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.

中文翻译：

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Ipanema的机器人开始工作：估算巴西乔布斯自动化的可能性

摘要本文利用1986年至2017年间巴西劳动力市场行政记录中的数据，复制了Frey和Osborne所采用的调查巴西工作自动化概率的方法。根据其技术资格要求，并估计从2018年到2046年每个作业区的工人的未来需求。为了估算每个职业的自动化可能性，我们首先收集了69位人工智能专家的专家意见，然后应用了高斯过程使用每个职业的文字描述作为输入。结果显示，2017年巴西所有正式就业工人中有55％处于自动化风险很高或很高的工作中，其价值与其他国家文献中的类似作品一致。本文的研究结果可以帮助政策制定者预测具有高自动化风险的职业可能增加的失业率，预测巴西劳动力市场的未来转型，从而支持经济和社会干预措施的规划。