Abstract
This research attempts to construct a second order observation model in understanding the significance of Artificial intelligence (AI) in changing the global power structure. Because of the inevitable ubiquity of AI in the world societies’ near future, it impacts all the sections of society triggering socio-technical iterative developments. Its horizontal impact and states’ race to become leader in the AI world asks for a vivid understanding of its impact on the international system. To understand the latter, Triple Helix (TH) model along with Shannon’s information entropy has been used to operationalize system’s theory. This model uses Shannon’s information theory to calculate the uncertainty generated from the interactions between the sub-systems considered. Data for the latter has been taken from Sanford Artificial Intelligence Laboratory 2019 report. It is found that European countries are the most effected in the AI era, with probability of losing their global influence and thus creating power void. Emerging powers such as India, Canada, South Africa and Brazil have better chances to fill the void and emerge as global influences.
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Abbreviations
- IE(AP) AP :
-
Information entropy of education (AI patents)
- IE(G) G :
-
Information entropy of constructed global power structure sub domain
- IE(I)I :
-
Information entropy of industry (AI investments)
- IE(I, AP) :
-
Combined information entropy between the industry (AI investments) and education (AI patents) sub systems
- IE(I, G) :
-
Combined information entropy between industry (AI investments) and the constructed global power structure sub systems
- IE(G, AP) :
-
Combined information entropy between constructed global power structure and education (AI patents) sub systems
- IE(G, AP, I) :
-
Combined information entropy between constructed global power structure, education (AI patents), and industry (AI investments) sub systems
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Appendix
Appendix
See Fig.
Impact of Artificial Intelligence. The analysis of the map is done from the vast literature available on the internet. Magazine, online articles have been referred. (Makala and Bakovic. 2020; Bratton2015; Cummings2017; Gill 2020; Lee et al. 2019; Andreu Perez et al. 2016; Julia et al. 2016; Kumar 2019; Malhotra 2021; Niti 2018; Scherer 2016; Future of Life Institute 2021; Pauwels 2019)
3.
The entropy values for the year 2015, 2016, 2017, and 2018 are calculated using the Stanford AI Laboratory 2019 Report. Shannon’s entropy function has been used to calculate the randomness between the two sub-systems and randomness within a subsystem. Detailed calculations will be provided on request (see Table
5,
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7,
8).
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Polcumpally, A.T. Artificial intelligence and global power structure: understanding through Luhmann's systems theory. AI & Soc 37, 1487–1503 (2022). https://doi.org/10.1007/s00146-021-01219-8
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DOI: https://doi.org/10.1007/s00146-021-01219-8