The Jevons Paradox of Labor: How AI Is Making Us Work More

The essay explores the unexpected consequence of AI-driven productivity increases: instead of freeing us, it's leading to a 'labor rebound effect,' where increased efficiency paradoxically leads to more work. This is driven by factors like the soaring opportunity cost of leisure, the creation of new work categories, and intensified competition. The author argues that we need to redefine our metrics of progress, shifting from a singular focus on efficiency to a broader consideration of human well-being, to avoid a 'Malthusian trap.' Examples of alternative metrics include employee time sovereignty, well-being indices, and impact depth. Ultimately, the article suggests that in an AI-powered world, the truly scarce resource is knowing what's worth doing—a deeply personal and subjective question.