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Title Data-and AI-driven Economic Growth in a General Equilibrium Model
Author Kyu yub Lee, Hyun Park
Date 2020-02-06
File WEB 20-04.pdf 

We attempt to characterize a data- and AI-driven economy and establish a general equilibrium growth model in order to describe the data economy and examine how data and AI can affect the economy in the long run.

To sum up, this article provides three policy implications. First, the authority should have a balanced view between privacy protection and data usage in economy-wide technology in terms of long-run growth. Privacy should not be considered only as utility loss, but must be considered as a contributor to loss in growth rates. Second, economic growth can be achieved by using higher amounts of data as well as continuous development in AI technology. A caveat is that AI-technology can boost economic growth only when it applies to all industries as general purpose technology. Lastly, the authorities should keep considering how to deal with new issues that include data ownership, outlaw data sharing, data market, AI bias, and so forth. Our model can be used as a starting point to such examinations.