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Jevons Paradox

The 1865 observation by William Stanley Jevons that efficiency improvements in coal-fired engines increased rather than decreased total coal consumption — the dynamic that converts AI efficiency gains into throughput expansion rather than ecological space.

The Jevons paradox, first articulated in The Coal Question (1865), is the empirical observation that efficiency improvements in the use of a resource often produce increased rather than decreased total consumption. Jevons noticed that steam engines had become dramatically more efficient over the preceding century, yet British coal consumption had risen, not fallen. His explanation: cheaper energy per unit of work made new applications economically viable, and the total demand generated by the new applications exceeded the savings from the efficiency improvement.

Jevons Paradox
Jevons Paradox

In The You On AI Field Guide

The paradox operates across domains with remarkable consistency. Computing hardware has become vastly more efficient per operation since the 1960s; total computing energy consumption has risen, not fallen. LED lighting is dramatically more efficient than incandescent; total lighting-related electricity consumption has risen, not fallen. The efficiency gains are captured by growth logic and converted into more throughput rather than less resource use.

Applied to AI, the dynamic is direct. Each generation

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