people in Africa use in a year, the report said.
鈥淚f you鈥檙e too polite, then that extra 鈥榩lease鈥� you put there can make a huge difference,鈥� Madani said. 鈥淵ou鈥檝e got to be very precise and be short.鈥�
A typical ChatGPT-style query is about 200 times more energy-intensive than the type of basic text classification used in an email spam filter, for example. AI-generated images or video require much more energy.
And the more complicated the AI, the more energy it takes to train or learn. The report said GPT-3 used about 1.3 billion watt-hours to train, but the next version used 50 to 70 billion watt-hours.
But it’s not training that really feasts on power, said study co-author Miriam Aczel, a United National University environmental policy researcher. About 90% of the power use of AI comes from operational requests, she said. GPT alone accounts for 2.5 billion prompts a day, she said.
Efficiency still means more power use
Even though tech advocates can argue that their machines are becoming more efficient, there’s a common paradox that finds when things get more efficient, they are used more often and total energy use soars even if individual uses are more efficient, Madani said. While some companies tout the use of renewable energy for data centers, Madani said that means the supply of clean electricity is depleted and thus dirtier energy is used elsewhere.
One of the problems in conducting this study is that many companies and places are not transparent about what data centers and AI are consuming or even where and how big they are, Aczel and Madani said.
鈥淲e cannot manage what companies do not disclose,鈥� Cornell’s You said.
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