On the Standardization of Behavioral Use Clauses and Their Adoption for Responsible Licensing of AI
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Abstract (arXiv)
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.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 18 of its 38 references that are in the map. First posted on arXiv 7 Feb 2024.
Builds on
18 of 38 references.
References · 18
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6 more
- 2020Behavioral Use Licensing for Responsible AIcited by 46
- 2023Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chaincited by 45
- 2022Edge Impulse: An MLOps Platform for Tiny Machine Learningcited by 24
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- 2023GRID: A Platform for General Robot Intelligence Developmentcited by 6
Built on by
Citing papers per year: 2024: 5; 2025: 1; 2026: 1.
7 papers.
- 2024Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Researchcited by 14
- 2024Acceptable Use Policies for Foundation Modelscited by 12
- 2024The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resourcescited by 11
- 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Modelscited by 1
- 2024Responsible AI in Open Ecosystems: Reconciling Innovation with Risk Assessment and Disclosurecited by 0
- 2025Opening the Scope of Openness in AIcited by 0
- 2026A governance horizon for ethical-use constraints in open-weight AI modelscited by 0
- 2026A governance horizon for ethical-use constraints in open-weight AI models23 May 2026
- 2025Opening the Scope of Openness in AI9 May 2025
- 2024Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research9 Dec 2024
- 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models17 Oct 2024
- 2024Responsible AI in Open Ecosystems: Reconciling Innovation with Risk Assessment and Disclosure27 Sep 2024
- 2024Acceptable Use Policies for Foundation Models29 Aug 2024
- 2024The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources24 Jun 2024
Similar, not cited
Close in wording, no citation either way
- 2025Who is Responsible? The Data, Models, Users or Regulations? A Comprehensive Survey on Responsible Generative AI for a Sustainable Future
- 2024"They've Stolen My GPL-Licensed Model!": Toward Standardized and Transparent Model Licensing
- 2026Do User-Authored Permission Policies Improve Protection Against AI Agent Overreach?
- 2025From Legal Text to Tech Specs: Generative AI's Interpretation of Consent in Privacy Law ↗
- 2025Are We Aligned? A Preliminary Investigation of the Alignment of Responsible AI Values between LLMs and Human Judgment
- 2026AI Agents Under EU Law
- 2025A Different Approach to AI Safety: Proceedings from the Columbia Convening on Openness in Artificial Intelligence and AI Safety
- 2026Responsible AI for General-Purpose Systems: Overview, Challenges, and A Path Forward