EconPapers    
Economics at your fingertips  
 

Automation in Latin America: Are Women at Higher Risk of Losing Their Jobs?

Pablo Egana-delSol, Monserrat Bustelo, Laura Ripani, Nicolas Soler and Mariana Viollaz

Technological Forecasting and Social Change, 2022, vol. 175, issue C

Abstract: The Fourth Industrial Revolution, which comprises digitization, artificial intelligence, robotics, among others, have the power to drastically increase economic output but may also displace workers. In this paper we assess the risk of automation for female and male workers in four Latin American countries – Bolivia, Chile, Colombia and El Salvador. Our study is the first to apply a task-based approach with a gender perspective in this region. Our main findings indicate that men are more likely than women to perform tasks linked to the ‘skills of the future’, such as STEM (science, technology, engineering and mathematics), information and communications technology, management and communication, and creative problem-solving tasks. Women thus have a higher average risk of automation, and 21% of women vs. 19% of men are at high risk (probability of automation greater than 70%). The differential impacts of the new technological trends for women and men must be assessed in order to guide the policy-making process to prepare workers for the future. Finally, country- level specific actions should be taken to prevent digital transformation from worsening existing gender inequalities in the labor market.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162521007642
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Automation in Latin America: Are Women at Higher Risk of Losing Their Jobs? (2020) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:175:y:2022:i:c:s0040162521007642

DOI: 10.1016/j.techfore.2021.121333

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-04-03
Handle: RePEc:eee:tefoso:v:175:y:2022:i:c:s0040162521007642