AI Has A Voracious Appetite For Electricity, And That’s A Problem – CleanTechnica

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Artificial intelligence, popularly known as AI, is very much in the news these days. Most people seem to think it is the greatest thing since sliced bread, but it may not be as much of a blessing as we might think. Bloomberg reports that John Ketchum, CEO of NextEra Energy, told those in attendance at CERAWeek in Houston that US power demand is poised to increase by 81% over the next five years. Toby Rice, chief of the largest US natural gas driller EQT, cited a prediction that AI will gobble up more power domestically than households by 2030 (emphasis added).

“It is going to be transformational,” ConocoPhillips CEO Ryan Lance told the audience. “It is going to be huge. It is going to impact every one of your businesses here.” You can almost see him licking his chops at the thought of all the lovely profits his company expects to make by supplying fossil fuels to thermal generators.

Chevron CEO Mike Wirth talked about sending employees back to school to study AI. Olivier Le Peuch, who leads SLB, said the technology is being used for robotic drilling and to prolong the productive life of aging wells. BP CEO Murray Auchincloss discussed its potential to enhance trading. None of those potentates offered so much as a hint as to how the emissions from generating all that lovely electricity might hasten the collapse of the Earth’s environment due to ever increasing average global temperatures.

Writing in the New Yorker recently, Elizabeth Kolbert explained that this “obscene” power demand comes because when you ask AI to help you with your bracket for the NCAA tournament, for instance, it has to sort through all human knowledge ever.

Sam Altman, the controversial head of OpenAI, told attendees at the World Economic Summit in Davos this year, “I think we still don’t appreciate the energy needs of this technology.” He added that he didn’t see how those needs could be met “without a breakthrough. We need fusion or we need, like, radically cheaper solar plus storage, or something, at massive scale — like, a scale that no one is really planning for.” And that, of course, is the problem. Once again, humanity is about to go off on a tear to acquire the latest and greatest new, new thing, whether that is AI or green hydrogen or…ohhh, shiny thing!

AI Vs Human Intelligence

The truth is, there’s no way we can build out renewable energy fast enough to meet this kind of extra demand, says Bill McKibben. “It’s going to be at the bleeding edge of the technically and politically possible to power the things we already do, like drive cars and heat homes. And so, in a rational world, faced with an emergency, we would put off scaling AI for now. The irony, of course, is that’s it’s often been touted as a tool to help solve climate change. But we have the tools we need — plain old intelligence gave us cheap solar panels.”

To illustrate his point, McKibben asked Anthropic’s AI bot Claude to comment. “It was amazing how much he sounded like a PR man,” he said. “After spinning a lot of jargon filled guff about how ‘responsible AI can likely be part of the solution to environmental challenges,’ Claude finally admitted he had no idea how much energy he was using. He said, ‘In general, the electricity usage of large language models like myself is a relevant consideration from an environmental perspective, but quantifying the exact amount would require additional information I don’t have access to.’”

Having been properly schooled by an AI bot, McKibben said, “Whatever. What we need is not more intelligence. We need more wisdom, to guide us through this pinch point in the human experiment. Including the wisdom to say no to some things, at least until the emergency subsides.” And of course Bill is correct. If we create more pollution to power AI, aren’t we regressing away from a sustainable world instead of progressing toward a future where people can live in temperatures for which their bodies have adapted over hundreds, if not thousands, of generations?

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AI & Climate Science

That question led MIT professor Priya Donti to co-found Climate Change AI, which calls itself “a global non-profit that catalyzes impactful work at the intersection of climate change and machine learning.” Speaking at the ClimateTech conference hosted by MIT Technology Review last fall, Donti said that not every application of AI requires immense amounts of energy. “There are a lot of models that can run on a laptop,” she pointed out.

More important, AI has vast potential to accelerate the search for solutions to the climate crisis. Drawing from “Tackling Climate Change With Machine Learning,” a 2022 paper she co-authored with 21 fellow researchers, Donti highlighted ways in which AI is helping scientists and policymakers think through and address the challenge of climate change:

• Gathering and analyzing data. The quantity of climate-related data produced far exceeds the human capacity to analyze it. Donti pointed to satellite imagery as one example — a firehose of pictures that show agricultural land, say, or forest cover around the world. In these cases, AI can be deployed to assess what kinds of crops are being grown where and what adaptation measures should be put in place in light of climate projections, or to analyze trends in deforestation and reforestation.
• Forecasting. AI can be instrumental in creating various types of forecasts. The nonprofit Open Climate Fix, for instance, uses a combination of historical data and satellite images of cloud cover to derive estimates that better match near-term solar power production with electricity demand. AI can also be used to predict demand for transportation infrastructure or the probability of extreme weather events.
• Improving systems efficiency and predictive maintenance. AI has a growing role to play in optimizing systems, such as freight transportation, food refrigeration, and heating and cooling in buildings. “A very unsexy but related application of AI and machine learning is predictive maintenance,” Donti said. For instance, AI can be used to detect and patch methane leaks in natural gas infrastructure before they worsen, thus preventing methane from leaking into the atmosphere.
• Facilitating the invention of next-generation technologies. AI can be used as a sort of scientific assistant. Donti described how researchers at Stanford used AI to help companies manufacture batteries more efficiently by analyzing the outcomes of past experiments. The project reportedly reduced the number of design cycles by a factor of 10.

Donti also highlighted three impediments to the use of AI in developing climate solutions. First and most explicit is that machine learning is being used on the other side of the balance. “The canonical example is AI being used to accelerate oil and gas exploration and extraction in a way that is projected to create $400 billion of profit for the oil and gas industry by 2025,” Donti said. There are more subtle cases, too, like the use of AI in targeted advertising, which drives consumption, or in developing autonomous vehicles which Donti said “support individualized transit as opposed to multimodal public transit.”

Second, as the use of artificial intelligence increases and demand for computing power rises, there is the question of AI’s carbon footprint. As the use of AI becomes more pervasive and the models grow in power, its contribution should be more carefully quantified and tracked, she said.

Third is the challenge of accuracy, particularly as it relates to infrastructure and public safety. For example, Donti studies the use of machine learning to optimize and control power grids, which have “hard constraints.” If you don’t get the physics right, the result of AI optimization could be a blackout, with related economic losses and even loss of life — “things you really don’t want,” she said.

The Takeaway

Professor Danti’s embrace of AI for climate research is laudable. But the question remains whether its generalized use may not represent an overall negative impact on the environment. Certainly if it will be an excuse to build more thermal generation so people can create term papers or legal briefs (not to mention Michael Barnard’s immensely entertaining graphics for his articles on CleanTechnica), that is hardly a reason to celebrate.

And yet, trying to limit the use of AI to endeavors that are socially beneficial is like trying to get people to only drive their cars when absolutely necessary. Not gonna happen. In order to maximize the limits of computer technology, we will need to vastly increase our electricity generating capabilities. We don’t have enough renewable energy as it is. How much of it should be diverted to power AI, or mine Bitcoin, or support online sports betting?

Those are the sorts of messy questions that few people want to answer and so they prefer not to ask them in the first place. And so we careen blissfully into the future using more and more resources to amuse ourselves. If we continue to do what we always have, we will continue to get what we have always gotten — a profligate waste of resources to keep us entertained. Yes, friends, we are that shallow.