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Job Transitions in a Time of Automation and Labor Market Crises
arXiv - CS - Computers and Society Pub Date : 2020-11-23 , DOI: arxiv-2011.11801
Nikolas Dawson, Marian-Andrei Rizoiu, Mary-Anne Williams

Job security can never be taken for granted, especially in times of rapid, widespread and unexpected social and economic change. These changes can force workers to transition to new jobs. This may be because technologies emerge or production is moved abroad. Perhaps it is a global crisis, such as COVID-19, which shutters industries and displaces labor en masse. Regardless of the impetus, people are faced with the challenge of moving between jobs to find new work. Successful transitions typically occur when workers leverage their existing skills in the new occupation. Here, we propose a novel method to measure the similarity between occupations using their underlying skills. We then build a recommender system for identifying optimal transition pathways between occupations using job advertisements (ads) data and a longitudinal household survey. Our results show that not only we can accurately predict occupational transitions (Accuracy = 76%), but we account for the asymmetric difficulties of moving between jobs (it is easier to move in one direction than the other). We also build an early warning indicator for new technology adoption (showcasing Artificial Intelligence), a major driver of rising job transitions. By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19), and can be leveraged by policy-makers, educators, and jobseekers who are forced to confront the often distressing challenges of having to find new jobs.

中文翻译:

自动化和劳动力市场危机时期的工作转变

工作安全永远不会被视为理所当然,尤其是在迅速,广泛和出乎意料的社会和经济变革时期。这些变化可能迫使工人过渡到新工作。这可能是因为技术出现或生产转移到国外。也许这是全球危机,例如COVID-19,它关闭了工业并大量转移了劳动力。不管有什么动力,人们都面临着在工作之间寻找新工作的挑战。当工人在新职业中利用现有技能时,通常会发生成功的过渡。在这里,我们提出了一种新颖的方法来利用职业的基本技能来衡量职业之间的相似性。然后,我们将建立一个推荐系统,以使用求职广告(ads)数据和纵向的家庭调查来确定职业之间的最佳过渡路径。我们的结果表明,不仅我们可以准确地预测职业转变(准确度= 76%),而且可以说明工作之间移动的不对称困难(一个方向比另一个方向更容易移动)。我们还为采用新技术(展示人工智能)建立了预警指标,这是不断增加的工作转变的主要驱动力。通过使用实时数据,我们的系统可以应对劳动力需求的变化(例如由COVID-19引起的变化),并且可以被决策者,教育者和求职者所利用,他们不得不面对通常令人沮丧的情况必须找到新工作的挑战。但是我们解释了在工作之间移动的不对称困难(在一个方向上移动比在另一个方向上容易)。我们还为采用新技术(展示人工智能)建立了预警指标,这是不断增加的工作转变的主要驱动力。通过使用实时数据,我们的系统可以应对劳动力需求的变化(例如由COVID-19引起的变化),并且可以被决策者,教育者和求职者所利用,他们不得不面对通常令人沮丧的情况必须找到新工作的挑战。但是我们解释了在工作之间移动的不对称困难(在一个方向上移动比在另一个方向上容易)。我们还为采用新技术(展示人工智能)建立了预警指标,这是不断增加的工作转变的主要驱动力。通过使用实时数据,我们的系统可以应对劳动力需求的变化(例如由COVID-19引起的变化),并且可以被决策者,教育者和求职者所利用,他们不得不面对通常令人沮丧的情况必须找到新工作的挑战。
更新日期:2020-11-25
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