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To put this in perspective: world wide the emissions were ~ 37.8 billion tonnes (gigatonnes) in 2024 and 4.77 billion tonnes in the US. So, we're talking about
by jillesvangurp 1y ago
To put this in perspective: world wide the emissions were ~ 37.8 billion tonnes (gigatonnes) in 2024 and 4.77 billion tonnes in the US. So, we're talking about 0.019 % of US emissions.
That's not nothing but also not that high relative to some other things. Addressing this is not going to do much to solve the overall problem that the US is emitting a lot of CO2. AI usage is probably going to grow over time. But it will have to grow a lot to get to displace e.g. transport, industrial heating, or agriculture as dominant sources of CO2 emissions.
Short term the tendency of AI data center providers to solve their energy needs with gas powered generation (mainly) is not great of course. It's opportunistic, there's extra underused gas generation capacity currently that's more or less readily available.
But long term there are some obvious cost savings there as well. Gas isn't cheap; even in the US. And gas turbines are actually scarce. Increased demand is hard to meet with just gas for this reason. AI data centers aren't picking the cheapest energy source but the easiest accessible energy source. Some companies are even looking at nuclear. And not because it's cheap. Likewise, some companies are apparently considering doing some AI compute in space (solar powered).
Long term, solar, wind, and batteries are likely to be the cheapest way to source energy in this sector as well as is already the case in other sectors. Energy is one of the largest cost components for providing AI compute and competition is likely to be fierce. There's no way that companies dependent on expensive forms of energy will be able to compete long term. The short term game is about grabbing market share. Surviving long term will require aggressive cost savings on energy generation.
- jmyeet 1y agoThere are actually a ton of problems with the energy use of AI data centers. 1. Exploiting local laws to basically pollute in essentially residential areas. This is what's happening with Grok's Memphis DC [1]. The gas turbines count as "mobile" so don't need the same pollution controls; 2. Domestic electricity production is heavily natural gas dependent. This is significantly better than coal but obviously not as good as renewables. But we are creating all this new demand for natural gas that is going to do nothing but drive up the price for everybody. This isn't just data centers. It's the policy of massively increasing LNG exports; and 3. For those DCs connected to the local grid, dthey are essentially getting residential customers to pay for the infrastructure and to subsidize the energy usage. Thing is, we've been here before [2]. So we have people with less income because company spend is moving to AI and the money those people have is being further eaten away by higher electricity prices. This is going to be a problem long before the CO2 emissions will be. [1]: https://www.politico.com/news/2025/05/06/elon-musk-xai-memphis-gas-turbines-air-pollution-permits-00317582 https://www.politico.com/news/2025/05/06/elon-musk-xai-memph... [2]: https://bfi.uchicago.edu/insight/research-summary/when-cryptomining-comes-to-town-high-electricity-use-spillovers-to-the-local-economy/ https://bfi.uchicago.edu/insight/research-summary/when-crypt...
- simianwords 1y agoThis is going to be the problem with any new construction or infra project in general. If you buy a big plot of land for a new shoe factory - you will need energy, real estate and many other things which will drive prices up. I'm seeing a big push back from just normal infra building but no one sees the other side - demand for AI is met. Taxes are paid. Jobs are secured.
- jmyeet 1y agoAt least a shoe factory will employ people and produce something people will buy. After a DC is built, it only needs a handful of people (compared to the capex) and as for its output? We just haven't seen AI create a service or product people really value and will pay for. This is really the most alarming thing about the AI boom: it's so much like 2000 and the dot-com bubble because so many companies never had a business model or revenue let alone made a profit.
- simianwords 1y ago> We just haven't seen AI create a service or product people really value and will pay for. That's not something you have to worry about because the risk is taken primarily by the companies themselves. ChatGPT has around 800 million weekly active users. That is humongous, considering such a new technology. I wonder what your stance would be if the companies do start making profit and become rich through data centres. If that happens are you okay? Because I see that also a problem that people propose - companies getting too rich and extracting wealth. What’s the ideal situation? In any case, I find this anti infra building a bit annoying if I may be direct. People want AI. Data centres are built to meet the demand. Profits are likely.
- jmyeet 1y agoIf only that were true. The likes of Google, Meta, Microsoft and Oracle will survive by cuttings costs (ie firing people) and probably getting bailed out by the government, either with direct loans or simply with government contracts. We're already seeing massive increases in homelessness. Now imagine if unemployment goes to 8-10%. We had higher unemployment in Covid but the government opened the money faucet to avoid a complete collapse. Unemployment peaked at around 10% in the GFC and it was both a massive wealth transfer to the already-wealthy and a massive decrease in real wages as entry-level positions disappeared. You don't spend trillions in corporate investment to have the bubble collapse and society not to feel the pain.
