What is the environmental impact of our AI podcasting tools?
Vol. 72 - Digiconomist's Alex de Vries on how much water an AI-generated podcast costs. PLUS, an important open letter you need to sign.
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How many water bottles is one AI-generated podcast dumping out?
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As of May 29, 2025, there are currently 37 long-term drinking water advisories in effect in 35 First Nations communities across Canada.
How many water bottles does one AI-generated podcast cost?
By now you’ve probably got at least one AI tool that a part of your podcast production workflow. Let’s be real, AI has had a massive impact on podcast production efficiency, especially for indie podcasters with limited time and resources.
But not only is there a conversation to be had about industry jobs being taken by AI, ever since I saw a Washington Post infographic about how one email generated by ChatGPT is the equivalent of pouring out a whole water bottle, I’ve been seriously re-evaluating how much AI should be embedded in my own workflow.
That’s why I reached out to Alex de Vries, researcher and founder of Digiconomist, a platform dedicated to exposing the unintended consequences of digital trends. These days Alex is researching the sustainability and power demand of Artificial Intelligence, and is a PhD candidate at Vrije Universiteit Amsterdam.
I talked to Alex about the energy and resource demands of AI creation tools and what podcasters can do about it.
This interview has been edited for length and clarity.
Kattie Laur: I wanna get your reaction to how AI is being used in the podcasting space, beacuse you really could generate a whole episode entirely from AI if you wanted to. So how about I run through an episode production workflow that is entirely run on AI.
First, somebody might go to ChatGPT to come up with a concept for a podcast episode: what the its gonna be about and who we should have as a guest on the show. What kind of environmental impact are we looking at there?
Alex de Vries: Well if you ask this question to ChatGPT, and you only ask it one time, then the energy consumption of generating an answer is going to be a couple of Watt-hours - it’s not going to be tremendous.
Very simply said, longer responses are going to require more power than shorter responses. Talking about a few Watt-hours, this is a low lumen LED bulb you have running for one hour - it’s not much. But if you start asking follow up questions, and you start to start evolving into a conversation, the more interactions you have the higher this number is gonna be.
Previously what researchers did was assume that if you have interaction with ChatGPT, it's always going to be a conversation. It's not just just one interaction. And that's where the bottle of water comes in, because if you have a conversation - somewhere between 15 to 50 interactions - they figure in order to generate that much power there is a certain water footprint associated with it. This is also not a given because it really depends on where a server is located, and is it running on solar power or wind power? Is it running on fossil fuels? [Fossil fuels] require cooling systems, so they require water. If your answer is being powered by hydropower, it's also going to require more water in the end. So this is all very context dependent.
It doesn't matter which model you ask, whether its ChatGPT or DeepSeek, we don't really know for sure what the differences between all these models are because the companies behind these models don't tell us. There's a lot of guesswork involved from researchers who are working on this topic - educated guesswork.
KL: I don't think there's a way to really AI generate a whole podcast yet, but I’m sure it’s coming with audio generation and video generation. But I have seen internet clips of actual podcasts where the hosts have been video-generated into babies. Talk to be about image and video generation.
AdV: In general, an image would be 50 times or 150 times worse than generating text. A video is a series of images, and the longer your video is the worse it's gonna get [for energy and water consumption]. The same is true for generating voice, but video is worse than voice.
Just the model for generating images, there are several orders of magnitudes between the highest and the lowest amount of power consumption involved, which makes it really tricky to make very strong statements about the footprint of image generation, let alone comparing that with the text generation.
Even if you find a more efficient model, good for you. But bigger is better with AI. So if everyone starts using a more efficient model, your efficiency gains are gone anyway.
These markets are highly competitive, especially video generation at the moment. Everyone wants to have the largest market share. In order to get the largest market share, you want to have the very best model out there. You can't combine “bigger is better” with environmental sustainability. It's fundamentally incompatible.
KL: It's like jumbo shrimp. It's an oxymoron.
AdV: Yes, exactly.
KL: So one way I have been using AI has been through Riverside’s AI Magic Clips tool, which selects moments from your recording and creates around 12 clips for you to post on social media.
You don't get to choose how many clips it makes for you, it just picks moments the AI thinks is interesting. In my experience it’s never more than 12, and sometimes they’re good or I only need to edit them minimally, but I’ve wondered why, when the clips are bad, I’m not able to click the button to make more clips for me. Is it something to do with intelligence?
AdV: I imagine why is because this is a great way to generate an excess amount of dark data. You're cutting a bunch of clips and those all have to be stored separately.
Just with a single click of the button, boom, you inflate your storage needs. You're using AI here but this is also dark data, and that actually has a footprint as well. The more we click on the ‘Magic Clip’ button, this will put a lot of stress on storage. So the limit will be there simply because if you push this button a hundred times, the service’s storage requirements are gonna increase so much that they can't handle it.
KL: So here's the question you don't wanna answer: given all these tools that we’ve talked about. Do you have an idea of how many water bottles or how watts we’re talking here? Because it’s got to be at least more than half a water bottle.
AdV: The thing is, you can get there from just the text generation tools you're using. But now you're also using different kinds of applications, image generation which is itself already 50 to 150 times worse, you'll be quickly at multiple bottles of water, but how many exactly? There's no way you can even start putting a number on that because it depends on so many factors.
The fact that we are using these tools for a variety of purposes at a pretty significant scale and it’s rapidly advancing, we’ve seen such a dramatic increase in power consumption. This is the worst increase in power consumption for any emerging tech at any time.
In a couple of years, bitcoin mining became responsible for half a percent of global energy consumption. Now AI is getting to that point in half the time. It's being driven by big money, the big tech companies that are throwing billions at is expanding their AI infrastructure. By the end of the year, half of data centers worldwide might be running AI hardware and that's all because there is mass adoption. It’s like death by a thousand paper cuts.
KL: Are we doomed?
AdV: Well, to a certain extent there is a natural boundary on this. We can have infinite demand for AI, but it's not like we have infinite capacity to deliver that.
There's just a really hard physical limit. There's only so much power we have available. If you have an industry that's growing this fast, ultimately it's gonna run into a power capacity wall. That's at least good news for the environment.
I don't want to put too much responsibility on content creators because the tech companies are just refusing to tell us the footprint related to all of these digital tools. It's not fair to ask the content creators to behave responsibly when the ones that possess the numbers for you to be able to make these decisions are not providing them.
This is a thing that's blowing up so fast that we should know what the impact is of all the tools that we're using. It all has a real world impact, and that's something that really has to change since our lives are increasingly digital. It is really weird that we're not getting the information we need to assess what AI means for the world.
Let's put the pressure on the tech companies. They really have to start providing some information so we can make better choices as content creators - as users.
Interested to learn more about this topic? Check out Alex’s latest paper on AI supply chain constraints and energy implications, and this video below (highly worth the watch)!
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You oughta know…
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Good Reads:
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