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.

翻译：对人工智能的疏忽或恶意使用日益增长的担忧，提升了业界对有助于管理该技术风险的工具的需求。2018年，带有行为使用条款的许可（通常称为“负责任人工智能许可”）被提出，旨在为开发者提供发布人工智能资产时，通过约束其用户行为以减轻负面应用的框架。截至2023年底，约有4万个软件和模型仓库采纳了负责任人工智能许可。采用行为使用条款的知名模型包括BLOOM（语言）、LLaMA2（语言）、Stable Diffusion（图像）和GRID（机器人学）。本文探究了这些许可被采纳的原因与方式，以及它们为适应特定用例而进行调整的原因与方式。我们采用混合方法研究，结合定性访谈、许可条款聚类分析以及许可采纳的定量分析。基于这些证据，我们认为负责任人工智能许可需要标准化，以避免混淆用户或削弱其影响力。同时，在某些情境下（如医疗领域），对行为限制进行定制化也是适当的。我们倡导能够满足用户需求并可通过工具支持的“标准化定制”。