- Aurornis 1y ago> To put this in perspective: world wide the emissions were ~ 37.8 billion tonnes (gigatonnes) in 2024 and 4.77 billion tonnes in the US. So, we're talking about 0.019 % of US emissions. Thank you for putting it in perspective. All of these headlines that quote isolated emissions numbers without anything to compare it to are deliberately useless. It’s meant to ride the wave of anti-data center and anti-AI outrage, not to be actually useful for forming an opinion. It’s also unhelpful when data center emissions is compared to personal household use or cars. The real comparison should be to other industrial and commercial operations. If we started putting datacenter emissions in context with other processes like global shipping, aluminum production, or other industrial scale activities people would realize it’s not a problem. Journalists aren’t doing that, though, because they want to tap into the anti-data center outrage in the zeitgeist right now.
- entuno 1y ago> All of these headlines that quote isolated emissions numbers without anything to compare it to are deliberately useless. I would go beyond that and say that they're deliberately misleading. They're not quoting a big scary-sounding number out of context to try and be unhelpful - it's an intentional and active choice to push a specific narrative.
- stavros 1y agoI have an issue with this, and it's not the perspective. It's not the AI usage directly that's producing the CO2, it's the fact that we're generating energy from CO2-producing sources. I have the same objection with the scaremongering titles "electric cars emit a ton of CO2! (If you assume they get all their energy from coal, anyway)". Yes, cars use energy, AI uses energy, so do lots of other things. We should cut down on frivolous uses of energy, but we should definitely, immediately transition away from fossil fuels to clean sources of energy. Then the title would be "AI adds no CO2 because how would it?".
- ivape 1y agoI give up on the clean energy narrative from America. If the goal is clean energy, then why are our leaders warning about Chinese EVs eating the world? EVs eating the world solves some part of the dirty energy problem. I don’t get it anymore, so, going to take my seat next to Carlin and just say ‘fuck it, planet will be fine’.
- gruez 1y ago>I give up on the clean energy narrative from America. If the goal is clean energy, then why are our leaders warning about Chinese EVs eating the world? Goomba fallacy[1]. Within the Democratic party at least, there are at least 3 camps with different reasons for supporting/opposing EVs: 1. environmentalists, who want to reach net zero ASAP 2. "made in America" types, who want to keep encourage/retain domestic manufacturing because they think they're a source of good blue collar jobs 3. china hawks, who want to stifle china's rise [1] https://en.wiktionary.org/wiki/Goomba_fallacy https://en.wiktionary.org/wiki/Goomba_fallacy
- dahart 1y ago> we’re talking about 0.019% of US emissions That’s assuming the numbers are accurate and in the ballpark, and I’m having a really hard time getting the numbers in the paper to add up. Do you believe them, or better yet, do you have other sources that support or confirm these numbers? Just googling, what I get back is estimates that AI in 2024 already consumed over 200PJ, nearly 10x the number in the article, and is projected to double in the next few years. US electricity production is already ~25-30% of US CO2 emissions, and data centers are at least a quarter of that, and AI is now a huge driver of data center energy use. Data centers are using more than 4% of US electricity. How is it possible that projected AI emissions are 0.019% from this one paper, while multiple other sources are estimating AI is already responsible for on the order of 2% of US emissions in 2024? I’m seeing a 100x discrepancy… I don’t suspect the authors have intentionally downplayed either estimates, but a bunch of the paper’s data is old enough that it’s not useful for examining AI trends today. The energy use data is from 2016 and 2019. The energy use of inference is from GPT3 and usage numbers in 2023. The estimates of NVIDIA servers sold is from 2023. AI has exploded since then, and I suspect their estimates are off by orders of magnitude because AI usage has exploded in the last 2 years. The author’s estimate of 28PJ of future AI energy use is based on a whole stack of assumptions in which small errors at every step can lead to very large errors in the estimate. That number is based on guesses of how automatable jobs are, and not on observations of the actual change in AI energy use today. https://www.pewresearch.org/short-reads/2025/10/24/what-we-know-about-energy-use-at-us-data-centers-amid-the-ai-boom/ https://www.pewresearch.org/short-reads/2025/10/24/what-we-k... https://www.technologyreview.com/2025/05/20/1116327/ai-energy-usage-climate-footprint-big-tech/ https://www.technologyreview.com/2025/05/20/1116327/ai-energ...
- jillesvangurp 1y agoI did a quick chat gpt research fact check on this and did not find any obvious red flags. That's not a substitute for good research, obviously. I don't think it matters unless they are off by something outrageous like at least an order of magnitude. That would push it close enough to a one tenth of a percent that you could argue it's rivaling some of the more minor sources of emissions like aviation (2-3% I believe). You'd still be off by another order of magnitude. I don't have any reason to believe that that is the case. But please do share if you have other/better information. I agree with you that reports like this typically have agendas and lots of little white lies, half truths, or assumptions that you might challenge. The question is are they overstating or understating the problem. And why. I can't judge that. I have my suspicions but I kept those out of my original comment; other of course than pointing out that based on the published numbers, this is does not seem like it actually is a very big problem.