Tech tycoons have got the economics of AI wrong – Crypto News

Even as economic growth was just taking off, some economists were already pessimistic. Coal, wrote William Stanley Jevons in 1865, is “the mainspring of modern material civilisation”. Yet it was finite and would soon run out. Although more could be found by digging deeper, it would be increasingly expensive to extract and these higher costs would reduce the competitiveness of Britain’s manufacturers. After all, in other countries the black fuel was still in sight of daylight. Efficiency gains—using less coal to produce the same amount of stuff—would not save the country. Indeed, cleverer use of limited resources would simply provide an incentive to burn even more coal, which would, paradoxically, lead to an even faster use of British reserves. There was no escape, the Victorian economist believed. Coal would be exhausted and the country was likely to “contract to her former littleness”.

The Jevons paradox—the idea that efficiency leads to more use of a resource, not less—has in recent days provided comfort to Silicon Valley titans worried about the impact of DeepSeek, the maker of a cheap and efficient Chinese chatbot, which threatens the more powerful but energy-guzzling American varieties. Satya Nadella, the boss of Microsoft, posted on X, a social-media platform, that “Jevons paradox strikes again! As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can’t get enough of,” along with a link to the Wikipedia page for the economic principle. Under this logic, DeepSeek’s progress will mean more demand for data centres, Nvidia chips and even the nuclear reactors that the hyperscalers were, prior to the unveiling of DeepSeek, paying to restart. Nothing to worry about if the price falls, Microsoft can make it up on volume.

The logic, however self-serving, has a ring of truth to it. Jevons’s paradox is real and observable in a range of other markets. Consider the example of lighting. William Nordhaus, a Nobel-prizewinning economist, has calculated that a Babylonian oil lamp, powered by sesame oil, produced about 0.06 lumens of light per watt of energy. That compares with up to 110 lumens for a modern light-emitting diode. The world has not responded to this dramatic improvement in energy efficiency by enjoying the same amount of light as a Babylonian at lower cost. Instead, it has banished darkness completely, whether through more bedroom lamps than could have been imagined in ancient Mesopotamia or the Las Vegas sphere, which provides passersby with the chance to see a 112-metre-tall incandescent emoji. Urban light is now so cheap and so abundant that many consider it to be a pollutant.

Likewise, more efficient chatbots could mean that AI finds new uses (some no doubt similarly obnoxious). The ability of DeepSeek’s model to perform about as well as more compute-hungry American AI shows that data centres are more productive than previously thought, rather than less. Expect, the logic goes, more investment in data centres and so on than you did before.

Although this idea should provide tech tycoons with some solace, they still ought to worry. The Jevons paradox is a form of a broader phenomenon known as “rebound effects”. These are typically not large enough to fully offset savings from improved efficiency. Usually they are examined by academics and policymakers keen to use less energy: environmental worries about peak coal turned into worries about peak oil and then into worries about greenhouse gases. Sometimes the effect is straightforward: tighter fuel standards, designed to lower emissions, lead American drivers to travel longer distances. Sometimes it is less direct: better-insulated houses have increased the size of windows in Europe, offsetting efficiency gains. Sometimes it is macroeconomic: less energy use by one industry frees up supply for another. The Jevons paradox occurs when the sum of all the rebounds is larger than the initial energy savings—and it is really quite rare.

How confident should Mr Nadella be that AI will turn out to be one of the instances where the Jevons paradox applies? The overall size of a rebound effect ultimately depends on the structure of demand: if the good in question can easily substitute for others, then the bounce-back will be bigger. If it is a luxury good—one for which demand rises faster than income—then again there will be more of a rebound effect. Cristina Peñasco and Laura Díaz Anadón of the University of Cambridge have looked at home insulation in Britain and found that the rebound effect is also more significant for poorer households than richer ones, since richer ones are already closer to their desired temperatures.

Got the morbs

Basing the bull case for AI on the Jevons paradox is, therefore, a bet not on the efficiency of the technology but on the level of demand. If adoption is being held back by price then efficiency gains will indeed lead to greater use. If technological progress raises expectations rather than reduces costs, as is typical in health care, then chatbots will make up an ever larger proportion of spending. At the moment, that looks unlikely. America’s Census Bureau finds that only 5% of American firms currently use AI and 7% have plans to adopt it in the future. Many others find the tech difficult to use or irrelevant to their line of business.

“Coal in truth stands not beside but entirely above all other commodities,” Jevons wrote in 1865. “It is the material energy of the country—the universal aid—the factor in everything we do. With coal almost any feat is possible or easy.” His paradox applied to the black fuel because it was energy that was the fundamental driving force of the industrial economy. For the moment, at least, the tools produced by hyperscalers are nothing of the sort. The intended message of Mr Nadella’s tweet was not subtle: don’t sell your Microsoft stock. He may have been right, but that would have been for reasons other than the Jevons paradox.

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