INTELLECTUAL PROPERTY IN THE AI ERA: ENSURING EQUITABLE ACCESS TO MEDICAL INNOVATIONS
The integration of Artificial Intelligence (AI) into the medical field has catalyzed groundbreaking innovations in diagnostics, treatment, and drug discovery, but it also presents complex challenges for intellectual property (IP) law. Traditional IP frameworks are increasingly ill-equipped to addres...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
faculty of law universitas lampung
2025-05-01
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| Series: | Indonesia Private Law Review |
| Subjects: | |
| Online Access: | https://jurnal.fh.unila.ac.id/index.php/iplr/article/view/4048 |
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| Summary: | The integration of Artificial Intelligence (AI) into the medical field has catalyzed groundbreaking innovations in diagnostics, treatment, and drug discovery, but it also presents complex challenges for intellectual property (IP) law. Traditional IP frameworks are increasingly ill-equipped to address issues of ownership, access, and benefit-sharing arising from AI-generated medical inventions. This research examines the limitations of existing IP laws in the context of healthcare AI, with a focus on their impact on equitable access and innovation. Using a literature review methodology, the research analyzes legal developments, empirical studies, and market trends, framed through Public Goods Theory and Collaborative Innovation Theory. The findings reveal that current IP regimes often foster monopolistic control, impeding access to essential AI-driven healthcare technologies, especially in low-resource settings. In response, the research proposes a collaborative IP ownership model that distributes rights among AI developers, healthcare institutions, and patients. This model supports innovation while promoting equitable access through mechanisms such as flexible licensing, price regulation, and public–private partnerships. The research concludes by recommending legal reforms to encourage global collaboration and ensure that the benefits of AI in healthcare are accessible to all. |
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| ISSN: | 2723-259X 2745-9284 |