Karakteristik Yuridis Pelanggaran Hak Cipta dalam Penggunaan Data untuk Pelatihan Large Language Model (LLM) Generatif - Asep Supriyadi; Aturkian Laia (INDO PUBLISHING, 2026)
The rapid development of generative artificial intelligence, particularly Large Language Models (LLMs), has created new copyright issues concerning the use of copyrighted works as training data without the authors’ permission. This study aims to examine the legal characteristics of copyrighted data used in LLM training, identify potential copyright infringements under Indonesian law, and analyze the regulatory challenges surrounding generative AI. The research employs a normative legal method using statutory and conceptual approaches, based on Law Number 28 of 2014 on Copyright, the Electronic Information and Transactions Law, and relevant academic literature. The findings indicate that data scraping, reproduction, and data processing for AI training may infringe the exclusive rights of copyright holders because such activities do not fall within the scope of fair use. The absence of explicit regulation on text and data mining creates legal uncertainty. Therefore, Indonesia should establish specific copyright exceptions, collective licensing mechanisms, and fair compensation to balance AI innovation with copyright protection.