Algorithms at Work: Assessing the Socio-Economic Impacts of Automation on Skilled Labor
Gabriele Moretti1, Beatrice Santoro2
1 Department of Economics, University of Milan, Italy | 2 Institute for Advanced Technological Research, Turin, Italy
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Abstract
The rapid proliferation of artificial intelligence, machine learning algorithms, and advanced robotics across industrial and service sectors has sparked intense scholarly debate concerning the future of human labor. This article investigates the structural mechanisms through which algorithmic automation reconfigures job tasks, wage polarization, and skill demands among professional workers in contemporary advanced economies. Drawing upon comprehensive empirical datasets from European manufacturing and financial hubs between 2012 and 2016, the authors deploy econometric task-model analysis to evaluate net employment shifts. Our findings indicate that while routine cognitive and manual tasks experience substantial displacement, non-routine creative and interpersonal roles exhibit robust complementarity with digital technologies. Furthermore, the research reveals significant regional disparities in adaptation capacity, heavily mediated by local vocational training infrastructure and institutional flexibility. We argue that mitigating the adverse distributional consequences of automation requires proactive public policies centered on lifelong educational modularity, portable social safety nets, and cooperative tripartite governance between labor unions, enterprises, and state authorities.