Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs

Eugenia Gonzalez Ehlinger, Fabian Stephany
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Abstract

For emerging professions, such as jobs in the field of Artificial Intelligence (AI) or sustainability (green), labour supply does not meet industry demand. In this scenario of labour shortages, our work aims to understand whether employers have started focusing on individual skills rather than on formal qualifications in their recruiting. By analysing a large time series dataset of around one million online job vacancies between 2019 and 2022 from the UK and drawing on diverse literature on technological change and labour market signalling, we provide evidence that employers have started so-called "skill-based hiring" for AI and green roles, as more flexible hiring practices allow them to increase the available talent pool. In our observation period the demand for AI roles grew twice as much as average labour demand. At the same time, the mention of university education for AI roles declined by 23%, while AI roles advertise five times as many skills as job postings on average. Our regression analysis also shows that university degrees no longer show an educational premium for AI roles, while for green positions the educational premium persists. In contrast, AI skills have a wage premium of 16%, similar to having a PhD (17%). Our work recommends making use of alternative skill building formats such as apprenticeships, on-the-job training, MOOCs, vocational education and training, micro-certificates, and online bootcamps to use human capital to its full potential and to tackle talent shortages.
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技能还是学位?基于技能的人工智能和绿色工作招聘的兴起
对于新兴职业,如人工智能(AI)或可持续发展(绿色)领域的工作,劳动力供应无法满足行业需求。在这种劳动力短缺的情况下,我们的工作旨在了解雇主在招聘时是否已开始注重个人技能而非正式学历。通过分析英国 2019 年至 2022 年间约一百万个在线职位空缺的大型时间序列数据集,并借鉴有关技术变革和劳动力市场信号的各种文献,我们提供了证据,证明雇主已开始针对人工智能和绿色职位进行所谓的 "基于技能的招聘",因为更灵活的招聘做法使他们能够增加可用的人才库。在我们的观察期内,对人工智能职位的需求增长是平均劳动力需求增长的两倍。与此同时,人工智能职位对大学教育的提及率却下降了 23%,而人工智能职位所宣传的技能则是平均招聘数量的五倍。我们的回归分析还显示,对于人工智能职位来说,大学学历不再显示教育溢价,而对于绿色职位来说,教育溢价依然存在。相比之下,人工智能技能的工资溢价为 16%,与拥有博士学位(17%)的工资溢价相似。我们的研究建议利用学徒制、在职培训、MOOCs、职业教育与培训、微型证书和在线训练营等替代技能培养形式,充分发挥人力资本的潜力,解决人才短缺问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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