The impact of workplace automation on workers’ happiness remains theoretically ambiguous, with conflicting predictions about its subjective wellbeing consequences. This study resolves this issue through a systematic analysis using nationally representative data from the Chinese General Social Survey. Five hypotheses derived from three dimensions of automation’s effects are tested, revealing the following core findings. First, workplace automation exerts a significant negative net effect on workers’ happiness and this finding remains robust across various robustness and endogeneity tests. Second, the analysis uncovers mechanisms operating in opposite directions: automation undermines subjective well-being by decreasing income, diminishing future expectations and increasing perceived unfairness, while enhancing it through reduced working hours and expanded leisure activities. Overall, automation’s net effect on workers’ happiness is negative. Third, automation’s impacts exhibit pronounced heterogeneity, disproportionately affecting vulnerable subgroups. Its adverse influence is more pronounced among individuals who are older, female, lower educated, with poorer self-rated health, without social security, non-homeowners, non-migrants, non-unionized workers, as well as those employed outside the primary labor market. Additionally, people in regions with a higher cost of living, weaker labor protection, and fewer unions are more vulnerable to this technological disruption. Findings of this research support the skill-biased technological change theory and highlight that higher levels of human capital, better social security and stronger labor protections help to mitigate automation’s adverse impacts on workers’ happiness. In the context of the new technological revolution of automation, this research has important policy implications on how to scientifically address the challenges posed to workers’ happiness.
Li et al. (Sun,) studied this question.