Intellectual Property in Language Models: Challenges of Ownership in the Integration of Multiple Databases

This work is the result of the project Innovative Solution for Generative Artificial Intelligence for Automated Responses, developed within the research group Centro de Competências em Soluções Livres at IFRN (CCSL-IFRN), and addresses the legal challenges related to intellectual property ownership and data protection in the development of language models based on Artificial Intelligence (AI). The study of this topic is relevant due to the insufficiency of current legislation in dealing with issues such as authorship, use of sensitive data, and liability. The objective of this work is to analyze these challenges and propose guidelines for a regulatory framework that balances innovation and the protection of rights. The methodology consists of qualitative research, using a hypothetical-deductive approach, employing bibliographic, documentary, and jurisprudential analysis. Based on the analysis conducted, it is concluded that a specific regulatory framework is necessary to address the peculiarities of language models, ensuring clarity in defining ownership and respecting the rights involved.

Authors

Publication Details

Journal
Beijing Law Review
Published
2025-01-01
DOI
https://doi.org/10.4236/blr.2025.161012
Citations
2
Primary Topic
Intellectual Property and Patents
Type
article
Field-Weighted Citation Impact
5.52
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article

Intellectual Property in Language Models: Challenges of Ownership in the Integration of Multiple Databases

Max Miller Silveira, Gonçalo A. Oliveira, Thiago Murilo Nobrega Galvão, Rocco Antônio Rangel Rosso Nelson et al.
2 citations
Beijing Law Review
Intellectual Property and Patents
5.52
article

Intellectual Property in Language Models: Challenges of Ownership in the Integration of Multiple Databases

Max Miller Silveira, Gonçalo A. Oliveira, Thiago Murilo Nobrega Galvão, Rocco Antônio Rangel Rosso Nelson, Thiago de Bessa da Silva, Thiago Vinícius Santana Costa, Moisés Cirilo de Brito Souto, Anderson Zanati Dultra, Tawfic Awwad Júnior
article en
2 citations

Abstract

This work is the result of the project Innovative Solution for Generative Artificial Intelligence for Automated Responses, developed within the research group Centro de Competências em Soluções Livres at IFRN (CCSL-IFRN), and addresses the legal challenges related to intellectual property ownership and data protection in the development of language models based on Artificial Intelligence (AI). The study of this topic is relevant due to the insufficiency of current legislation in dealing with issues such as authorship, use of sensitive data, and liability. The objective of this work is to analyze these challenges and propose guidelines for a regulatory framework that balances innovation and the protection of rights. The methodology consists of qualitative research, using a hypothetical-deductive approach, employing bibliographic, documentary, and jurisprudential analysis. Based on the analysis conducted, it is concluded that a specific regulatory framework is necessary to address the peculiarities of language models, ensuring clarity in defining ownership and respecting the rights involved.

Beijing Law ReviewVol. 16(01)
Openalex Percentile: Top 6%
Intellectual Property and Patents
5.52
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Intellectual Property in Language Models: Challenges of Ownership in the Integration of Multiple Databases — Max Miller Silveira, Gonçalo A. Oliveira, et al. · Beijing Law Review (2025) | TGRS Research Map | TGRS