A survey on ethical principles of AI and implementations
Open accessAbstract
AI has powerful capabilities in prediction, automation, planning, targeting, and personalisation. Generally, it is assumed that AI can enable machines to exhibit human-like intelligence, and is claimed to benefit to different areas of our lives. Since AI is fueled by data and is a distinct form of autonomous and self-learning agency, we are seeing increasing ethical concerns related to AI uses. In order to mitigate various ethical concerns, national and international organisations including governmental organisations, private sectors as well as research institutes have made extensive efforts by drafting ethical principles of AI, and having active discussions on ethics of AI within and beyond the AI community. This paper investigates these efforts with a focus on the identification of fundamental ethical principles of AI and their implementations. The review found that there is a convergence around limited principles and the most prevalent principles are transparency, justice and fairness, responsibility, non-maleficence, and privacy. The investigation suggests that ethical principles need to be combined with every stages of the AI lifecycle in the implementation to ensure that the AI system is designed, implemented and deployed in an ethical manner. Similar to ethical framework used in biomedical and clinical research, this paper suggests checklist-style questionnaires as benchmarks for the implementation of ethical principles of AI.
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Ethical AI needs different approaches that integrate human involvement, accountability, and management intervention.
“The scholarly argument is that ethical AI needs different approaches that integrate human involvement, accountability, and management intervention [14].”
From Mitigating Bias in Retail AI Hiring Tools: A Human-Centered H-A-I-R-E Governance Framework for Low-Wage Hires (2026) · cites this paper as [14]
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- Authors
- Zhou, J., Chen, F., Berry, A., Reed, M., Zhang, S., & Savage, S.
- Affiliations
- University of Technology Sydney (AU)
- Venue
- 2020 IEEE Symposium Series on Computational Intelligence (SSCI)
- Publisher
- IEEE
- Published
- 2020-12-01
- Pages
- 3010-3017
- OpenAlex
- W3119416105
- Cited by
- 99
- References
- 10
- Citations by year
- 2026: 16 · 2025: 26 · 2024: 24 · 2023: 17 · 2022: 12 · 2021: 4
- FWCI
- 8.56
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- IEEE Symposium Series on Computational Intelligence (SSCI) (publishedVersion)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- AI ethics, transparency, fairness and justice, responsibility, non-maleficence, privacy, AI lifecycle, ethical frameworks
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