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Thinking responsibly about responsible AI and ‘the dark side’ of AI

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  • Patrick Mikalef
  • Kieran Conboy
  • Jenny Eriksson Lundström
  • Aleš Popovič

Abstract

Artificial Intelligence (AI) has been argued to offer a myriad of improvements in how we work and live. The notion of AI comprises a wide-ranging set of technologies that allow individuals and organizations to integrate and analyze data and use that insight to improve or automate decision-making. While most attention has been placed on the positive aspects companies realize by the adoption by the adoption and use of AI, there is a growing concern around the negative and unintended consequences of such technologies. In this special issue we have made a call for research papers that help us explore the dark side of AI use. By adopting a dark side lens, we aimed to expand our understanding of how AI should be implemented in practice, and how to minimize or avoid negative outcomes. In this editorial, we build on the notion of responsible AI, to highlight the different ways in which AI can potentially produce unintended consequences, as well as to suggest alternative paths future IS research can follow to improve our knowledge about how to mitigate such occurrences. We further expand on dark side theorizing in order to uncover hidden assumptions of current literature as well as to propose other prominent themes that can guide future IS research on AI adoption and use.

Suggested Citation

  • Patrick Mikalef & Kieran Conboy & Jenny Eriksson Lundström & Aleš Popovič, 2022. "Thinking responsibly about responsible AI and ‘the dark side’ of AI," European Journal of Information Systems, Taylor & Francis Journals, vol. 31(3), pages 257-268, May.
    • Handle: RePEc:taf:tjisxx:v:31:y:2022:i:3:p:257-268
    DOI: 10.1080/0960085X.2022.2026621
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    Cited by:

    1. Arpan Kumar Kar & P. S. Varsha & Shivakami Rajan, 2023. "Unravelling the Impact of Generative Artificial Intelligence (GAI) in Industrial Applications: A Review of Scientific and Grey Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 659-689, December.
    2. Wang, Weisha & Wang, Yichuan & Chen, Long & Ma, Rui & Zhang, Minhao, 2024. "Justice at the Forefront: Cultivating felt accountability towards Artificial Intelligence among healthcare professionals," Social Science & Medicine, Elsevier, vol. 347(C).
    3. Priporas, Constantinos Vasilios & Vellore Nagarajan, Durga & Kamenidou, Irene (Eirini), 2023. "A technology-people-integrated toolkit for retail care management during a crisis," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).

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