The future of employment revisited: how model selection affects digitization risks

Abstract

The uniqueness of human labour is at question in times of smart technologies. As computing power and data available increases, the discussion on technological unemployment reawakens. Prominently, Frey and Osborne (Technol Forecast Soc Change 114:254–280, 2017) estimated that half of US employment must be considered exposed to computerization within the next 20 years; followed by a series of papers expanding the research with information on heterogeneous job-specific tasks within the same jobs diminishing digitization potentials to only smaller fractions of workers at high risk. The main contribution of our work is to show that the diversity of previous findings regarding the degree of digitization is additionally driven by model selection. For our case study, we consult experts in machine learning and industry professionals on the susceptibility to digital technologies in the Austrian labour market. Our results indicate that, while clerical computer-based routine jobs are likely to change in the next decade, professional activities, such as the processing of complex information, are less prone to digital change.