"AI, and especially generative AI such as Large Language Models (LLMs) and other tools that can generate videos and images, brings up strong views and increasingly urgent concerns ...
It’s important to note that AI is not the same thing as data centres. About a third of current data centre capacity is used for AI: the rest supports the many other ways we also use data every day, from accessing our household bills online to watching our favourite show...
Today, as this Nature Climate Action perspective explains in detail, there are numerous ways that AI can help accelerate the low-carbon transition, if used wisely and well. This includes optimizing power grids, catalyzing behavioural change, and improving climate and policy modeling ...Obviously, though, it would be much better for all our data and AI needs to be powered by renewable energy: and a brand new report by the Union of Concerned Scientists shows how smart policy could put that goal within reach...
Although AI only accounts for about a third of current data centre usage, it’s much less efficient: and rather than increasing its efficiency, companies are just building more. Not only is this driving a massive increase in electricity demand, but the energy the data centres are relying on is mostly fossil fuels. In the U.S., for example, data centres’ energy is nearly 50% more carbon-intensive than the grid. And of course these servers, infrastructure, and cooling systems require large amounts of fresh water as well...
The real environmental issue with all of this is not that we use energy, data, and even AI. They aren’t inherently bad in and of themselves. What determines their impact is how they’re created, how they’re used, and what powers them. And right now, there’s no question that much new AI technology is using energy inefficiently and operating with no transparency or oversight, and with no regard to its harmful side effects."
