论文标题
如果某些职业的前景随着技术进步而停滞不前？检测就业脆弱性的任务属性方法
If the Prospect of Some Occupations Are Stagnating With Technological Advancement? A Task Attribute Approach to Detect Employment Vulnerability
论文作者
论文摘要
两种不同的趋势可以证明美国的技术失业存在。首先，比寻找工作的失业者人数要多，其次是贝弗里奇曲线的转移。有很多尝试寻找技术失业的原因。但是，所有这些方法在评估现代技术对就业未来的影响方面失败。这项研究假设，不再需要对任务的技能要求或常规的非公布歧视，而是需要一种整体方法来预测这次第四次工业革命的出现，即广泛应用AI，ML算法和机器人。考虑了三个关键属性：瓶颈，危险和常规。从O*NET数据库中选择了45个相关属性，该属性可以定义这三种类型的任务。进行主轴因子分析和K-Medoid聚类，该研究发现了367个脆弱职业的清单。这项研究进一步分析了国家就业数据的过去九年，发现在过去的四年中，尽管经济增长持续了长期，但易受伤害职业的增长仅是不可剥削的职业的一半。
Two distinct trends can prove the existence of technological unemployment in the US. First, there are more open jobs than the number of unemployed persons looking for a job, and second, the shift of the Beveridge curve. There have been many attempts to find the cause of technological unemployment. However, all of these approaches fail when it comes to evaluating the impact of modern technologies on employment future. This study hypothesizes that rather than looking into skill requirement or routine non-routine discrimination of tasks, a holistic approach is required to predict which occupations are going to be vulnerable with the advent of this 4th industrial revolution, i.e., widespread application of AI, ML algorithms, and Robotics. Three critical attributes are considered: bottleneck, hazardous, and routine. Forty-five relevant attributes are chosen from the O*NET database that can define these three types of tasks. Performing Principal Axis Factor Analysis, and K-medoid clustering, the study discovers a list of 367 vulnerable occupations. The study further analyzes the last nine years of national employment data and finds that over the previous four years, the growth of vulnerable occupations is only half than that of non-vulnerable ones despite the long rally of economic expansion.
