Documents Giuntella, Osea 4 results

"This study explores the relationship between artificial intelligence (AI) and workers' well being and health using longitudinal survey data from Germany (2000–2020). Using a measure of occupational exposure to AI, we explore an event study design and a difference-in-differences approach to compare AI-exposed and non-exposed workers. Before AI became widely available, there is no evidence of differential pretrends in workers' well-being and health. We find no evidence of a sizeable negative impact of AI on workers' well-being and mental health. If anything, there is evidence of an improvement in health status and health satisfaction, which may be explained by the decline in job physical intensity. Overall, our results are consistent with the lack of negative effects of AI on the labor markets."

This work is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

"A handful of studies have investigated the effects of robots on workers in advanced economies. According to a recent report from the World Bank (2016), 1.8 billion jobs in developing countries are susceptible to automation. Given the inability of labor markets to adjust to rapid changes, there is a growing concern that the effect of automation and robotization in emerging economies may increase inequality and social unrest. Yet, we still know very little about the impact of robots in developing countries. In this paper we analyze the effects of exposure to industrial robots in the Chinese labor market. Using aggregate data from Chinese prefectural cities (2000-2016) and individual longitudinal data from China, we find a large negative impact of robot exposure on employment and wages of Chinese workers. Effects are concentrated in the state-owned sector and are larger among low-skilled, male, and prime-age and older workers. Furthermore, we find evidence that exposure to robots affected internal mobility and increased the number of labor-related strikes and protests."

"This study explores the relationship between the adoption of industrial robots and workplace injuries using data from the United States (US) and Germany. Our empirical analyses, based on establishment-level data for the US, suggest that a one standard deviation increase in robot exposure reduces work-related injuries by approximately 16%. These results are driven by manufacturing firms (-28%), while we detect no impact on sectors that were less exposed to industrial robots. We also show that the US counties that are more exposed to robot penetration experience a significant increase in drug- or alcohol-related deaths and mental health problems, consistent with the extant evidence of negative effects on labor market outcomes in the US. Employing individual longitudinal data from Germany, we exploit within-individual changes in robot exposure and document similar effects on job physical intensity (-4%) and disability (-5%), but no evidence of significant effects on mental health and work and life satisfaction, consistent with the lack of significant impacts of robot penetration on labor market outcomes in Germany."

"This study explores the relationship between artificial intelligence (AI) and workers' well-being and mental health using longitudinal survey data from Germany (2000-2020). We construct a measure of individual exposure to AI technology based on the occupation in which workers in our sample were first employed and explore an event study design and a difference-in-differences approach to compare AI-exposed and non-exposed workers. Before AI became widely available, there is no evidence of differential pre-trends in workers' well-being and concerns about their economic futures. Since 2015, however, with the increasing adoption of AI in firms across Germany, we find that AI-exposed workers have become less satisfied with their life and job and more concerned about job security and their personal economic situation. However, we find no evidence of a significant impact of AI on workers' mental health, anxiety, or depression."