If you’ve been following technology news recently, you’ve probably noticed a sudden increase in references to a 19th-century economics theory called the Jevons Paradox, which is named for the neoclassical economist William Stanley Jevons, and captures the observation that increasing the efficiency of a resource can lead to greater consumption.
Jevons first articulated this idea in an 1865 book, pithily titled, The Coal Question: An Inquiry Concerning the Progress of the Nation, and the Probable Exhaustion of Our Coal-Mines. He argued that building more efficient steam engines – ones that required less fuel to generate the same power – would not solve the problem of England’s diminishing coal supplies. If you made the engines more efficient, Jevons predicted, people would find more applications for steam power, and even more coal would be burned overall.
This is indeed what happened. (At least, the part about increased coal consumption. The feared coal shortage was averted through new mining techniques.)
The Jevons Paradox is popular again because it provides a useful frame for understanding the potential impact of AI on jobs. Many fear that this technology will make workers so efficient that the labor market will shrink. If one programmer can now do the work of five, then companies will fire 80% of their programmers!
The Jevons Paradox implies the opposite might occur. If you make workers more efficient, their output will become cheaper, and the demand for their services might grow. If one programmer can now do the work of five, the effective cost of creating software will become so cheap that many more individuals and organizations will now pay to develop their own tools and applications.
This is a fascinating prediction that’s worth keeping an eye on. (For a deeper dive into the counterintuitive economics of AI, I recommend Derek Thompson’s recent interview with Alex Imas.) But there’s also a darker side to the Jevons Paradox that hasn’t been discussed as much recently: suddenly increasing demand for a resource can create unexpected negative side effects.
More efficient steam engines, for example, led to soot-stained buildings and the smoky start to the era of human-driven climate change. More recently, in the context of knowledge work, the arrival of digital communication tools such as email and Slack created similar unanticipated problems. By making communication significantly more efficient, the demand for fast interaction exploded, leading to our current moment in which the average knowledge worker is now interrupted once every two minutes. (For more on how this descent into communication madness occurred, check out my 2021 bestseller, A World Without Email.)
If AI ends up making certain types of workers more efficient, I hope the Jevons Paradox holds, as it’s better than the alternative of labor market contraction. But we need to remain vigilant about its side effects. It’s tempting to assume that increasing efficiency, in any context, can only make things better, but economic history has often told a more complicated tale.
