Toward Effective AI Governance: A Review of Principles

• URL: http://arxiv.org/abs/2505.23417v1
• Date: Thu, 29 May 2025 13:07:45 GMT
• Title: Toward Effective AI Governance: A Review of Principles
• Authors: Danilo Ribeiro, Thayssa Rocha, Gustavo Pinto, Bruno Cartaxo, Marcelo Amaral, Nicole Davila, Ana Camargo,
• Abstract summary: The aim of this study is to identify which frameworks, principles, mechanisms, and stakeholder roles are emphasized in secondary literature on AI governance.<n>The most cited frameworks include the EU AI Act and NIST RMF; transparency and accountability are the most common principles.
• Score: 2.5411385112104448
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Artificial Intelligence (AI) governance is the practice of establishing frameworks, policies, and procedures to ensure the responsible, ethical, and safe development and deployment of AI systems. Although AI governance is a core pillar of Responsible AI, current literature still lacks synthesis across such governance frameworks and practices. Objective: To identify which frameworks, principles, mechanisms, and stakeholder roles are emphasized in secondary literature on AI governance. Method: We conducted a rapid tertiary review of nine peer-reviewed secondary studies from IEEE and ACM (20202024), using structured inclusion criteria and thematic semantic synthesis. Results: The most cited frameworks include the EU AI Act and NIST RMF; transparency and accountability are the most common principles. Few reviews detail actionable governance mechanisms or stakeholder strategies. Conclusion: The review consolidates key directions in AI governance and highlights gaps in empirical validation and inclusivity. Findings inform both academic inquiry and practical adoption in organizations.

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