Unlocking Fair Use in the Generative AI Supply Chain: A Systematized Literature Review
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866913455358869504 |
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| author | Mahuli, Amruta Biega, Asia |
| author_facet | Mahuli, Amruta Biega, Asia |
| contents | Through a systematization of generative AI (GenAI) stakeholder goals and expectations, this work seeks to uncover what value different stakeholders see in their contributions to the GenAI supply line. This valuation enables us to understand whether fair use advocated by GenAI companies to train model progresses the copyright law objective of promoting science and arts. While assessing the validity and efficacy of the fair use argument, we uncover research gaps and potential avenues for future works for researchers and policymakers to address. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_00613 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Unlocking Fair Use in the Generative AI Supply Chain: A Systematized Literature Review Mahuli, Amruta Biega, Asia Artificial Intelligence Computers and Society Machine Learning Through a systematization of generative AI (GenAI) stakeholder goals and expectations, this work seeks to uncover what value different stakeholders see in their contributions to the GenAI supply line. This valuation enables us to understand whether fair use advocated by GenAI companies to train model progresses the copyright law objective of promoting science and arts. While assessing the validity and efficacy of the fair use argument, we uncover research gaps and potential avenues for future works for researchers and policymakers to address. |
| title | Unlocking Fair Use in the Generative AI Supply Chain: A Systematized Literature Review |
| topic | Artificial Intelligence Computers and Society Machine Learning |
| url | https://arxiv.org/abs/2408.00613 |