THE INTERSECTION OF ARTIFICIAL INTELLIGENCE AND INTERNATIONAL TRADE LAWS: CHALLENGES AND OPPORTUNITIES
DOI:
https://doi.org/10.31436/iiumlj.v32i1.912Keywords:
Artificial Intelligence, International Trade Laws, Data Protection, Intellectual Property Rights, Trade Barriers, Regulatory HarmonisationAbstract
Artificial Intelligence (AI) is reshaping international trade, presenting both challenges and opportunities for existing global legal frameworks. This research explores the intersection of AI and international trade laws, focusing on key areas such as data protection, intellectual property rights (IPR), trade barriers, and regulatory harmonisation. The cross-border flow of data in trade activities raises concerns about privacy and data protection, necessitating the balance between trade liberalisation and regulatory compliance. Moreover, the emergence of AI-generated intellectual property assets poses novel questions regarding ownership, liability, and enforcement mechanisms. Discriminatory practices and trade barriers fueled by AI-driven automation and predictive analytics threaten market access and fair competition. Harmonising regulatory approaches to AI governance is imperative to promote interoperability, innovation, and market integration. Despite these challenges, AI offers significant opportunities to enhance trade facilitation, efficiency, and dispute resolution mechanisms. Embracing AI technologies can streamline supply chains, reduce transaction costs, and expedite customs procedures. Additionally, AI-driven dispute resolution mechanisms offer innovative solutions to resolve trade disputes promptly and efficiently. To address these complexities, policymakers must enhance data governance frameworks, promote IPR harmonisation, and foster regulatory cooperation at both domestic and international levels. By embracing the transformative potential of AI while upholding fundamental principles of fairness and transparency, stakeholders can build a more resilient and inclusive global trading system. The qualitative research methodology has been applied to the following article.
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References
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