Research and Practice of AI Ethics: A Case Study Approach Juxtaposing Academic Discourse with Organisational Reality

Ryan, M., Antoniou, J., Brooks, L., Jiya, T., Macnish, K. and Stahl, B. (2021) Research and Practice of AI Ethics: A Case Study Approach Juxtaposing Academic Discourse with Organisational Reality. Science and Engineering Ethics. 27(2), p. 16. 1353-3452.

Ryan_etal_SEE_Research_and_Practice_of_AI_Ethics_A_Case_Study_Approach_Juxtaposing_Academic_Discourse_with ... (886kB)

Item Type:	Article
Abstract:	This study investigates the ethical use of Big Data and Artificial Intelligence (AI) technologies (BD + AI)-using an empirical approach. The paper categorises the current literature and presents a multi-case study of 'on-the-ground' ethical issues that uses qualitative tools to analyse findings from ten targeted case-studies from a range of domains. The analysis coalesces identified singular ethical issues, (from the literature), into clusters to offer a comparison with the proposed classification in the literature. The results show that despite the variety of different social domains, fields, and applications of AI, there is overlap and correlation between the organisations' ethical concerns. This more detailed understanding of ethics in AI + BD is required to ensure that the multitude of suggested ways of addressing them can be targeted and succeed in mitigating the pertinent ethical issues that are often discussed in the literature.
Uncontrolled Keywords:	Original Research/Scholarship, Smart information systems, Big data analytics, Artificial intelligence ethics, Multiple-case study analysis, Philosophy of technology
Creators:	Ryan, Mark, Antoniou, Josephina, Brooks, Laurence, Jiya, Tilimbe, Macnish, Kevin and Stahl, Bernd
Faculties, Divisions and Institutes:	Faculties > Faculty of Business & Law > Business Systems & Operations
Date:	8 March 2021
Date Type:	Publication
Page Range:	p. 16
Journal or Publication Title:	Science and Engineering Ethics
Volume:	27
Number:	2
Language:	English
DOI:	https://doi.org/10.1007/s11948-021-00293-x
ISSN:	1353-3452
Status:	Published / Disseminated
Refereed:	Yes
Related URLs:	https://pure.northampton.ac.uk/en/public...
URI:	http://nectar.northampton.ac.uk/id/eprint/14475

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