The Efficiency Trap: Why Doing More With Less Is Killing Us
William Stanley Jevons must be laughing in his grave. In 1865, he noticed that as steam engines became more efficient at burning coal, England didn't use less coal—it used vastly more. This became known as the Jevons Paradox, and it remains the ultimate middle finger to our modern dreams of "green growth." The logic is simple and brutal: when you make a resource cheaper to use through efficiency, you don't save it; you just find more ways to burn it.
We see this everywhere. We invented LED bulbs that use 90% less energy, so we decided to light up our trees, our building facades, and our driveways all night long. We made car engines more fuel-efficient, so we built massive SUVs and moved to the suburbs to drive longer commutes. Even in the digital realm, 5G and high-speed fiber were supposed to make data "leaner," but instead, we just started streaming 4K cat videos in the shower. Now, in 2026, AI is the ultimate Jevons monster. Every time we optimize a Large Language Model to run on less power, a thousand new startups sprout up to use that "saved" energy for even more mindless automation. We aren't solving the energy crisis; we are just making the fire more efficient at spreading.
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