The DOI matches its Crossref record; 0 of the 27 references it cites were found in a registry or an index.
Beyond the promise: implementing ethical AI
Open accessAbstract
Artificial Intelligence (AI) applications can and do have unintended negative consequences for businesses if not implemented with care. Specifically, faulty or biased AI applications risk compliance and governance breaches and damage to the corporate brand. These issues commonly arise from a number of pitfalls associated with AI development, which include rushed development, a lack of technical understanding, and improper quality assurance, among other factors. To mitigate these risks, a growing number of organisations are working on ethical AI principles and frameworks. However, ethical AI principles alone are not sufficient for ensuring responsible AI use in enterprises. Businesses also require strong, mandated governance controls including tools for managing processes and creating associated audit trails to enforce their principles. Businesses that implement strong governance frameworks, overseen by an ethics board and strengthened with appropriate training, will reduce the risks associated with AI. When applied to AI modelling, the governance will also make it easier for businesses to bring their AI deployments to scale.
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“The rapid evolution of AI technologies has outpaced the formulation of comprehensive ethical guidelines, raising concerns about the potential misuse and unintended consequences of these powerful tools [32], [33].”
From Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond (2024) · cites this paper as [33]
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The Institute for Ethical AI & Machine Learning: The responsible machine learning principles. https://www.ethical.institute/principles.html. Accessed 27 July 2020
(n.d.)
UnresolvedUNI Global Union: Top 10 principles for ethical artificial intelligence. https://www.thefutureworldofwork.org/media/35420/uni_ethical_ai.pdf (2017). Accessed 27 July 2020
(n.d.)
UnresolvedMicrosoft: Responsible AI. https://www.microsoft.com/en-us/ai/responsible-ai?activetab=pivot1:primaryr6/. Accessed 27 July 2020
(n.d.)
UnresolvedOrganisation for Responsible Business: What is responsible business. https://www.orbuk.org.uk/what-is-responsible-business/. Accessed 27 July 2020 and Online document Global Initiatives. Responsible Business. https://www.responsiblebusiness.com/. Accessed 27 July 2020
(n.d.)
UnresolvedGartner: Gartner says nearly half of CIOs are planning to deploy artificial intelligence. https://www.gartner.com/en/newsroom/press-releases/2018-02-13-gartner-says-nearly-half-of-cios-are-planning-to-deploy-artificial-intelligence (2018). Accessed 27 July 2020
(n.d.)
UnresolvedKanioura, A., Lucini, F.: Ready. Set. Scale. Accenture. https://www.accenture.com/us-en/insights/artificial-intelligence/scaling-enterprise-ai?src=SOMS&c=acn_glb_scalingenterpriexacttarget_11099764&n=emc_0120 (2019). Accessed 27 July 2020
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UnresolvedAccenture: AI ethics and governance. https://www.accenture.com/us-en/services/applied-intelligence/ai-ethics-governance. Accessed 27 July 2020
(n.d.)
UnresolvedMarr, B.: Is artificial intelligence dangerous? 6 AI risks everyone should know about. Forbes.https://www.forbes.com/sites/bernardmarr/2018/11/19/is-artificial-intelligence-dangerous-6-ai-risks-everyone-should-know-about/#5920f7dc2404(2018). Accessed 27 July 2020
(n.d.)
UnresolvedDastin, J.: Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G (2018). Accessed 27 July 2020
(n.d.)
UnresolvedHunt, E.: Tay, Microsoft's AI chatbot, gets a crash course in racism from Twitter. https://www.theguardian.com/technology/2016/mar/24/tay-microsofts-ai-chatbot-gets-a-crash-course-in-racism-from-twitter (2016). Accessed 27 July 2020
(n.d.)
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Cited by
Sorted by citations
Grassini, S. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1191628 · Cited by 330
“Investigating this area can yield invaluable insights into the determinants influencing individuals’ acceptance or resistance to AI, as well as the potential benefits and risks they associate with its deployment (Nadimpalli, 2017; Eitel-Porter, 2021).”
BackgroundDefining organizational AI governance
Mäntymäki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022) · AI and Ethics · doi:10.1007/s43681-022-00143-x · Cited by 378
“Thus, the current unorganized state of AI governance literature is unfortunate because organizations deploying AI in their operations play a key role in implementing AI governance in practice [13, 16, 17].”
BackgroundInfluentialAkinrinola, O., Okoye, C. C., Ofodile, O. C., & Ugochukwu, C. E. (2024) · GSC Advanced Research and Reviews · doi:10.30574/gscarr.2024.18.3.0088 · Cited by 206
“Their role is to develop, implement, and enforce ethical guidelines for AI development, ensuring alignment with organizational values and societal expectations (Eitel-Porter, 2021).”
BackgroundEthical Framework for Harnessing the Power of AI in Healthcare and Beyond
Nasir, S., Khan, R. A., & Bai, S. (2024) · IEEE Access · doi:10.1109/access.2024.3369912 · Cited by 152
“The rapid evolution of AI technologies has outpaced the formulation of comprehensive ethical guidelines, raising concerns about the potential misuse and unintended consequences of these powerful tools [32], [33].”
BackgroundEthical management of human-AI interaction: Theory development review
Hammerschmidt, T., Passlack, N., & Posegga, O. (2023) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2023.101772 · Cited by 195
Metadata
- Authors
- Eitel-Porter, R.
- Affiliations
- Accenture (United Kingdom) (GB)
- Corresponding author
- Eitel-Porter, Ray
- Venue
- AI and Ethics
- Published
- 2020-10-06
- Volume
- 1
- Issue
- 1
- Pages
- 73-80
- ISSN
- 2730-5953 (ISSN-L)
- 2730-5961
- OpenAlex
- W3092263108
- Cited by
- 245
- References
- 27
- Citations by year
- 2026: 37 · 2025: 62 · 2024: 72 · 2023: 37 · 2022: 25 · 2021: 12
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- AI and Ethics (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- ethical AI, AI governance, responsible AI, algorithmic bias, AI risk management, AI ethics principles, ethics boards, audit trail
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