AI Vocabulary · 08 Rules & Responsibility

What is Rebound Effect (Jevons Paradox)?

When efficiency makes something cheaper to use, people use more of it, so total consumption can rise.

Intermediate

In the 19th century, the economist William Stanley Jevons observed that using coal more efficiently increased Britain's total coal consumption, because coal became worth using in more places. This is the rebound effect. Researchers distinguish a direct rebound, more use of the same product, from indirect and economy-wide effects, where savings are spent elsewhere or a whole technology spreads.

AI shows the pattern clearly. Google reports that the energy per prompt of its Gemini app fell 33-fold in one year. In the same period, the International Energy Agency counted about 17% more electricity use by data centres worldwide in 2025 and about 50% more in AI-focused data centres. Sasha Luccioni, Emma Strubell and Kate Crawford argue that efficiency gains in AI therefore give no guarantee of a smaller footprint.

Why it matters for you

Falling prices per token make new uses of AI affordable, and that is good for builders. It also means that per-query efficiency claims answer a different question from total impact. Both belong in an honest picture.

Own it

When you judge the footprint of an AI feature, look at the total: energy per task times the number of tasks. A cheaper model that you call ten times as often may use more energy than before. Track your cost per task and your volume together.

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