Venue: Aula, Minderbroedersberg 4-6, Maastricht
online: https://www.youtube.com/@UMphddefense
In recent decades, the enthusiasm to understand the effects of the proliferation of novel automation technologies has heightened amidst rapid advancements in technologies such as Artificial Intelligence (AI) and robotics. Given that, historically, the use of automation has been associated with economic growth, technological unemployment, and structural changes in the labour market resulting in inequality, the present debate reflects both high expectations and deep concerns and will likely persist as these technologies evolve and advance.
Key questions raised include whether modern automation will result in higher productivity growth gains than earlier automation waves and through what channels the expected gains would be realized. Other questions have been more concerned with identifying the group of workers who are at higher or lower risk of displacement through automation. From a global viewpoint, questions have also emerged regarding whether the developing world would be adversely impacted through trade with the advanced world, as the latter adopts automation and returns previously offshored production activities from the former. This thesis focuses on addressing these questions using modern quantitative techniques.