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Ethical framework for Artificial Intelligence and Digital technologies

Author

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  • Ashok, Mona
  • Madan, Rohit
  • Joha, Anton
  • Sivarajah, Uthayasankar

Abstract

The use of Artificial Intelligence (AI) in Digital technologies (DT) is proliferating a profound socio-technical transformation. Governments and AI scholarship have endorsed key AI principles but lack direction at the implementation level. Through a systematic literature review of 59 papers, this paper contributes to the critical debate on the ethical use of AI in DTs beyond high-level AI principles. To our knowledge, this is the first paper that identifies 14 digital ethics implications for the use of AI in seven DT archetypes using a novel ontological framework (physical, cognitive, information, and governance). The paper presents key findings of the review and a conceptual model with twelve propositions highlighting the impact of digital ethics implications on societal impact, as moderated by DT archetypes and mediated by organisational impact. The implications of intelligibility, accountability, fairness, and autonomy (under the cognitive domain), and privacy (under the information domain) are the most widely discussed in our sample. Furthermore, ethical implications related to the governance domain are shown to be generally applicable for most DT archetypes. Implications under the physical domain are less prominent when it comes to AI diffusion with one exception (safety). The key findings and resulting conceptual model have academic and professional implications.

Suggested Citation

  • Ashok, Mona & Madan, Rohit & Joha, Anton & Sivarajah, Uthayasankar, 2022. "Ethical framework for Artificial Intelligence and Digital technologies," International Journal of Information Management, Elsevier, vol. 62(C).
    • Handle: RePEc:eee:ininma:v:62:y:2022:i:c:s0268401221001262
    DOI: 10.1016/j.ijinfomgt.2021.102433
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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. Behera, Rajat Kumar & Bala, Pradip Kumar & Rana, Nripendra P. & Irani, Zahir, 2023. "Responsible natural language processing: A principlist framework for social benefits," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    3. 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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