Technology, Inequality and Labor Market · APVV-23-0090
Research / Projects
The future of work is a source of controversy. New technologies, advances in automation and digitalization, and the use of AI have the potential to outcompete humans in a wide range of tasks. Evidence so far suggests that massive investments in new technologies have led to long-run productivity gains, yet the gains are so unequally distributed that many workers are left behind, experiencing job insecurity and stagnating wages. Similar pressures from robotics and digitalization had a different impact on local labor markets across developed countries, as institutional differences played a major role in shaping the distribution of benefits.
The project provides new empirical evidence on the effects of different technologies on employment and wage inequality, displacement of workers, and creation of new work, and explores the role of institutions, strategies, and policies in shifting these trends toward an inclusive society and shared prosperity.
Do employment and inequality effects depend on interactions between labor market institutions, economic factors, and technologies? How does task displacement shape wage structures and labor market polarization in Europe?
Can automation explain the growing wedge between labor productivity and wages in European countries? Which technologies complement workers and create new work, and which policies can bring productivity and wages in line again?
How does automation affect vulnerable groups, with a focus on gender, education, and ethnicity? Semi-structured interviews with key policy stakeholders and social partners map their views on the impact of automation.
Translating findings from WP1–WP3 into policy recommendations and disseminating them to policymakers and stakeholders through policy briefs, the project web page, conference sessions, and public events.
Former members: Paulína Borovská, Tomáš Ševček.
Published in Journal for Labour Market Research, 60, Article 5 (2026)
Published in Eurasian Business Review, 15(4), 953–1001 (2025)
New measures of occupational exposure to industrial robots and artificial intelligence, based on the semantic similarity of job task descriptions and technology descriptions, are used to analyze changes in labor and skill demand in the United Kingdom over the past decade. Robot exposure is positively associated with increased demand for skilled workers, while AI exposure is weakly associated with a decline in demand for skilled workers.
Published in Eurasian Business Review, 15, 925–951 (2025)
The impact of AI on employment is neither predetermined nor uniform: it is shaped by the implementation context, organizational choices, and institutional frameworks, with heterogeneity across countries, sectors, firms, and demographic groups calling for adaptive policy responses.
Building on the intersectional framework of vulnerability, the paper provides a conceptual and analytical framework for understanding how automation affects different population subgroups in Slovakia and Czechia, and serves as the basis for semi-structured interviews with stakeholders.
Using an instrumental variable approach for EU manufacturing sectors over 2011–2019, the paper finds that robot adoption reduces both workplace injuries and deaths. The safety benefits materialize only in high-tech sectors and in countries where industrial relations provide strong worker protection.
A model of production in the age of automation with emission externalities predicts that robot use raises emissions on average, that the effect weakens as robots become more efficient, and that robots can reduce emissions where electricity comes mainly from renewable sources. The empirical analysis supports these predictions.
The research data center at the Department of Economic Policy was completed and extended in 2025 (internal drives, cooling, authentication tokens). Three primary computers are in operation, providing approximately 100 TFLOPS with 128 GB RAM, 80 TFLOPS with 64 GB RAM, and 30 TFLOPS with 32 GB RAM — a stable technical base for big data, numerical optimization, and local language models.
Occupational exposure to robotics, software and artificial intelligence, built from the cosine similarity between patent texts and occupational task descriptions and aggregated at the occupation level, for the ISCO-08 and UK SOC 2010 classifications.
Summer roundtable on automation, AI, and the future of work in Europe. Wednesday, July 2, 2026, 9:00 a.m.–1:30 p.m., Department of Economic Policy (room 4B.26), Faculty of Economics and Finance, Bratislava University of Economics and Business.
This project has received funding from the Slovak Research and Development Agency (APVV) under the General Call 2023, Grant Agreement APVV-23-0090.