This study systematically maps how ethical principles of Artificial Intelligence (AI) and privacy-preserving techniques are embedded in governance frameworks at global, continental, and national levels. It offers a multi-layered comparison of normative, policy, and technical instruments, showing how ethical AI ideals are translated or fail to translate into operational AI governance practices. Using a mixed-methods empirical design, the study analyses 132 documents following a structured coding framework to examine ethical principles, enforceability, and the operationalization of privacy-preserving techniques. The findings show that most frameworks emphasize privacy, transparency, and accountability, yet only a fraction convert these commitments into verifiable technical or regulatory requirements. High ethical values are widespread, but the operational depth of tools such as audits, logging systems, data-protection assessments, and advanced privacy-preserving techniques remains uneven, particularly in resource-constrained settings. Binding instruments demonstrate stronger implementation pathways than advisory values. The study demonstrates persistent gaps between principles and practices and underscores the need for governance models that integrate enforceable controls with locally grounded ethical considerations. It concludes that trustworthy AI in diverse contexts requires verifiable governance through risk-tiered audits, mandatory integration of privacy-enhancing techniques, and community-aligned ethical frameworks.
Research Article | Open Access | Download Full Text
Volume 3 | Issue 4 | Year 2025 | Article Id: AIR-V3I4P102 DOI: https://doi.org/10.59232/AIR-V3I4P102
Ethical AI and Privacy: Strategies for Effective Governance
Taban Habibu, Obudra Ceasar
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 15 Oct 2025 | 26 Nov 2025 | 17 Dec 2025 | 30 Dec 2025 |
Citation
Taban Habibu, Obudra Ceasar. “Ethical AI and Privacy: Strategies for Effective Governance.” DS Journal of Artificial Intelligence and Robotics, vol. 3, no. 4, pp. 44-64, 2025.
Abstract
Keywords
AI ethics, AI governance, Artificial Intelligence, Privacy-preserving techniques, Data privacy.
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