Comment by jillesvangurp
8 hours 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.
I 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?".
> 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-k...
https://www.technologyreview.com/2025/05/20/1116327/ai-energ...
I 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.
Curious to hear what facts you verified with ChatGPT. I did provide some stats, and they’re sourced from the links I shared, and they do suggest 28PJ is off by an order of magnitude, and that the conclusion of 0.02% emissions might be off by as much as two orders of magnitude. What stats did you find that back up the paper’s summary?
From the technology review article:
“In analyzing both public and proprietary data about data centers as a whole, as well as the specific needs of AI, the researchers came to a clear conclusion. Data centers in the US used somewhere around 200 terawatt-hours of electricity in 2024, roughly what it takes to power Thailand for a year. AI-specific servers in these data centers are estimated to have used between 53 and 76 terawatt-hours of electricity. On the high end, this is enough to power more than 7.2 million US homes for a year.”
53 to 76 twh == 191 to 273 PJ, already used by AI in 2024
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? 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’.
>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
> 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.
> 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.
There 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-memph...
[2]: https://bfi.uchicago.edu/insight/research-summary/when-crypt...
> 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
This is not the case for any well run utility. Commercial customers will pay their share and have their own rates.
Residential power rates are heavily regulated and require a lot of work and justification to raise.
The one case you’re citing appears to be some failure or perhaps corruption. It’s not a universal rule.
I don't know what to tell you other than this is well-established [1][2][3][4].
Also, what exactly is a "well run utility"? IMHO all utilities should be municipality or state owned. All privatization does is transfer wealth from the government and the not-wealthy to the already-wealthy. I suspect you might not agree however.
There are caps on how much utilities can charge but they're allowed to absorb capex (eg by building new transmission lines to a new DC) and if the utility has to buy electricity on the spot market because of increased demand (as was the case with crypto mining in upstate New York), then that raises the per-kWh cost of electricity for everyone, which is great in a cost-plus model.
We've seen this exact thing with healthcare insurance premiums. By law, a certain percentage of premiums has to be spent on giving care. Sounds good, right? So how do you, as an insurance company get around that? You push for higher premiums because that same percentage of profit now means more money. And how do you increase healthcare spend to keep that percentage intact? By spending with providers you also own.
[1]: https://www.bloomberg.com/graphics/2025-ai-data-centers-elec...
[2]: https://energyathaas.wordpress.com/2025/09/29/what-will-data...
[3]: https://www.techpolicy.press/how-your-utility-bills-are-subs...
[4]: https://substack.perfectunion.us/p/how-data-centers-are-driv...
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>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
Can't you make the same argument about anything consuming a scarce resource? Airplanes suck they use oil and make gas prices more expensive for drivers! Amazon sucks because their delivery trucks use oil and make gas more expensive for drivers! Of course, you can argue that airplanes and amazon provide some sort of value and therefore it's worth the consumption/price rises, but that just ends up being a roundabout way of saying "I hate airplanes" or whatever.
It also ignores implications of Jevons Paradox [0], which could go in a couple of different directions.
[0] https://en.wikipedia.org/wiki/Jevons_paradox
This 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.
At 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.
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The pollution issue isn't really possible to solve without using a proper power plant with a tall stack on each unit.
The portable gas turbine units are already very efficient and have surprisingly good emissions controls. Especially the aero derived variety. The problem is dumping the exhaust at ~ground level. This can create hotspots of nitrogen oxides. Especially with so many units running at once. If you exhaust at 100'+, the chances of hazardous accumulation are negligible by comparison.
There's really no clean way to do this fast. You typically need FAA approval to build a stack that would be tall enough to be effective. The best hope for local residents is a rapid crash sometime soon.