Artificial intelligence and skilled employment in South Africa: Exploring key variables

Fiyinfoluwa Giwa, Nicholas Ngepah

Research output: Contribution to journalArticlepeer-review

Abstract

The discourse surrounding artificial intelligence (AI) and its repercussions on skilled employment merits careful consideration. While AI technologies have the potential to result in job displacement within specific sectors, they concurrently usher in new employment opportunities, especially for individuals possessing advanced skills. The primary objective of this paper is to thoroughly evaluate the impact of AI on skilled employment within the South African economy. To achieve this objective, the study employs the Autoregressive Distributed Lag (ARDL) model and Granger causality analysis, spanning from 2012Q1 to 2021Q4. The results derived from the ARDL estimation reveal a substantial and positive contribution of artificial intelligence to skilled employment in South Africa, a trend observed in both the long and short run. However, two structural breaks were identified in the data, hence a re-estimation of the ARDL model. The re-estimated ARDL model revealed a negative and significant relationship between AI and skilled employment. In light of these findings, this study advocates implementing regulations and labor market policies that promote the responsible deployment of AI technology while safeguarding workers’ rights and job security. This could include establishing guidelines for AI deployment in the workplace, ensuring transparency and accountability in AI systems, and implementing social safety nets to support workers during job transitions.

Original languageEnglish
Article number100231
JournalResearch in Globalization
Volume8
DOIs
Publication statusPublished - Jun 2024
Externally publishedYes

Keywords

  • Artificial intelligence
  • Autoregressive Distributed Lag (ARDL)
  • Granger Causality
  • Skilled employment
  • South Africa

ASJC Scopus subject areas

  • Global and Planetary Change
  • Geography, Planning and Development
  • Development
  • Environmental Science (miscellaneous)
  • Urban Studies
  • Economics, Econometrics and Finance (miscellaneous)

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