The Future of Work in Developing Economies: What can we learn from the Global South?

Abstract

In recent years, there has been an escalation of concern revolving around the effect that automation will have on the future of work. Numerous studies have begun to investigate automation’s impact on labor markets, although all have focused on industrialized nations, which consist of more service oriented and skilled labor force. This is the first paper to study automation risk rates for developing nations. We examine automation’s effect on 10 developing countries throughout Latin America, Africa, Southeast Europe, and Asia. To address the heterogeneity of occupations across countries, we apply a task-based approach and re-calibrate the effect of automation on labor market while analyzing the task structure between and within countries. Modeling off previous studies, We followed an expectation-maximization algorithm to predict the risk of automation at worker's level. Individuals whose risk of automation was 70\% or higher were then considered to be highly automatable. Our results suggest that these developing countries have higher levels of predicted automation risk compared to developed economies. Countries range in their level of highly automatable jobs from the lowest being Yunnan –a Chinese province of 50 million inhabitants-- with 5\% to the highest of Ghana and Sri Lanka with 42\% and 43\%, respectively. We also find that occupations containing relatively more routine tasks are more likely to be automated, while workers with a higher level of education reduce their risks.

Keywords: Artificial Intelligence; AI; Automation; digitalization; future of work; labor markets; technological change; Industry 4.0.

JEL Classification: J23; J24; O33