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
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BackgroundInfluential
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
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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).”
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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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