Il futuro del lavoro nel settore automobilistico: un'analisi brevettuale

The rapid development of advanced digital technologies is fundamentally transforming labor dynamics across all sectors. This master thesis aims to contribute to the ongoing debate on the impact of technological adoption on labor dynamics in the automotive industry which is currently facing its most profound transformation given technological changes and a radical transition towards electric mobility. By utilizing natural language processing techniques on full-text patents between 2010-2023, this study addresses how does the integration of advanced automation and digital technologies is leading to labor-saving efforts within the automotive sector, and what are the implications for the job dynamics in this industry. Our main findings suggest that, within the period under study, the direct claiming of labor-saving heuristics represents a relatively small proportion of the overall patent activity. Among the identified labor-saving patents, there are two periods with more concentration (2010-2013 and 2019-2022) where is possible to identify a shift from advanced manufacturing technologies and cloud computing for data collection to artificial intelligence and advanced robotics. A more detailed identification of technologies within labor- saving patents highlights the heterogeneity of their impact on labor. While robotics and 3d manufacturing are mainly used to automate repetitive tasks, reduce manual intervention, and improve overall efficiency in manufacturing operations, artificial intelligence and cloud computing focus on automating decision-making processes. The qualitative analysis of the texts allows the identification of a smaller subset of labor-saving patents related to green technologies, predominantly focusing on the enhance of operational efficiency.