Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of AI

Daniel Mcduff, Tim Korjakow, Scott Cambo, Jesse Josua Benjamin, Jenny Lee, Yacine Jernite, Carlos Muñoz Ferrandis, Aaron Gokaslan, Alek Tarkowski, Joseph Lindley, A. Feder Cooper, Danish Contractor
Proceedings of the 41st International Conference on Machine Learning, PMLR 235:35255-35266, 2024.

Abstract

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.

Cite this Paper

BibTeX
@InProceedings{pmlr-v235-mcduff24a, title = {Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of {AI}}, author = {Mcduff, Daniel and Korjakow, Tim and Cambo, Scott and Benjamin, Jesse Josua and Lee, Jenny and Jernite, Yacine and Mu\~{n}oz Ferrandis, Carlos and Gokaslan, Aaron and Tarkowski, Alek and Lindley, Joseph and Cooper, A. Feder and Contractor, Danish}, booktitle = {Proceedings of the 41st International Conference on Machine Learning}, pages = {35255--35266}, year = {2024}, editor = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix}, volume = {235}, series = {Proceedings of Machine Learning Research}, month = {21--27 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v235/main/assets/mcduff24a/mcduff24a.pdf}, url = {https://proceedings.mlr.press/v235/mcduff24a.html}, abstract = {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.} }
Endnote
%0 Conference Paper %T Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of AI %A Daniel Mcduff %A Tim Korjakow %A Scott Cambo %A Jesse Josua Benjamin %A Jenny Lee %A Yacine Jernite %A Carlos Muñoz Ferrandis %A Aaron Gokaslan %A Alek Tarkowski %A Joseph Lindley %A A. Feder Cooper %A Danish Contractor %B Proceedings of the 41st International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2024 %E Ruslan Salakhutdinov %E Zico Kolter %E Katherine Heller %E Adrian Weller %E Nuria Oliver %E Jonathan Scarlett %E Felix Berkenkamp %F pmlr-v235-mcduff24a %I PMLR %P 35255--35266 %U https://proceedings.mlr.press/v235/mcduff24a.html %V 235 %X 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.
APA
Mcduff, D., Korjakow, T., Cambo, S., Benjamin, J.J., Lee, J., Jernite, Y., Muñoz Ferrandis, C., Gokaslan, A., Tarkowski, A., Lindley, J., Cooper, A.F. & Contractor, D.. (2024). Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of AI. Proceedings of the 41st International Conference on Machine Learning, in Proceedings of Machine Learning Research 235:35255-35266 Available from https://proceedings.mlr.press/v235/mcduff24a.html.

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