PhD defence Nicholas Rounding

“Tasks, Technology and Labour: Empirical Studies on Automation and AI in the Workplace”

This thesis explores the relation between new technologies and work, shedding light on factor allocation, adoption dynamics, and productivity, displacement and reinstatement effects. By combining complementary methodological approaches and data sources, it examines heterogeneous settings, technologies, and affected workers to elucidate the mechanisms through which new technologies affect work. It begins by examining automation technologies, factor allocation and adoption dynamics in the first two chapters, before turning to the reinstating effects of technology in the final two.  Importantly, all the studies in this thesis highlight the importance of the study context and the technologies being studies. Further, it sheds light on how actual AI adoption is affecting workers today, the three empirical chapters investigating AI demonstrate the importance of human labour in the world today, casting doubt on the extent of the ability of current AI tools to fully replace human labour in the near future. Alongside contextual dependence and adoption dynamics, this thesis also highlights the interplay between technological change and within-occupation skill distributions, showing that the returns are greatest for those with the lowest skills.

Supervisors: Prof. dr. Didier Fouarge, Prof. dr. Mark Levels, Prof. dr. Marie-Christine Fregin

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