P. Albuquerque, Cayan Atreio Portela Barcena Saavedra, Rafael Lima de Morais, Yaohao Peng
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引用次数: 5
Abstract
Abstract In this paper, we replicated the method applied by Frey and Osborne to investigate the automation probability of jobs in Brazil, using data from Brazilian labor market administrative records between 1986 and 2017. We categorized each job listed on Brazil’s Occupational Classification System into Job Zones based on its technical qualifications requirements and estimated the future demand for workers of each Job Zone from 2018 to 2046. To estimate the probability of automation for each occupation, we first collected the expert opinion of 69 specialists on artificial intelligence and then applied a Gaussian process using as input the text description of each occupation. The results showed that in 2017 55% of all formally employed workers in Brazil are in jobs with high or very high risk of automation, a value consistent with similar works found in the literature for other countries. The findings of this paper can aid policy makers to anticipate potential increased unemployment for occupations with high risk of automation, anticipate future transformations of the Brazilian labor market, and consequently support the planning of economic and social interventions.
期刊介绍:
Latin American Business Review is a quarterly, refereed journal which facilitates the exchange of information and new ideas between academics, business practitioners, public policymakers, and those in the international development community. Special features of the journal will keep you current on various teaching, research, and information sources. These activities all focus on the business and economic environment of the diverse and dynamic countries of the Americas.