This paper studies the effects of automation in economies with labor market distortions that generate worker rents—wages above opportunity cost—in some jobs. We show that automation targets high-rent tasks, dissipating rents and amplifying wage losses from automation. It also reduces within-group wage dispersion for exposed groups. Automation-driven rent dissipation is inefficient and reduces (and could even negate) the productivity gains from automation. Using data for the US from 1980 to 2016, we find evidence of sizable rent dissipation and reduced within-group wage dispersion due to automation. Using these estimates and accounting for equilibrium effects, we estimate that automation accounts for 52% of the increase in between group inequality in the US since 1980, with rent dissipation being responsible for a fifth of this contribution. We also estimate that inefficient rent dissipation offset 60–90% of the productivity gains from automation since 1980.

Automation and technological advancements have fundamentally reshaped the labor market, raising the sea level and transforming the landscape of human faculties and machine capabilities. These developments brought gains to society but came at the expense of displaced workers, who often experienced reduced employment opportunities and real wages. Mitigating losses associated with such disruptions while minimizing efficiency losses is a key policy challenge now more relevant due to the development of AI and LLMs capable of automating many more tasks previously considered safe. In the near term, targeted transfers provide the best way of dealing with such disruptions. Pre-distribution and taxes on automation technologies can provide a reasonable substitute for dealing with localized disruptions when targeted transfers are not feasible. Redistribution via the income tax system can help, but it might be too coarse to deal with localized disruptions. Active labor market policies can help, too, but fail to protect the most vulnerable workers: those left behind.