Well-Being Analysis on Human Capital Improvement in The Age of Artificial Intelligence

Current article analyzes the relationship between human capital improvement, artificial intelligence, and socioeconomic development. Specifically, it investigates the impact of human capital improvement, general artificial intelligence, and average IQ scores on total reserves. The purpose of this study was to investigate the relationship between various independent variables and the dependent variable, total reserve. The data was analyzed using a multiple regression model in Stata. The results indicated that poverty and GARI were not significant predictors of total reserve. However, there was a significant negative relationship between HCI and total reserve, as well as a significant negative relationship between GAI and total reserve. Additionally, there was a marginally significant positive relationship between IQ and total reserve, and a marginally significant negative relationship between GII and total reserve. The coefficient for GDP per capita was also negative, but not statistically significant. These findings suggest that at least some of the independent variables have a significant relationship with total reserve, supporting the alternative hypothesis. Further research is needed to explore the direction and magnitude of these relationships. The analysis uses a linear robust regression model to account for potential outliers and influential observations. The results show that only HCI and GAI are statistically significant predictors of total reserves, while the relationship between IQ and total reserves is weaker. The findings suggest that policymakers should focus on improving human capital and harnessing the potential of artificial intelligence to promote socioeconomic development.

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