Madani: Multidisciplinary Scientific Journal
Vol 3, No 3 (2025): April 2025

Artificial Intelligence and Global Governance: Regulatory Opportunities and Ethnical Challenges

Rohida, Leni (Unknown)
Asyifa, Eteh Resa (Unknown)



Article Info

Publish Date
24 Apr 2025

Abstract

The rapid development of Artificial Intelligence (AI) has brought significant transformations in various aspects of life, including global governance. However, this progress also presents complex ethical and regulatory challenges. This study aims to analyze regulatory opportunities and ethical challenges arising from the integration of AI in global governance. It is based on the increasing use of AI across various sectors, such as healthcare, finance, and defense, which raises concerns related to privacy, algorithmic bias, accountability, and global disparities. Without an adequate regulatory framework, the potential misuse of AI could threaten social stability and global security. The objective of this study is to identify opportunities for developing effective and sustainable regulations and to examine the ethical challenges that need to be addressed in AI implementation. The research employs a qualitative methodology with a literature review and policy analysis approach, encompassing a review of existing regulations and case studies. The findings indicate that while AI offers significant opportunities to enhance efficiency and innovation, ethical challenges such as algorithmic bias, lack of transparency, and global inequities remain major obstacles. On the other hand, this study identifies opportunities to strengthen regulatory frameworks through international collaboration, AI ethics standardization, and increased public awareness. The conclusion of this study highlights the importance of a multistakeholder approach in developing inclusive and equitable AI regulations. The proposed policy recommendations include establishing a global oversight body, enhancing AI literacy, and integrating ethical principles into the design and implementation of AI systems.

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