The Impact of Artificial Intelligence on Labor Markets in Developing Countries: A New Method with an Illustration for Lao PDR and Viet Nam

37 Pages Posted: 19 May 2022

See all articles by Francesco Carbonero

Francesco Carbonero

University of Turin

Jeremy Davies

East Village Software Consultants

Ekkehard Ernst

International Labour Organization (ILO)

Frank M. Fossen

University of Nevada, Reno; IZA Institute of Labor Economics

Daniel Samaan

International Labour Organization (ILO)

Alina Sorgner

University of Jena

Abstract

AI is transforming labor markets around the world. Existing research has focused on advanced economies but has neglected developing economies. Different impacts of AI on labor markets in different countries arise not only from heterogeneous occupational structures, but also from the fact that occupations vary across countries in their composition of tasks. We propose a new methodology to translate existing measures of AI impacts that were developed for the US to countries at various levels of economic development. Our method assesses semantic similarities between textual descriptions of work activities in the US and workers' skills elicited in surveys for other countries. We implement the approach using the measure of suitability of work activities for machine learning provided by Brynjolfsson et al. (2018) for the US and the World Bank's STEP survey for Lao PDR and Viet Nam. Our approach allows characterizing the extent to which workers and occupations in a given country are subject to destructive digitalization, which puts workers at risk of being displaced, in contrast to transformative digitalization, which tends to benefit workers. We find that workers in Lao PDR are less likely than in Viet Nam to be in the "machine terrain", where workers will have to adapt to occupational transformations due to AI and are at risk of being partially displaced. Our method based on semantic textual similarities using SBERT is advantageous compared to approaches transferring AI impact scores across countries using crosswalks of occupational codes.

Keywords: labor, digitalization, machine learning, artificial intelligence, skills, developing countries

JEL Classification: J22, J23, O14, O33

Suggested Citation

Carbonero, Francesco and Davies, Jeremy and Ernst, Ekkehard and Fossen, Frank M. and Samaan, Daniel and Sorgner, Alina, The Impact of Artificial Intelligence on Labor Markets in Developing Countries: A New Method with an Illustration for Lao PDR and Viet Nam. IZA Discussion Paper No. 14944, Available at SSRN: https://ssrn.com/abstract=4114450 or http://dx.doi.org/10.2139/ssrn.4114450

Francesco Carbonero

University of Turin

Via Po 53
Torino, 10100
Italy

Jeremy Davies

East Village Software Consultants

Ekkehard Ernst

International Labour Organization (ILO) ( email )

Route des Morillons 4
Geneva, 1211
Switzerland
+41 22 799 77 91 (Phone)

Frank M. Fossen

University of Nevada, Reno ( email )

1664 N. Virginia Street
Reno, NV 89557-0030
United States

HOME PAGE: http://business.unr.edu/faculty/ffossen/

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

HOME PAGE: http://www.iza.org/en/webcontent/personnel/photos/index_html?key=2906

Daniel Samaan

International Labour Organization (ILO)

Route des Morillons 4
Geneva, 1211
Switzerland

Alina Sorgner (Contact Author)

University of Jena ( email )

F├╝rstengraben 1
Jena, 07743
Germany

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