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  5. Democratization, state capacity and developmental correlates of international artificial intelligence trade

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Article
en
2023

Democratization, state capacity and developmental correlates of international artificial intelligence trade

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en
2023
Vol 31 (5)
Vol. 31
DOI: 10.1080/13510347.2023.2259318

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Arhan S Ertan
Arhan S Ertan

Boğaziçi University

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Hamid Akın Ünver
Arhan S Ertan

Abstract

Does acquiring artificial intelligence (AI) technologies from the US or China render countries more authoritarian or technologically less advantageous? In this article, we explore to what extent importing AI/high-tech from the US and/or China goes parallel with importers' (a) democratization or autocratization, (b) state capacity, and (c) technological progress across a decade (2010–2020). Our work demonstrates that not only are Chinese AI/high-tech exports not congruous with importers' democratic backsliding, but autocratization attributed to Chinese AI is also visible in importers of US AI. In addition, for most indicators, we do not observe any significant effect of acquiring AI from the US or China on importers' state capacity or technological progress across the same period. Instead, we find that the story has a global inequality dimension as Chinese exports are clustered around countries with a lower GDP per capita, whereas US high-technology exports are clustered around relatively wealthier states with slightly weaker capacity over territorial control. Overall, the article empirically demonstrates the limitations of some of the prevalent policy discourses surrounding the global diffusion of AI and its contribution to democratization, state capacity, and technological development of importer nations.

How to cite this publication

Hamid Akın Ünver, Arhan S Ertan (2023). Democratization, state capacity and developmental correlates of international artificial intelligence trade. , 31(5), DOI: https://doi.org/10.1080/13510347.2023.2259318.

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Publication Details

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Article

Year

2023

Authors

2

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1080/13510347.2023.2259318

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