By Lauren Leffer
It might seem like magic. Type a request into ChatGPT, click a button and — presto! — here’s a five-paragraph analysis of Shakespeare’s Hamlet and, as an added bonus, it’s written in iambic pentameter. Or tell DALL-E about the chimeric animal from your dream, and out comes an image of a gecko-wolf-starfish hybrid. If you’re feeling down, call up the digital “ghost” of your deceased grandmother and receive some comfort (SN: 6/15/24, p. 10).
Despite how it may appear, none of this materializes out of thin air. Every interaction with a chatbot or other generative AI system funnels through wires and cables to a data center — a warehouse full of server stacks that pass these prompts through the billions (and potentially trillions) of parameters that dictate how a generative model responds.
Processing and answering prompts eats up electricity, as does the supporting infrastructure like fans and air conditioning that cool the whirring servers. In addition to big utility bills, the result is a lot of climate-warming carbon emissions. Electricity generation and server cooling also suck up tons of water, which is used in fossil fuel and nuclear energy production, and for evaporative or liquid heat dissipation systems.
This year, as the popularity of generative AI continued to surge, environmentalists sounded the alarm about this resource-hungry technology. The debate over how to weigh the costs against the less tangible benefits that generative AI brings, such as increased productivity and information access, is steeped in ideological divisions over the purpose and value of technology.
For decades before the generative AI boom, efficiency gains have compensated for the growing energy demand that’s come with expansions in data centers and computing, says Andrew Chien, a computer scientist at the University of Chicago. That’s changed. By the end of 2020, data center expansion began to outpace efficiency improvements, he says. Both Google’s and Microsoft’s self-reported energy usage more than doubled between 2019 and 2023. ChatGPT’s release at the end of 2022 kick-started a generative AI frenzy — exacerbating the issue, Chien says. Before 2022, total energy demand in the United States had been stable for about 15 years. Now it’s rising.
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