AI-exposure and labour market: a systematic literature review on estimations, validations, and perceptions

被引:1
作者
Ghosh, Dona [1 ,2 ]
Ghosh, Rajarshi [3 ]
Chowdhury, Sahana Roy [4 ]
Ganguly, Boudhayan [5 ]
机构
[1] Thiagarajar Sch Management, Fac Econ, Madurai, India
[2] Taylors Univ, Subang Jaya, Malaysia
[3] IMI Kolkata, Kolkata, India
[4] Int Management Inst, Fac Econ, Kolkata, India
[5] Int Management Inst, Fac MIS & Analyt, Kolkata, India
关键词
Artificial intelligence; Automation; Employment; Job creation; Job destruction; J21; J24; O31; O33; ARTIFICIAL-INTELLIGENCE; COMPUTERS; IMPACT;
D O I
10.1007/s11301-023-00393-x
中图分类号
F [经济];
学科分类号
02 ;
摘要
The artificial intelligence (AI) revolution is still in its infancy, but it is constantly changing across time and space. Any AI-penetration, adoption and diffusion trigger further rounds of supply-induced demand for newer AI-exposures. Understandably, the demand and supply are intertwined, and currently, it is a formidable challenge to comprehensively capture and delineate the extent of AI's influence, as evidenced in existing literature. The paper details out the fundamental inferences drawn by the recent literature on this, thoroughly and systematically. The findings are based on peer-reviewed articles from the domains of economics, HR, business and management literature spanning 2010-2023. Although growing AI exposure is widely acknowledged in the literature, clarity and comprehensiveness are missing on several grounds. This review analyses the adoption of technology based on AI, whether in a broad or narrow sense, as well as the skill sets required and its impact on the labour market as documented in extant literature, encompassing employment, occupations, earnings, and organisation. Three overarching concerns are identified: First, to assess and infer on possible labour market impacts due to the AI-exposure of firms the proxies of AI exposure taken by the literature are quite diverse: robotization, digital evolution index, human-machine collaboration, technological progress etc. Second, the methodologies employed in qualitative and quantitative literature exhibit a wide range of diversity; these techniques often yielded contradictory and divergent conclusions, potentially influenced by the size and structure of the data utilised in the respective methods. Third, research is limited to China or regions of developed countries, making it difficult to draw general conclusions. The literature at present, is dispersed, and is yet to build any consensus on deciphering the skill-types that possibly would see the largest impacts, the sectors that might see plethora of AI-enabled economic repercussions, whether indeed there will be an overall net- job destruction or net-job creation, and does that differ across economic regions? The paper details out the fundamental inferences drawn by the recent literature on this, thoroughly and systematically.
引用
收藏
页码:677 / 704
页数:28
相关论文
共 83 条
  • [1] Accenture, 2018, ARTIFICIAL INTELLIGE
  • [2] Artificial Intelligence and Jobs: Evidence from Online Vacancies
    Acemoglu, Daron
    Autor, David
    Hazell, Jonathon
    Restrepo, Pascual
    [J]. JOURNAL OF LABOR ECONOMICS, 2022, 40 : S293 - S340
  • [3] Automation and New Tasks: How Technology Displaces and Reinstates Labor
    Acemoglu, Daron
    Restrepo, Pascual
    [J]. JOURNAL OF ECONOMIC PERSPECTIVES, 2019, 33 (02) : 3 - 29
  • [4] ACYPRESTE RAFAEL DE, 2022, Brazil. J. Polit. Econ., V42, P1014, DOI 10.1590/0101-31572022-3320
  • [5] Aghion P., 2019, EC STAT, V510, P149, DOI [10.24187/ecostat.2019.510t.1994, DOI 10.24187/ECOSTAT.2019.510T.1994]
  • [6] Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction
    Agrawal, Ajay
    Gans, Joshua S.
    Goldfarb, Avi
    [J]. JOURNAL OF ECONOMIC PERSPECTIVES, 2019, 33 (02) : 31 - 49
  • [7] "Aging-and-Tech Job Vulnerability": A proposed framework on the dual impact of aging and AI, robotics, and automation among older workers
    Alcover, Carlos-Maria
    Guglielmi, Dina
    Depolo, Marco
    Mazzetti, Greta
    [J]. ORGANIZATIONAL PSYCHOLOGY REVIEW, 2021, 11 (02) : 175 - 201
  • [8] A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities
    Ali, Omar
    Abdelbaki, Wiem
    Shrestha, Anup
    Elbasi, Ersin
    Alryalat, Mohammad Abdallah Ali
    Dwivedi, Yogesh K.
    [J]. JOURNAL OF INNOVATION & KNOWLEDGE, 2023, 8 (01):
  • [9] Digital transformation, development and productivity in developing countries: is artificial intelligence a curse or a blessing?
    Aly, Heidi
    [J]. REVIEW OF ECONOMICS AND POLITICAL SCIENCE, 2022, 7 (04) : 238 - 256
  • [10] Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey
    Antes, Alison L.
    Burrous, Sara
    Sisk, Bryan A.
    Schuelke, Matthew J.
    Keune, Jason D.
    DuBois, James M.
    [J]. BMC MEDICAL INFORMATICS AND DECISION MAKING, 2021, 21 (01)