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

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  • 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
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    References listed on IDEAS

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    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.
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