The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Ethics as a Service: A Pragmatic Operationalisation of AI Ethics
Open accessAbstract
As the range of potential uses for Artificial Intelligence (AI), in particular machine learning (ML), has increased, so has awareness of the associated ethical issues. This increased awareness has led to the realisation that existing legislation and regulation provides insufficient protection to individuals, groups, society, and the environment from AI harms. In response to this realisation, there has been a proliferation of principle-based ethics codes, guidelines and frameworks. However, it has become increasingly clear that a significant gap exists between the theory of AI ethics principles and the practical design of AI systems. In previous work, we analysed whether it is possible to close this gap between the ‘what’ and the ‘how’ of AI ethics through the use of tools and methods designed to help AI developers, engineers, and designers translate principles into practice. We concluded that this method of closure is currently ineffective as almost all existing translational tools and methods are either too flexible (and thus vulnerable to ethics washing) or too strict (unresponsive to context). This raised the question: if, even with technical guidance, AI ethics is challenging to embed in the process of algorithmic design, is the entire pro-ethical design endeavour rendered futile? And, if no, then how can AI ethics be made useful for AI practitioners? This is the question we seek to address here by exploring why principles and technical translational tools are still needed even if they are limited, and how these limitations can be potentially overcome by providing theoretical grounding of a concept that has been termed ‘Ethics as a Service.’
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Citations
Cites
The global landscape of AI ethics guidelines
Jobin, A., Ienca, M., & Vayena, E. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0088-2 · Cited by 6,220 · cited 2×
“…the development of bioethics), where changes are sometimes theory-led, and can partly be explained by the relative ‘newness’ of the conce pt of AI ethical principles in the public policy domain 1 : less than 20% of all the AI ethics documents are more than four-years old (Jobin et al., 2019).”
BackgroundFloridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., et al. (2018) · Minds and Machines · doi:10.1007/s11023-018-9482-5 · Cited by 4,774
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The Ethics of AI Ethics: An Evaluation of Guidelines
Hagendorff, T. (2020) · Minds and Machines · doi:10.1007/s11023-020-09517-8 · Cited by 1,911 · cited 1×
“In doing so we can hope to create a bridge between abstract principles and technical implementations (Hagendorff, 2020).”
BackgroundThe Ethics of AI Ethics -- An Evaluation of Guidelines
Hagendorff, T. (2019) · arXiv · doi:10.48550/arxiv.1903.03425 · Cited by 1,907 · cited 1×
“In doing so we can hope to create a bridge between abstract principles and technical implementations (Hagendorff, 2020).”
BackgroundPrinciples alone cannot guarantee ethical AI
Mittelstadt, B. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0114-4 · Cited by 1,886 · cited 1×
“Hence, ethical principles have been accused of being too flexible (or too undefined) to be of practical use to AI practitioners (Mittelstadt, 2019; Whittlestone et al., 2019).”
BackgroundAnanny, M., & Crawford, K. (2018) · New Media & Society · doi:10.1177/1461444816676645 · Cited by 1,836
A Unified Framework of Five Principles for AI in Society
Floridi, L., & Cowls, J. (2019) · Harvard Data Science Review · doi:10.1162/99608f92.8cd550d1 · Cited by 1,631 · cited 4×
“When something (ethical tools, methods or guidelines) is too flexible it does little to protect against the risks of ethics shopping and ethics washing (Floridi, 2019b).”
BackgroundInfluentialSelf-citationMorley, J., Floridi, L., Kinsey, L., & Elhalal, A. (2020) · Science and Engineering Ethics · doi:10.1007/s11948-019-00165-5 · Cited by 882
Self-citationGoverning artificial intelligence: ethical, legal and technical opportunities and challenges
Cath, C. (2018) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2018.0080 · Cited by 745 · cited 2×
“Proposed external auditing mechanisms typically focus on specific parts of the system, rather than looking at the overall system function (Cath, 2018), and so do little to address the risks of ‘unpredictability’ described above.”
BackgroundMethod
Cited by
Ahmad, K., Maabreh, M., Ghaly, M., Khan, K., Qadir, J., & Al-Fuqaha, A. (2022) · Computer Science Review · doi:10.1016/j.cosrev.2021.100452 · Cited by 291
Operationalising AI Ethics: Barriers, Enablers and next Steps
Morley, J., Kinsey, L., Elhalal, A., Garcia, F., Ziosi, M., & Floridi, L. (2023) · AI & SOCIETY · doi:10.1007/s00146-021-01308-8 · Cited by 215
Self-citationElliott, K., Price, R., Shaw, P., Spiliotopoulos, T., Ng, M., Coopamootoo, K., & van Moorsel, A. (2021) · Society · doi:10.1007/s12115-021-00594-8 · Cited by 184
Auditing of AI: Legal, Ethical and Technical Approaches
Mökander, J. (2023) · Digital Society · doi:10.1007/s44206-023-00074-y · Cited by 152
“This development is not limited to the private sector (Morley et al., 2021).”
BackgroundSelf-citationOrtega-Bolaños, R., Bernal-Salcedo, J., Germán Ortiz, M., Galeano Sarmiento, J., Ruz, G. A., & Tabares-Soto, R. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10740-3 · Cited by 76
Integrating ethics in AI development: a qualitative study
Arbelaez Ossa, L., Lorenzini, G., Milford, S. R., Shaw, D., Elger, B. S., & Rost, M. (2024) · BMC Medical Ethics · doi:10.1186/s12910-023-01000-0 · Cited by 67
The dilemma and countermeasures of educational data ethics in the age of intelligence
Guan, X., Feng, X., & Islam, A. Y. M. A. (2023) · Humanities and Social Sciences Communications · doi:10.1057/s41599-023-01633-x · Cited by 55
Curto, G., Jojoa Acosta, M. F., Comim, F., & Garcia-Zapirain, B. (2024) · AI & SOCIETY · doi:10.1007/s00146-022-01494-z · Cited by 53
Implementing AI Ethics: Making Sense of the Ethical Requirements
Agbese, M., Mohanani, R., Khan, A., & Abrahamsson, P. (2023) · Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering · doi:10.1145/3593434.3593453 · Cited by 49
How to design an AI ethics board
Schuett, J., Reuel, A.-K., & Carlier, A. (2025) · AI and Ethics · doi:10.1007/s43681-023-00409-y · Cited by 46
Papyshev, G., & Yarime, M. (2024) · AI & SOCIETY · doi:10.1007/s00146-022-01611-y · Cited by 27
Zhang, X., Zhou, W., Hu, W., Zhou, S., Hu, X., & Yang, L. (2025) · Technology in Society · doi:10.1016/j.techsoc.2025.102900 · Cited by 1
Metadata
- Authors
- Morley, J., Elhalal, A., Garcia, F., Kinsey, L., Mökander, J., & Floridi, L.
- Venue
- Minds and Machines
- Published
- 2021-06
- Volume
- 31
- Issue
- 2
- Pages
- 239-256
- ISSN
- 0924-6495 (ISSN-L)
- 1572-8641
- OpenAlex
- W3129283743
- Cited by
- 266
- References
- 29
- FWCI
- 38.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
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