From MIT Sloan Management Review
Much has been written about the rise of automation in developed countries. Economists have been busily creating models seeking to quantify the likely impact of automation on employment.1 However, far less has been written about the potential effects on work in developing nations. This is surprising, given that automation may be especially troublesome for developing economies.
We know that economic growth brings significant shifts toward higher-skilled occupations and that the economies of many developing nations rely largely on manual labor and routinized manufacturing work. Because some types of manual and routinized work can be easily handled by computers, machinery, and artificial intelligence, it’s clear that large-scale automation could have significant and wide-reaching effects on workers in developing countries.
We wanted to get a more detailed understanding of how automation might affect developing economies compared with those of the developed world. To do this, we examined a database of more than 13,000 workers from 10 countries that contained the workers’ descriptions of the tasks they completed at their jobs and in their households.2 We combined this data with an occupation-level assessment of which jobs would most likely be automated, in order to quantify the risk of displacement.
Read the full post at MIT Sloan Management Review.
Pablo Egaña del Sol is an assistant professor of economics at the Asia School of Business in Kuala Lumpur and an international faculty fellow at MIT’s Sloan School of Management.
Connor Joyce is a behavioral researcher at Microsoft.