一些职业的前景是否随着技术进步而停滞不前？就业脆弱性检测的任务属性方法
If the Prospect of Some Occupations Are Stagnating With Technological Advancement? A Task Attribute Approach to Detect Employment Vulnerability
摘要：
有两种截然不同的趋势可以证明美国存在技术性失业。首先，空缺职位的数量多于正在找工作的失业人数，其次，贝弗里奇曲线的移动。人们曾多次试图找出技术性失业的原因。然而，在评估现代技术对未来就业的影响时，所有这些方法都失败了。这项研究假设，与其研究技能要求或任务的常规非常规歧视，还需要一种整体方法来预测随着第四次工业革命的到来，哪些职业将变得脆弱，即，AI、ML算法和机器人技术的广泛应用。三个关键属性被认为是：瓶颈，危险，和常规。从O*NET数据库中选择了45个相关属性，可以定义这三种类型的任务。该研究通过主轴因子分析和K-medoid聚类，发现了367个脆弱职业的列表。该研究进一步分析了过去九年的国家就业数据，发现在过去四年中，尽管经济扩张长期反弹，但脆弱职业的增长率仅为非脆弱职业的一半。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
