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This paper investigates the presence of explicit labour-saving heuristics within robotic patents. It analyses innovative actors engaged in robotic technology and their economic environment (identity, location, industry), and identifies the technological fields more exposed to labour-saving innovations. It exploits advanced natural language processing and probabilistic topic modelling techniques applied to the universe of USPTO patent applications between 2009 and 2018, matched with the ORBIS (Bureau van Dijk) firm-level dataset. The results show that labour-saving patent holders comprise not only robot producers, but mainly adopters. Consequently, labour-saving robotic patents appear along the entire supply chain. Additionally, labour-saving innovations are directed towards manual activities in services (e.g. in the logistics sector), activities entailing social intelligence (e.g. in the healthcare sector) and cognitive skills (e.g. learning and predicting).
Montobbio et al. (Sat,) studied this question.