Robots and the origin of their labour-saving impact
Fabio Montobbio, Jacopo Staccioli, E. Virgillito & Marco Vivarelli
#2020-007
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
particularly exposed to labour-saving innovations. It exploits advanced
natural language processing and probabilistic topic modelling techniques
on the universe of patent applications at the USPTO between 2009 and
2018, matched with ORBIS (Bureau van Dijk) firm-level dataset. The
results show that labour-saving patent holders comprise not only robots
producers, but also adopters. Consequently, labour-saving robotic
patents appear along the entire supply chain. The paper shows that
labour-saving innovations challenge manual activities (e.g. in the
logistics sector), activities entailing social intelligence (e.g. in the
healthcare sector) and cognitive skills (e.g. learning and predicting).
JEL Classification: O33, J24, C38
Keywords: Robotic Patents, Labour-Saving Technology, Search Heuristics, Probabilistic Topic Models