Pelindungan Hak Cipta atas Karya-Karya Seni yang Digunakan Sebagai Dataset bagi Generative Artificial Intelligence (AI Generatif)

Thadeus, Claudio (2024) Pelindungan Hak Cipta atas Karya-Karya Seni yang Digunakan Sebagai Dataset bagi Generative Artificial Intelligence (AI Generatif). S1 thesis, Universitas Kristen Indonesia.

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Abstract

Kemunculan AI Generatif yang mampu menciptakan karya seni melalui proses komputasi memunculkan isu Hak Cipta. Sebabnya, sistem AI Generatif bergantung kepada dataset yang memuat karya-karya seni untuk dijadikan referensi saat membuat karya baru. Padahal, transformasi Ciptaan bila dilakukan tanpa izin merupakan pelanggaran Hak Cipta. Rumusan masalah dalam skripsi ini adalah bagaimana aturan hukum pelindungan Hak Cipta di Indonesia terkait pemanfaatan karya-karya seni sebagai dataset bagi AI generatif dalam menghasilkan karya seni yang baru dan bagaimana model perlindungan hukum yang ideal. Penelitian ini menggunakan metode penelitian hukum normatif dengan pendekatan perundang-undangan, perbandingan dan konseptual. Data yang digunakan adalah data sekunder berupa bahan hukum primer: Undang-Undang Republik Indonesia Nomor 28 Tahun 2014 tentang Hak Cipta beserta peraturan-peraturan turunannya, dengan undang-undang Hak Cipta dari negara Amerika Serikat, Inggris dan Jepang sebagai pembanding, bahan hukum sekunder diperoleh dari jurnal internasional, sedangkan bahan hukum tersier berupa kamus dan ensiklopedia, yang disusun dan dianalisis. Penelitian ini sampai kepada kesimpulan bahwa No. 28 Tahun 2014 belum mempunyai ketentuan yang relevan terkait pelindungan Hak Cipta dalam dataset AI Generatif. Adapun, karena AI merupakan sesuatu yang relatif masih baru, ada banyak hal terkait pelindungan Hak Cipta yang perlu dieksplorasi, mulai dari pembuatan regulasi, pembentukan lembaga dan mekanisme pengumpulan royalti. Kata Kunci: Artificial Intelligence, kecerdasan buatan, Hak Cipta. / The emergence of Generative AI capable of making artistic works through computational processes raises a Copyright issue. This is because the Generative AI system relies on a dataset containing artistic works that are used as references when creating new works. In fact, transformation of a work is a violation of copyright if carried out without permission. The problem statements in this thesis are how is Copyright protected by the regulations in Indonesia regarding the use of artistic works as datasets for generative AI in producing new works of art and what is the ideal model of legal protection. This research uses normative legal research methods with statutory, comparative, and conceptual approaches. The data used is secondary data with the primary legal materials being Law of the Republic of Indonesia Number 28 of 2014 concerning Copyright and its derivative regulations, with Copyright laws from the United States, United Kingdom, and Japan as a comparison. Secondary legal materials were obtained from international journals, while tertiary legal materials are in the form of dictionaries and encyclopedias, which are compiled and analyzed. The conclusion of this research is that Law No. 28 of 2014 does not yet have relevant provisions regarding copyright protection in Generative AI datasets. Since AI is a relatively new technology, there are many things related to copyright protection that need to be explored, starting from law-making, establishing enforcement institutions and mechanisms for collecting royalties. Keyword: Artificial Intelligence, Copyright

Item Type: Thesis (S1)
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorPanjaitan, HulmanNIDN0020096802hulman.panjaitan@uki.ac.id
Thesis advisorTobing, Gindo L.NIDN8831640017gindo.tobing@uki.ac.id
Subjects: LAW > Law in general. Comparative and uniform law. Jurisprudence > Comparative law. International uniform law > Intellectual property
LAW > Law in general. Comparative and uniform law. Jurisprudence > Comparative law. International uniform law > Intellectual property > Copyright
Divisions: FAKULTAS HUKUM > Ilmu Hukum
Depositing User: Mr Claudio Thadeus
Date Deposited: 07 Mar 2024 10:56
Last Modified: 07 Mar 2024 10:56
URI: http://repository.uki.ac.id/id/eprint/14004

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