Artificial Intelligence in Monitoring Trademark and Domain Name Infringement in Intellectual Property Law in Indonesia
DOI:
https://doi.org/10.25139/lex.v9i4.11042Keywords:
Artificial Intelligence, Intellectual Property, TrademarkAbstract
This research examines the implementation of artificial intelligence technologies within Indonesia's trademark and domain name infringement monitoring system through normative legal analysis. The study investigates how AI integration can enhance enforcement mechanisms while addressing the complex legal challenges that emerge from automated enforcement procedures. The research employs legal instrumentalism and responsive law theories to analyze Indonesia's existing intellectual property legal framework and identify regulatory requirements for AI implementation. The analysis reveals that Indonesia's Law Number 20 of 2016 concerning Trademarks and Geographical Indications provides sufficient statutory foundation for AI integration through Article 83's surveillance authority, enabling deployment of machine learning algorithms, natural language processing, and computer vision technologies for proactive infringement detection. However, contemporary digital infringement activities, including sophisticated cybersquatting, algorithmic trademark manipulation, and cross-border enforcement challenges, expose structural limitations of traditional enforcement approaches that necessitate technological enhancement. The study identifies significant legal challenges, including accuracy and reliability requirements for automated decision-making, due process and procedural fairness considerations under Indonesia's constitutional framework, data privacy obligations under Law Number 27 of 2022, and liability frameworks for AI-generated enforcement actions. The research concludes that successful AI implementation requires comprehensive regulatory reform, including legislative amendments, standard operating procedures, certification requirements, and inter-agency coordination mechanisms. The findings demonstrate that while existing legal frameworks provide foundational authority for AI integration, specific regulatory provisions must be developed to address algorithmic accountability, maintain procedural safeguards, and balance enforcement efficiency with constitutional protections. This research contributes essential insights for policymakers developing AI governance frameworks in intellectual property enforcement contexts.
References
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