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| Format: | Preprint |
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2024
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| Online-Zugang: | https://arxiv.org/abs/2402.05979 |
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| _version_ | 1866909099297341440 |
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| author | McDuff, Daniel Korjakow, Tim Cambo, Scott Benjamin, Jesse Josua Lee, Jenny Jernite, Yacine Ferrandis, Carlos Muñoz Gokaslan, Aaron Tarkowski, Alek Lindley, Joseph Cooper, A. Feder Contractor, Danish |
| author_facet | McDuff, Daniel Korjakow, Tim Cambo, Scott Benjamin, Jesse Josua Lee, Jenny Jernite, Yacine Ferrandis, Carlos Muñoz Gokaslan, Aaron Tarkowski, Alek Lindley, Joseph Cooper, A. Feder Contractor, Danish |
| contents | Growing concerns over negligent or malicious uses of AI have increased the appetite for tools that help manage the risks of the technology. In 2018, licenses with behaviorial-use clauses (commonly referred to as Responsible AI Licenses) were proposed to give developers a framework for releasing AI assets while specifying their users to mitigate negative applications. As of the end of 2023, on the order of 40,000 software and model repositories have adopted responsible AI licenses licenses. Notable models licensed with behavioral use clauses include BLOOM (language) and LLaMA2 (language), Stable Diffusion (image), and GRID (robotics). This paper explores why and how these licenses have been adopted, and why and how they have been adapted to fit particular use cases. We use a mixed-methods methodology of qualitative interviews, clustering of license clauses, and quantitative analysis of license adoption. Based on this evidence we take the position that responsible AI licenses need standardization to avoid confusing users or diluting their impact. At the same time, customization of behavioral restrictions is also appropriate in some contexts (e.g., medical domains). We advocate for ``standardized customization'' that can meet users' needs and can be supported via tooling. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_05979 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On the Standardization of Behavioral Use Clauses and Their Adoption for Responsible Licensing of AI McDuff, Daniel Korjakow, Tim Cambo, Scott Benjamin, Jesse Josua Lee, Jenny Jernite, Yacine Ferrandis, Carlos Muñoz Gokaslan, Aaron Tarkowski, Alek Lindley, Joseph Cooper, A. Feder Contractor, Danish Software Engineering Artificial Intelligence Growing concerns over negligent or malicious uses of AI have increased the appetite for tools that help manage the risks of the technology. In 2018, licenses with behaviorial-use clauses (commonly referred to as Responsible AI Licenses) were proposed to give developers a framework for releasing AI assets while specifying their users to mitigate negative applications. As of the end of 2023, on the order of 40,000 software and model repositories have adopted responsible AI licenses licenses. Notable models licensed with behavioral use clauses include BLOOM (language) and LLaMA2 (language), Stable Diffusion (image), and GRID (robotics). This paper explores why and how these licenses have been adopted, and why and how they have been adapted to fit particular use cases. We use a mixed-methods methodology of qualitative interviews, clustering of license clauses, and quantitative analysis of license adoption. Based on this evidence we take the position that responsible AI licenses need standardization to avoid confusing users or diluting their impact. At the same time, customization of behavioral restrictions is also appropriate in some contexts (e.g., medical domains). We advocate for ``standardized customization'' that can meet users' needs and can be supported via tooling. |
| title | On the Standardization of Behavioral Use Clauses and Their Adoption for Responsible Licensing of AI |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2402.05979 |