Automation and related technologies: a mapping of the new knowledge base

Abstract

Using the entire population of USPTO patent applications published between 2002 and 2019, and leveraging on both patent classification and semantic analysis, this paper aims to map the current knowledge base centred on robotics and AI technologies. These technologies are investigated both as a whole and distinguishing core and related innovations, along a 4-level core-periphery architecture. Merging patent applications with the Orbis IP firm-level database allows us to put forward a twofold analysis based on industry of activity and geographic location. In a nutshell, results show that: (i) rather than representing a technological revolution, the new knowledge base is strictly linked to the previous technological paradigm; (ii) the new knowledge base is characterised by a considerable -but not impressively widespread -degree of pervasiveness; (iii) robotics and AI are strictly related, converging (particularly among the related technologies and in more recent times) and jointly shaping a new knowledge base that should be considered as a whole, rather than consisting of two separate GPTs; (iv) the US technological leadership turns out to be confirmed (although declining in relative terms in favour of Asian countries such as South Korea, China and, more recently, India).JEL classification: O33.

Identifying and characterising AI adopters

“…Indeed, when replicating the same heat map but using job postings' location information available for the subset of Lightcast™ firms, patterns remain qualitatively similar. 27 This is also in line with previous findings relying solely on job postings data (Samek, Squicciarini and Cammeraat, 2021 [25]) and is not unexpected, considering United Kingdom's concentration of economic activity in those identified regions, in particular in ICT and services (OECD, 2022 [37]) and its unequal distribution of skills across different geographical areas (OECD, 2020 [38]).…”

“…In fact, AI-related IPRs tend to be available across several countries; with patenting rates highest in the United States followed by Japan, Korea and the People's Republic of China (Dernis et al, 2021[18]). Information from company websites can, in principle, be retrieved beyond the United Kingdom (see, for instance, Kinne and Axenbeck's (2019 [32]) study on innovation in firms from company websites) whereas information on AI talent from job postings is already available for a number of Anglo-Saxon and European countries (Squicciarini and Nachtigall, 2021 [24]; Samek, Squicciarini and Cammeraat, 2021 [25]; Pouliakas, 2021 [33]; Acemoglu et al, 2022[34]). Orbis covers a wide range of countries, although the representativeness of the data differs significantly across them (see Bajgar et al (2020[31]) for further discussion).…”

“…While this sector accounts for a relatively small share of the economy (around 10%), AI adopters appear particularly concentrated in this sector. 25 This is followed by professional and scientific activities (ISIC Rev.4 69-75), which account for about 21% of AI adopters. Focusing on different groups of adopters (Figure 4.2) provides additional interesting insights, which are also relevant to keep in mind when interpreting the rest of this characterisation section.…”

“…7 The ongoing debate discusses more and more AI's role in changing labour and skills demand (Bessen, 2019[51]; Samek, Squicciarini and Cammeraat, 2021 [25]; Georgieff and Hyee, 2021 [56]; Acemoglu et al, 2022[34]), its impact on facilitating prediction and innovation (Agrawal, Gans and Goldfarb, 2018 [53]; Cockburn, Henderson and Stern, 2018 [52]; Gierten et al, 2021 [58]), and its potential to tackle societal challenges such as climate change. These issues are beyond the scope of the present analysis.…”

The Empirics of Technology, Employment and Occupations: Lessons Learned and Challenges Ahead

“…Despite the expectations of a new disruptive paradigm, forecasts were anything but dire and some studies started instead to put into an historical perspective both the debate and the fears of technological unemployment as a recurrent theme throughout the history of capitalism (Cetrulo and Nuvolari, 2019;Staccioli and Virgillito, 2021), from Luddism onward. Empirical research has grown identifying the extent to which the content of the new technological paradigm is in fact revolutionary or not (Lee and Lee, 2021;Martinelli et al, 2021;Santarelli et al, 2022). These studies emphasise the patterns of continuity of the fourth industrial revolution in terms of knowledge bases, rather than the emergence of a discontinuity.…”