IDEAS home Printed from https://ideas.repec.org/a/bla/jinfst/v72y2021i1p128-135.html
   My bibliography  Save this article

Artificial intelligence and the world of work, a co‐constitutive relationship

Author

Listed:
  • Carsten Østerlund
  • Mohammad Hossein Jarrahi
  • Matthew Willis
  • Karen Boyd
  • Christine T. Wolf

Abstract

The use of intelligent machines—digital technologies that feature data‐driven forms of customization, learning, and autonomous action—is rapidly growing and will continue to impact many industries and domains. This is consequential for communities of researchers, educators, and practitioners concerned with studying, supporting, and educating information professionals. In the face of new developments in artificial intelligence (AI), the research community faces 3 questions: (a) How is AI becoming part of the world of work? (b) How is the world of work becoming part of AI? and (c) How can the information community help address this topic of Work in the Age of Intelligent Machines (WAIM)? This opinion piece considers these 3 questions by drawing on discussion from an engaging 2019 iConference workshop organized by the NSF supported WAIM research coordination network (note: https://waim.network).

Suggested Citation

  • Carsten Østerlund & Mohammad Hossein Jarrahi & Matthew Willis & Karen Boyd & Christine T. Wolf, 2021. "Artificial intelligence and the world of work, a co‐constitutive relationship," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 128-135, January.
  • Handle: RePEc:bla:jinfst:v:72:y:2021:i:1:p:128-135
    DOI: 10.1002/asi.24388
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asi.24388
    Download Restriction: no

    File URL: https://libkey.io/10.1002/asi.24388?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    2. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    3. L. G. Pee & Shan L. Pan & Lili Cui, 2019. "Artificial intelligence in healthcare robots: A social informatics study of knowledge embodiment," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(4), pages 351-369, April.
    4. Michael Haenlein & Andreas Kaplan & Chee-Wee Tan & Pengzhu Zhang, 2019. "Artificial intelligence (AI) and management analytics," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(4), pages 341-343, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    2. Ayat Sami ODEIBAT, 2021. "The Effect Of Technology Evolution On The Future Of Jobs," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 17, pages 57-67, June.
    3. Wang, Lei & Zhou, Yahong & Chiao, Benjamin, 2023. "Robots and firm innovation: Evidence from Chinese manufacturing," Journal of Business Research, Elsevier, vol. 162(C).
    4. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
    5. Zhang, Yucheng & Zhang, Meng & Li, Jing & Liu, Guangjian & Yang, Miles M. & Liu, Siqi, 2021. "A bibliometric review of a decade of research: Big data in business research – Setting a research agenda," Journal of Business Research, Elsevier, vol. 131(C), pages 374-390.
    6. Chowdhury, Soumyadeb & Budhwar, Pawan & Dey, Prasanta Kumar & Joel-Edgar, Sian & Abadie, Amelie, 2022. "AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework," Journal of Business Research, Elsevier, vol. 144(C), pages 31-49.
    7. Grewal, Dhruv & Kroschke, Mirja & Mende, Martin & Roggeveen, Anne L. & Scott, Maura L., 2020. "Frontline Cyborgs at Your Service: How Human Enhancement Technologies Affect Customer Experiences in Retail, Sales, and Service Settings," Journal of Interactive Marketing, Elsevier, vol. 51(C), pages 9-25.
    8. Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    9. Huang, Ming-Hui & Rust, Roland T., 2022. "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, Elsevier, vol. 98(2), pages 209-223.
    10. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    11. Loebbing, Jonas, 2018. "An Elementary Theory of Endogenous Technical Change and Wage Inequality," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181603, Verein für Socialpolitik / German Economic Association.
    12. Basso, Henrique S. & Jimeno, Juan F., 2021. "From secular stagnation to robocalypse? Implications of demographic and technological changes," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 833-847.
    13. Iftekhairul Islam & Fahad Shaon, 2020. "If the Prospect of Some Occupations Are Stagnating With Technological Advancement? A Task Attribute Approach to Detect Employment Vulnerability," Papers 2001.02783, arXiv.org.
    14. Ayhan, Fatih & Elal, Onuray, 2023. "The IMPACTS of technological change on employment: Evidence from OECD countries with panel data analysis," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    15. Caroline Lloyd & Jonathan Payne, 2021. "Fewer jobs, better jobs? An international comparative study of robots and ‘routine’ work in the public sector," Industrial Relations Journal, Wiley Blackwell, vol. 52(2), pages 109-124, March.
    16. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    17. Gilberto Santos & Jose Carlos Sá & Maria João Félix & Luís Barreto & Filipe Carvalho & Manuel Doiro & Kristína Zgodavová & Miladin Stefanović, 2021. "New Needed Quality Management Skills for Quality Managers 4.0," Sustainability, MDPI, vol. 13(11), pages 1-22, May.
    18. Grinis, Inna, 2017. "The STEM requirements of "non-STEM" jobs: evidence from UK online vacancy postings and implications for skills & knowledge shortages," LSE Research Online Documents on Economics 85123, London School of Economics and Political Science, LSE Library.
    19. van den Broek, Tijs & van Veenstra, Anne Fleur, 2018. "Governance of big data collaborations: How to balance regulatory compliance and disruptive innovation," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 330-338.
    20. Daniele Angelini, 2023. "Aging Population and Technology Adoption," Working Paper Series of the Department of Economics, University of Konstanz 2023-01, Department of Economics, University of Konstanz.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jinfst:v:72:y:2021:i:1:p:128-135. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.