Income Inequality and Artificial Intelligence: Globalization and age dependency for developed countries

In the recent times, the role of artificial intelligence in social, economic, and environmental decision-making is important. Artificial intelligence is considered a source of enabling countries to achieve sustainable development goals. The economic consequences of the introduction of artificial intelligence are mostly overlooked and yet to be explore empirically. This work aims to empirically determine the impact of artificial intelligence on income inequality in the pioneers of the field, i.e., the G7 economies. Also, it aims to explore the role of fiscal intervention in mediating the impact of artificial intelligence on income inequality in these economies. The panel data techniques such as the test for cross sectional dependence and the test for slope heterogeneity are used. Furthermore, CIPS is used to determine the level of integration of the variables in the model. Westerlund test for cointegration and granger causality test by Dumitrescu and Hurlin (2012) are also used in the study. Furthermore, CSARDL technique is used to find out the impact of artificial intelligence along with control variables on income inequality. The results show that artificial intelligence reduces income inequality in the G7 both in the short and the long run. The absolute value of the long-term coefficients is larger than those in the short run. Based on the empirical findings of the work, it is recommended that appropriate fiscal interventions are needed in the short run to sustain the income inequality reduction impact of artificial intelligence. However, in the long run such interventions can be counter-productive but the requisite skills to optimally utilize artificial intelligence should be imparted to individuals.