aceLegal Ethics of Generative Artificial Intelligence Training Data Usage in Large Language Models: Copyright and Personal Data Perspective
This research originates from security and privacy risks associated with Generative AI Large Language Models (LLMs), especially concerning data used for training in relation to Intellectual Property Rights (IPR) and Personal Data Protection (PDP). The study seeks to examine existing regulatory guidance and develop a national framework that protects user privacy and IPR. The method employs normative legal research using statutory and conceptual approaches, by reviewing the legal frameworks of Indonesia, South Kor…
A legal analysis of Indonesian, South Korean, EU and Japanese rules found that large language models keep absorbing users' prompts, data and corrections for training, which exposes security weaknesses under personal data protection laws and risks harming original creators.
The conclusions come from normative legal analysis of four jurisdictions plus direct prompt testing, and the proposed framework and shared responsibility model are recommendations that have not been tested in practice.
Sources
- Peer-reviewedJurnal Pembangunan Hukum Indonesia2026-11-06
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Truvace Impact Record TRV-2026-2413, v1: “Legal Ethics of Generative Artificial Intelligence Training Data Usage in Large Language Models: Copyright and Personal Data Perspective.” Truvace, 2026-11-07. /record/TRV-2026-2413 (accessed on the day you copy it). sha256 92fec6605aa0823e…
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