The impact of intelligent automation on subjective well-being and job satisfaction: A comparison between standard and nonstandard employment

Abstract

The accelerating global adoption of intelligent automation (IA) technologies is fundamentally transforming economic structures and reshaping individual lifestyles. Despite intense debate regarding the societal impacts of IA, including both beneficial and adverse effects, empirical evidence on its net influence on multidimensional well-being outcomes remains scarce. Drawing on a nationally representative dataset from China (2018–2020), we employed multilevel probit models with instrumental variables to investigate how IA influences subjective well-being (SWB) and job satisfaction (JS), differentiating between standard and nonstandard employment contexts. Our findings revealed distinct nonlinear relationships: an inverted U-shaped pattern between IA and SWB, versus a U-shaped relationship between IA and JS, with turning points above the 35th and 80th percentiles of IA intensity distribution, respectively. These contrasting trajectories suggest that IA’s impacts vary considerably between consumption utility and production utility domains. The results demonstrate significant heterogeneity in the well-being effects of IA across different forms of employment. Specifically, within standard employment arrangements, IA exerts strong marginal diminishing effects on JS, though with an earlier turning point as IA intensity increases. Moreover, our counterfactual decomposition analysis verifies that IA contributes to narrowing the overall SWB and JS gaps between standard and nonstandard forms of employment by approximately 13% and 19%, respectively. Our mediation analysis identified three distinct transmission mechanisms — psychological factors, social interactions, and structural inequality — through which IA influences well-being, with mental exhaustion and actual inequality accounting for 38% and 30% of the total negative effect of IA on JS, respectively. These findings suggest that policy interventions would ensure balanced technological integration to maximize technology’s welfare benefits while mitigating its polarizing tendencies. This study provides important implications for understanding how technological transformation shapes human well-being across increasingly segmented global labor markets.