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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2405.01560 |
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| _version_ | 1866910432501956608 |
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| author | German, Daniel M. |
| author_facet | German, Daniel M. |
| contents | This paper summarizes the current copyright related risks that Machine Learning (ML) and Artificial Intelligence (AI) systems (including Large Language Models --LLMs) incur. These risks affect different stakeholders: owners of the copyright of the training data, the users of ML/AI systems, the creators of trained models, and the operators of AI systems. This paper also provides an overview of ongoing legal cases in the United States related to these risks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_01560 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Copyright related risks in the creation and use of ML/AI systems German, Daniel M. Software Engineering Computers and Society 68-04 K.5.1 This paper summarizes the current copyright related risks that Machine Learning (ML) and Artificial Intelligence (AI) systems (including Large Language Models --LLMs) incur. These risks affect different stakeholders: owners of the copyright of the training data, the users of ML/AI systems, the creators of trained models, and the operators of AI systems. This paper also provides an overview of ongoing legal cases in the United States related to these risks. |
| title | Copyright related risks in the creation and use of ML/AI systems |
| topic | Software Engineering Computers and Society 68-04 K.5.1 |
| url | https://arxiv.org/abs/2405.01560 |