Our new article in Joule titled "To better understand AI’s growing energy use, analysts need a data revolution" was published online at Joule today

Our new article in Joule on data needs for understanding AI electricity use came out online today in Joule (link will be good until October 8, 2024). Here’s the summary section:

As the famous quote from George Box goes, “All models are wrong, but some are useful.” Bottom-up AI data center models will never be a perfect crystal ball, but energy analysts can soon make them much more useful for decisionmakers if our identified critical data needs are met. Without better data, energy analysts may be forced to take several shortcuts that are more uncertain, less explanatory, less defensible, and less useful to policymakers, investors, the media, and the public.
Meanwhile, all of these stakeholders deserve greater clarity on the scales and drivers of the electricity use of one of the most disruptive technologies in recent memory. One need only look to the history of cryptocurrency mining as a cautionary tale: after a long initial period of moderate growth, mining electricity demand rose rapidly. Meanwhile, energy analysts struggled to fill data and modeling gaps to quantify and explain that growth to policymakers—and to identify ways of mitigating it—especially at local levels where grids were at risk of stress.
The electricity demand growth potential of AI data centers is much larger, so energy analysts must be better prepared. With the right support and partnerships, the energy analysis community is ready to take on the challenges of modeling a fast moving and uncertain sector, to continuously improve, and to bring much-needed scientific evidence to the table. Given the rapid growth of AI data center operations and investments, the time to act is now.“

I worked with my longtime colleagues Eric Masanet and Nuoa Lei on this article.