The relationship between artificial intelligence, big data, and unemployment in G7 countries: New insights from dynamic panel data model

Abstract

This study investigates the impact of artificial intelligence (AI) and big data technologies on unemployment in the G7 countries using a dynamic panel estimation approach. The analysis covers the period from 2005 to 2020 and incorporates various control variables related to unemployment rates, along with AI, big data, data science, and machine learning Google Trend Index (GTI). The Arellano–Bover/Blundell–Bond (1998) system estimator is employed to ensure robust results, particularly in cases involving multiple lags of the dependent variable. The most noteworthy results highlight a negative association between AI, big data technologies, and unemployment. These technologies enhance productivity, leading to increased capital accumulation and the creation of new jobs. This validates the "displacement effect" for AI and big data technologies, implying that while certain jobs may be automated, the net effect is job creation. Consequently, implementing AI and big data technologies in economic processes can effectively reduce unemployment rates and boost wages by creating new job opportunities.