3. For every five to 50 questions asked, ChatGPT requires 500 milliliters of water
It’s not just power that AI requires—these data centers also need fresh water to operate the cooling systems necessary to keep facilities safe.
“Think about your computer, when it starts to ventilate and gets very hot,” Le Bas said. “[Then] multiply that by thousands. We need massive cooling systems.”
By 2027, the water needed for those cooling systems will amount to one-half of what the entire U.K. is currently using, according to one estimate from Cornell University.
4. ChatGPT-3 was trained on 45 terabytes of text data, translated for AI using human labor
The social cost of training AI isn’t currently well understood, Le Bas noted.
But reporting from Time showed that some contractors in Kenya were paid less than $2 per day to sift through disturbing content generated by early versions of ChatGPT, highlighting the labor-related risks associated with outsourcing some aspects of training LLMs.
5. General models can use 30 times more energy than specialized models
One way marketers can curb the impact of their AI use is by using specialized models when applicable. A 2023 study by Carnegie Mellon and Hugging Face showed that specialized models are much more energy-efficient that general models like ChatGPT.
Another way companies can cut the carbon cost of AI is by adopting “conscious computing” practices, which aim to encourage lower-impact tools when appropriate, Le Bas said. Rather than putting every query through ChatGPT, conscious computing principles would urge people to consider whether there’s a more specialized or simple option for the task. Browser plug-ins like Carbon Scaledown can track GPT-related emissions.
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