New Tools are Needed for Tracking Adherence to AI Model Behavioral Use Clauses

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: McDuff, Daniel, Korjakow, Tim, Klyman, Kevin, Contractor, Danish
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866908382799069184
author McDuff, Daniel
Korjakow, Tim
Klyman, Kevin
Contractor, Danish
author_facet McDuff, Daniel
Korjakow, Tim
Klyman, Kevin
Contractor, Danish
contents Foundation models have had a transformative impact on AI. A combination of large investments in research and development, growing sources of digital data for training, and architectures that scale with data and compute has led to models with powerful capabilities. Releasing assets is fundamental to scientific advancement and commercial enterprise. However, concerns over negligent or malicious uses of AI have led to the design of mechanisms to limit the risks of the technology. The result has been a proliferation of licenses with behavioral-use clauses and acceptable-use-policies that are increasingly being adopted by commonly used families of models (Llama, Gemma, Deepseek) and a myriad of smaller projects. We created and deployed a custom AI licenses generator to facilitate license creation and have quantitatively and qualitatively analyzed over 300 customized licenses created with this tool. Alongside this we analyzed 1.7 million models licenses on the HuggingFace model hub. Our results show increasing adoption of these licenses, interest in tools that support their creation and a convergence on common clause configurations. In this paper we take the position that tools for tracking adoption of, and adherence to, these licenses is the natural next step and urgently needed in order to ensure they have the desired impact of ensuring responsible use.
format Preprint
id arxiv_https___arxiv_org_abs_2505_22287
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle New Tools are Needed for Tracking Adherence to AI Model Behavioral Use Clauses
McDuff, Daniel
Korjakow, Tim
Klyman, Kevin
Contractor, Danish
Computers and Society
Artificial Intelligence
Foundation models have had a transformative impact on AI. A combination of large investments in research and development, growing sources of digital data for training, and architectures that scale with data and compute has led to models with powerful capabilities. Releasing assets is fundamental to scientific advancement and commercial enterprise. However, concerns over negligent or malicious uses of AI have led to the design of mechanisms to limit the risks of the technology. The result has been a proliferation of licenses with behavioral-use clauses and acceptable-use-policies that are increasingly being adopted by commonly used families of models (Llama, Gemma, Deepseek) and a myriad of smaller projects. We created and deployed a custom AI licenses generator to facilitate license creation and have quantitatively and qualitatively analyzed over 300 customized licenses created with this tool. Alongside this we analyzed 1.7 million models licenses on the HuggingFace model hub. Our results show increasing adoption of these licenses, interest in tools that support their creation and a convergence on common clause configurations. In this paper we take the position that tools for tracking adoption of, and adherence to, these licenses is the natural next step and urgently needed in order to ensure they have the desired impact of ensuring responsible use.
title New Tools are Needed for Tracking Adherence to AI Model Behavioral Use Clauses
topic Computers and Society
Artificial Intelligence
url https://arxiv.org/abs/2505.22287