This paper examines the impact of industrial robot usage on US labor markets from 1990 to 2007. Using a model that captures the competition between robots and human labor in different tasks, the authors estimate that robots can reduce employment and wages. The local labor market effects of robots are estimated by regressing changes in employment and wages on the exposure to robots, defined as the sum of the national penetration of robots in each industry times the baseline employment share of that industry. The empirical analysis focuses on commuting zones in the United States, where the measure of exposure to robots is constructed using data from the International Federation of Robotics (IFR) on robot usage and baseline employment shares from the Census. The authors use an instrumental variables strategy, leveraging the spread of robots in other advanced economies as an instrument for robot adoption in the US. The results show that the increase in the stock of robots (approximately one new robot per thousand workers) reduced the employment-to-population ratio by 0.37 percentage points and wages by 0.73 percent in commuting zones with average US exposure to robots. The negative effects are significant and robust, even after controlling for other factors such as industry composition, demographics, and exposure to imports from China and Mexico. The authors also find that the effects are more pronounced in manufacturing, routine manual occupations, and for workers with less than a college education.This paper examines the impact of industrial robot usage on US labor markets from 1990 to 2007. Using a model that captures the competition between robots and human labor in different tasks, the authors estimate that robots can reduce employment and wages. The local labor market effects of robots are estimated by regressing changes in employment and wages on the exposure to robots, defined as the sum of the national penetration of robots in each industry times the baseline employment share of that industry. The empirical analysis focuses on commuting zones in the United States, where the measure of exposure to robots is constructed using data from the International Federation of Robotics (IFR) on robot usage and baseline employment shares from the Census. The authors use an instrumental variables strategy, leveraging the spread of robots in other advanced economies as an instrument for robot adoption in the US. The results show that the increase in the stock of robots (approximately one new robot per thousand workers) reduced the employment-to-population ratio by 0.37 percentage points and wages by 0.73 percent in commuting zones with average US exposure to robots. The negative effects are significant and robust, even after controlling for other factors such as industry composition, demographics, and exposure to imports from China and Mexico. The authors also find that the effects are more pronounced in manufacturing, routine manual occupations, and for workers with less than a college education.