Speed of Catch-up and Convergence of the Artificial Intelligence Divide: Robotic and Patents

Gachon Center of Convergence Research Working Paper Series 2022-02

35 Pages Posted: 9 Jul 2022 Last revised: 24 Aug 2022

See all articles by Yu Sang Chang

Yu Sang Chang

Gachon University - College of Business and Economics

Seongmin Jeon

Gachon University - College of Business and Economics

Sung Jun Jo

Gachon University - College of Business and Economics

Young Eun Kim

Gachon University - College of Business

Date Written: April 22, 2022

Abstract

This study examined the dynamics of the AI divide on robotics and AI patents from 42 to 57 countries grouped in the two subgroups of income and AI adoption levels. The most important finding is that for robotics, a very large relative AI divide which existed at the beginning year between the leading and lagging countries has narrowed very rapidly. The relative AI divide between the high- and middle-income subgroups at the beginning has also narrowed at a rapid pace. In contrast, a smaller relative AI divide existing at the beginning for patents experienced significantly slower pace of narrowing relative digital divide.

The theory of convergence applies extremely well so that widely variable initial relative divides at the beginning year in the study period are related to the variable annual speed of catch-up rates, which, in turn, are associated with the different annual reduction rates of the relative divide.

In contrast, actual penetration numbers of robotics and patents are substantially higher by the top nine leading countries over the bottom line lagging countries as well as by the high income countries over the middle income countries. Furthermore, these actual higher penetration numbers continued to increase in spite of continuous reduction of relative digital divide. Thus, multiple years will still be needed to equalize the varying levels on the actual number of AI adoption between the leading and lagging subgroups of countries as well as between the high- and middle-income subgroups of countries.

In terms of the micro convergence analysis of AI divides for individual countries within the respective income and adoption subgroups, active ranking changes among countries occurred in nearly all the subgroups. In general, reduction rates of relative AI divide from macro analysis were supported by rapid ranking changes among individual countries from micro analysis.

Keywords: Speed of catch-up, convergence, artificial intelligence divide, robotic, patents, relative ai divide, absolute ai divide

Suggested Citation

Chang, Yu Sang and Jeon, Seongmin and Jo, Sung Jun and Kim, Young Eun, Speed of Catch-up and Convergence of the Artificial Intelligence Divide: Robotic and Patents (April 22, 2022). Gachon Center of Convergence Research Working Paper Series 2022-02 , Available at SSRN: https://ssrn.com/abstract=4140776 or http://dx.doi.org/10.2139/ssrn.4140776

Yu Sang Chang (Contact Author)

Gachon University - College of Business and Economics ( email )

Korea

Seongmin Jeon

Gachon University - College of Business and Economics ( email )

1342 Seongnamdaero
Sujeong-gu
Seongnam, Gyeonggi 461-701
Korea

Sung Jun Jo

Gachon University - College of Business and Economics ( email )

Korea

Young Eun Kim

Gachon University - College of Business ( email )

1342 Seongnam-daero, Sujeong-gu, Seongnam-si
Seongnam, Gyeinggi-do
Korea, Republic of (South Korea)

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