mlsanityData to 7 Oct 2026

Behavioral Use Licensing for Responsible AI

arXiv 2011.03116 ↗First posted 4 Nov 2020cs.CYcited by 46

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Abstract (arXiv)

With the growing reliance on artificial intelligence (AI) for many different applications, the sharing of code, data, and models is important to ensure the replicability and democratization of scientific knowledge. Many high-profile academic publishing venues expect code and models to be submitted and released with papers. Furthermore, developers often want to release these assets to encourage development of technology that leverages their frameworks and services. A number of organizations have expressed concerns about the inappropriate or irresponsible use of AI and have proposed ethical guidelines around the application of such systems. While such guidelines can help set norms and shape policy, they are not easily enforceable. In this paper, we advocate the use of licensing to enable legally enforceable behavioral use conditions on software and code and provide several case studies that demonstrate the feasibility of behavioral use licensing. We envision how licensing may be implemented in accordance with existing responsible AI guidelines.

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Nov 2020.

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Citing papers per year: 2022: 7; 2023: 14; 2024: 16; 2025: 5; 2026: 4.

46 papers.

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  2. 2023The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Datasetcited by 148
  3. 2023Auditing large language models: a three-layered approachcited by 135
  4. 2023The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AIcited by 73
  5. 2022rPPG-Toolbox: Deep Remote PPG Toolboxcited by 63
  6. 2023The Gradient of Generative AI Release: Methods and Considerationscited by 63
  7. 2022SimPer: Simple Self-Supervised Learning of Periodic Targetscited by 44
  8. 2024AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policiescited by 34
  9. 2023Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domainscited by 31
  10. 2024Who's in and who's out? A case study of multimodal CLIP-filtering in DataCompcited by 15
  11. 2022Artificial Intelligence for Health Message Generation: Theory, Method, and an Empirical Study Using Prompt Engineeringcited by 14
  12. 2023BigSmall: Efficient Multi-Task Learning for Disparate Spatial and Temporal Physiological Measurementscited by 13
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  2. 2024AFreeCA: Annotation-Free Counting for Allcited by 12
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  4. 2023Motion Matters: Neural Motion Transfer for Better Camera Physiological Measurementcited by 11
  5. 2024The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resourcescited by 11
  6. 2022Can There be Art Without an Artist?cited by 10
  7. 2023Moderating Model Marketplaces: Platform Governance Puzzles for AI Intermediariescited by 9
  8. 2024PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Softwarecited by 9
  9. 2025Comprehensive Analysis of Transparency and Accessibility of ChatGPT, DeepSeek, And other SoTA Large Language Modelscited by 8
  10. 2024On the Standardization of Behavioral Use Clauses and Their Adoption for Responsible Licensing of AIcited by 7
  11. 2023GRID: A Platform for General Robot Intelligence Developmentcited by 6
  12. 2024Rethinking Software Engineering in the Foundation Model Era: A Curated Catalogue of Challenges in the Development of Trustworthy FMwarecited by 6
  13. 2024Copycats: the many lives of a publicly available medical imaging datasetcited by 5
  14. 2024Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineagecited by 4
  15. 2023PyTrial: Machine Learning Software and Benchmark for Clinical Trial Applicationscited by 3
  16. 2023Towards Open Federated Learning Platforms: Survey and Vision from Technical and Legal Perspectivescited by 3
  17. 2024"They've Stolen My GPL-Licensed Model!": Toward Standardized and Transparent Model Licensingcited by 3
  18. 2026Permissive-Washing in the Open AI Supply Chain: A Large-Scale Audit of License Integritycited by 3
  19. 2022Prioritizing Policies for Furthering Responsible Artificial Intelligence in the United Statescited by 2
  20. 2023Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AIcited by 2
  21. 2024Governance of Generative Artificial Intelligence for Companiescited by 2
  22. 2024Using Large Language Models to Enrich the Documentation of Datasets for Machine Learningcited by 2
  23. 2024A Systematic Review of NeurIPS Dataset Management Practicescited by 2
  24. 2023An investigation of licensing of datasets for machine learning based on the GQM modelcited by 1
  25. 2024Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implicationscited by 1
  26. 2025ML-Asset Management: Curation, Discovery, and Utilizationcited by 1
  27. 2026From Reflection to Repair: A Scoping Review of Dataset Documentation Toolscited by 1
  28. 2023Automatic Geo-alignment of Artwork in Children's Story Bookscited by 0
  29. 2024Responsible AI in Open Ecosystems: Reconciling Innovation with Risk Assessment and Disclosurecited by 0
  30. 2025Opening the Scope of Openness in AIcited by 0
  31. 2025The Hitchhikers Guide to Production-ready Trustworthy Foundation Model powered Software (FMware)cited by 0
  32. 2025New Tools are Needed for Tracking Adherence to AI Model Behavioral Use Clausescited by 0
  33. 2026AI Supply Chain Galaxy: 3D Visual Analytics for License Compliancecited by 0
  34. 2026Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Modelscited by 0