Skills or degree? The rise of skill-based hiring for AI and green jobs

IF 12.9 1区 管理学 Q1 BUSINESS
Matthew Bone , Eugenia González Ehlinger , Fabian Stephany
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引用次数: 0

Abstract

Emerging professions in fields like Artificial Intelligence (AI) and sustainability (green jobs) are experiencing labour shortages as industry demand outpaces labour supply. In this context, our study aims to understand whether employers have begun focusing more on individual skills rather than formal qualifications in their recruitment processes. We analysed a large time-series dataset of approximately eleven million online job vacancies in the UK from 2018 to mid-2024, drawing on diverse literature on technological change and labour market signalling. Our findings provide evidence that employers have initiated “skill-based hiring” for AI roles, adopting more flexible hiring practices to expand the available talent pool. From 2018 to 2023, demand for AI roles grew by 21 % as a proportion of all postings (and accelerated into 2024). Simultaneously, mentions of university education requirements for AI roles declined by 15 %. Our regression analysis shows that university degrees have a significantly lower wage premium for both AI and green roles. In contrast, AI skills command a wage premium of 23 %, exceeding the value of degrees up until the PhD-level (33 %). In occupations with high demand for AI skills, the premium for skills is high, and the reward for degrees is relatively low. We recommend leveraging alternative skill-building formats such as apprenticeships, on-the-job training, MOOCs, vocational education and training, micro-certificates, and online bootcamps to fully utilise human capital and address talent shortages.
技能还是学位?人工智能和绿色工作的技能型招聘的兴起
随着行业需求超过劳动力供应,人工智能(AI)和可持续发展(绿色工作)等领域的新兴职业正面临劳动力短缺。在这种背景下,我们的研究旨在了解雇主在招聘过程中是否开始更多地关注个人技能而不是正式资格。我们分析了英国从2018年到2024年中期约1100万个在线职位空缺的大型时间序列数据集,并借鉴了有关技术变革和劳动力市场信号的各种文献。我们的研究结果提供了证据,表明雇主已经为人工智能角色启动了“基于技能的招聘”,采用更灵活的招聘做法来扩大可用的人才库。从2018年到2023年,人工智能职位的需求占所有职位的比例增长了21%(并加速到2024年)。与此同时,提到大学学历的人工智能职位要求下降了15%。我们的回归分析表明,大学学位对人工智能和绿色角色的工资溢价都明显较低。相比之下,人工智能技能的工资溢价为23%,超过了博士学位之前的学位价值(33%)。在对人工智能技能要求高的职业中,技能的溢价很高,而学位的回报相对较低。我们建议利用其他技能建设形式,如学徒制、在职培训、mooc、职业教育和培训、微证书和在线训练营,充分利用人力资本,解决人才短缺问题。
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来源期刊
CiteScore
21.30
自引率
10.80%
发文量
813
期刊介绍: Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.
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