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Publication

Ethical Framework for Artificial Intelligence and Digital Technologies

Ashok, M.
Madan, R.
Joha, A.
Publication Date
2022-02
End of Embargo
Supervisor
Rights
© 2021 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Peer-Reviewed
Yes
Open Access status
openAccess
Accepted for publication
28/09/2021
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Department
Awarded
Embargo end date
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.
Version
Accepted manuscript
Citation
Ashok M, Madan R, Joha A et al (2021) Ethical Framework for Artificial Intelligence and Digital Technologies. International Journal of Information Management. 62: 102433.
Link to publisher’s version
Link to published version
Type
Article
Qualification name
Notes