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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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Ye, D., Yuan, R., Luo, J., Liu, M. J., & Yannopoulou, N. (2025) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2025.124349 · Cited by 16
An Integrative Theoretical Framework for Responsible Artificial Intelligence
Haidar, A. (2023) · International Journal of Digital Strategy Governance and Business Transformation · doi:10.4018/ijdsgbt.334844 · Cited by 23
A DSL for Testing LLMs for Fairness and Bias
Morales, S., Clarisó, R., & Cabot, J. (2024) · ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS) · doi:10.1145/3640310.3674093 · Cited by 22
“The works of several researchers [12, 14, 24], the European Commission [9], the European Union AI Act [13], and the UNESCO recommendation on the ethics of AI [38], among others, constitute this basis.”
Chatikobo, M. V., & Pasipamire, N. (2024) · Cogent Education · doi:10.1080/2331186x.2024.2425209 · Cited by 30
Exploring the impact of responsible AI usage on users’ behavioral intentions
Chedrawi, C., Haddad, G., Tarhini, A. A., Osta, S., & Kazoun, N. (2025) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100813 · Cited by 21
Risk as a driver for AI framework development on manufacturing
Vyhmeister, E., González-Castañé, G., & Östbergy, P.-O. (2022) · AI and Ethics · doi:10.1007/s43681-022-00159-3 · Cited by 15
“The trends show that around 85% of the AI projects could deliver erroneous outcomes due to bias in data, algorithms, or poor managing by the teams involved in their development and implementation [25].”
BackgroundLay User Involvement in Developing Human-centric Responsible AI Systems: When and How?
Vincenzi, B., Stumpf, S., Taylor, A. S., & Nakao, Y. (2024) · ACM Journal on Responsible Computing · doi:10.1145/3652592 · Cited by 16
“The options (see Appendix A.2 ) for this question were always the same at each stage, and were based on prior literature and common real-world practices (e.g., References [ 35 , 69 , 71 , 89 ]).”
MethodResponsible AI-Based Business Process Management and Improvement
Pisoni, G., & Moloney, M. (2024) · Digital Society · doi:10.1007/s44206-024-00105-2 · Cited by 18
Care robot literacy: integrating AI ethics and technological literacy in contemporary healthcare
Turja, T., Kork, A., Ilomäki, S., Hellstrand, I., & Koistinen, A.-K. (2024) · AI and Ethics · doi:10.1007/s43681-024-00576-6 · Cited by 22
“The convergence of these phases is evident as AI development is already characterized by its pursuit of fairness, trustworthiness and empowerment of users [59].”
Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer
Chatterjee, A., Riegler, M. A., Ganesh, K., & Halvorsen, P. (2025) · Scientific Reports · doi:10.1038/s41598-025-87510-w · Cited by 15
Serdenia, J. R. C., Dumagay, A. H., Balasa, K. A., Capacio, E. A., & Lauzon, L. D. S. (2025) · LatIA · doi:10.62486/latia2025313 · Cited by 21
Møgelvang, A., & Grassini, S. (2025) · Discover Education · doi:10.1007/s44217-025-00657-6 · Cited by 16
“These attitudes influence not only user engagement but also the ethical deployment, regulatory frameworks, and societal acceptance of AI systems [7–9].”
Skeja, A., & Sadiku-Dushi, N. (2025) · Leadership & Organization Development Journal · doi:10.1108/lodj-06-2025-0530 · Cited by 19
Transparency and Accountability
Pappachan, P., Moslehpour, M., Bansal, R., & Rahaman, M. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-3860-5.ch006 · Cited by 15
Musa, S., Abubakari, M. S., & Abdulwahab, L. O. (2025) · Advances in multimedia and interactive technologies book series · doi:10.4018/979-8-3373-1681-9.ch012 · Cited by 13
Algorithmic Social Injustices: Antecedents and Mitigations
Tanriverdi̇, H., & Akinyemi, J.-P. O. (2025) · MIS Quarterly · doi:10.25300/misq/2025/18314 · Cited by 15
Artificial Intelligence and Ethics Challenges of Technologies
Marino, D., Cananzi, D. M., & Aragona, F. (2024) · Studies in systems, decision and control · doi:10.1007/978-3-031-50902-5_3 · Cited by 10
Business Management Transformation Through the Influence of Artificial Intelligence
Prorok, M., & Takács, I. (2024) · IEEE International Symposium on Intelligent Systems and Informatics (SISY) · doi:10.1109/sisy62279.2024.10737615 · Cited by 10
“The integration of artificial intelligence into an expanding range of business management domains necessitates ongoing scrutiny of this subject matter [4].”
BackgroundThe Role of Artificial Intelligence in Business Management
Nadi, A. H., Ahshan, K. A., Rahman, S. M. M., & Sofin, M. R. (2024) · Advances in business information systems and analytics book series · doi:10.4018/979-8-3693-1842-3.ch008 · Cited by 11
Prem, E. (2023) · Springer eBooks · doi:10.1007/978-3-031-45304-5_15 · Cited by 9
Towards a Definition of a Responsible Artificial Intelligence
Göllner, S., Tropmann-Frick, M., & Brumen, B. (2024) · Frontiers in artificial intelligence and applications · doi:10.3233/faia231146 · Cited by 10
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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