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What is it about humanity that we can’t give away to intelligent machines? A European perspective

Author

Listed:
  • Coombs, Crispin
  • Stacey, Patrick
  • Kawalek, Peter
  • Simeonova, Boyka
  • Becker, Joerg
  • Bergener, Katrin
  • Carvalho, João Álvaro
  • Fantinato, Marcelo
  • Garmann-Johnsen, Niels F.
  • Grimme, Christian
  • Stein, Armin
  • Trautmann, Heike

Abstract

One of the most significant recent technological developments concerns the development and implementation of ‘intelligent machines’ that draw on recent advances in artificial intelligence (AI) and robotics. However, there are growing tensions between human freedoms and machine controls. This article reports the findings of a workshop that investigated the application of the principles of human freedom throughout intelligent machine development and use. Forty IS researchers from ten different countries discussed four contemporary AI and humanity issues and the most relevant IS domain challenges. This article summarizes their experiences and opinions regarding four AI and humanity themes: Crime & conflict, Jobs, Attention, and Wellbeing. The outcomes of the workshop discussions identify three attributes of humanity that need preservation: a critique of the design and application of AI, and the intelligent machines it can create; human involvement in the loop of intelligent machine decision-making processes; and the ability to interpret and explain intelligent machine decision-making processes. The article provides an agenda for future AI and humanity research.

Suggested Citation

  • Coombs, Crispin & Stacey, Patrick & Kawalek, Peter & Simeonova, Boyka & Becker, Joerg & Bergener, Katrin & Carvalho, João Álvaro & Fantinato, Marcelo & Garmann-Johnsen, Niels F. & Grimme, Christian & , 2021. "What is it about humanity that we can’t give away to intelligent machines? A European perspective," International Journal of Information Management, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:ininma:v:58:y:2021:i:c:s0268401221000049
    DOI: 10.1016/j.ijinfomgt.2021.102311
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    Cited by:

    1. Akter, Shahriar & Dwivedi, Yogesh K. & Sajib, Shahriar & Biswas, Kumar & Bandara, Ruwan J. & Michael, Katina, 2022. "Algorithmic bias in machine learning-based marketing models," Journal of Business Research, Elsevier, vol. 144(C), pages 201-216.
    2. Denis Dennehy & Anastasia Griva & Nancy Pouloudi & Yogesh K. Dwivedi & Matti Mäntymäki & Ilias O. Pappas, 2023. "Artificial Intelligence (AI) and Information Systems: Perspectives to Responsible AI," Information Systems Frontiers, Springer, vol. 25(1), pages 1-7, February.

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