mlsanityData to 7 Oct 2026

Acceptable Use Policies for Foundation Models

arXiv 2409.09041 ↗First posted 29 Aug 2024cs.CY cs.AI cs.CLcited by 12

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Abstract (arXiv)

As foundation models have accumulated hundreds of millions of users, developers have begun to take steps to prevent harmful types of uses. One salient intervention that foundation model developers adopt is acceptable use policies: legally binding policies that prohibit users from using a model for specific purposes. This paper identifies acceptable use policies from 30 foundation model developers, analyzes the use restrictions they contain, and argues that acceptable use policies are an important lens for understanding the regulation of foundation models. Taken together, developers' acceptable use policies include 127 distinct use restrictions; the wide variety in the number and type of use restrictions may create fragmentation across the AI supply chain. Developers also employ acceptable use policies to prevent competitors or specific industries from making use of their models. Developers alone decide what constitutes acceptable use, and rarely provide transparency about how they enforce their policies. In practice, acceptable use policies are difficult to enforce, and scrupulous enforcement can act as a barrier to researcher access and limit beneficial uses of foundation models. Nevertheless, acceptable use policies for foundation models are an early example of self-regulation that have a significant impact on the market for foundation models and the overall AI ecosystem.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 65 of its 182 references that are in the map. First posted on arXiv 29 Aug 2024.

Builds on

65 of 182 references.

References · 65

  1. 2017Deep reinforcement learning from human preferencescited by 3,846
  2. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 2,993
  3. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
  4. 2023Universal and Transferable Adversarial Attacks on Aligned Language Modelscited by 2,914
  5. 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,565
  6. 2023Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversationscited by 1,124
  7. 2023Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!cited by 1,106
  8. 2018Model Cards for Model Reportingcited by 1,068
  9. 2020CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Modelscited by 703
  10. 2018Gender Bias in Coreference Resolution: Evaluation and Debiasing Methodscited by 657
  11. 2024WildChat: 1M ChatGPT Interaction Logs in the Wildcited by 598
  12. 2023DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Modelscited by 505
38 more
  1. 2023"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Modelscited by 457
  2. 2023SmoothLLM: Defending Large Language Models Against Jailbreaking Attackscited by 434
  3. 2024Mixture-of-Agents Enhances Large Language Model Capabilitiescited by 420
  4. 2023Shadow Alignment: The Ease of Subverting Safely-Aligned Language Modelscited by 284
  5. 2023Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulationcited by 202
  6. 2023Removing RLHF Protections in GPT-4 via Fine-Tuningcited by 165
  7. 2023Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigationscited by 157
  8. 2023Sociotechnical Safety Evaluation of Generative AI Systemscited by 154
  9. 2024Large Legal Fictions: Profiling Legal Hallucinations in Large Language Modelscited by 144
  10. 2022Power to the People? Opportunities and Challenges for Participatory AIcited by 137
  11. 2022Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reductioncited by 137
  12. 2024Collective Constitutional AI: Aligning a Language Model with Public Inputcited by 120
  13. 2023Evaluating and Mitigating Discrimination in Language Model Decisionscited by 117
  14. 2023Foundation Models and Fair Usecited by 112
  15. 2022Fusing finetuned models for better pretrainingcited by 110
  16. 2024The Art of Saying No: Contextual Noncompliance in Language Modelscited by 100
  17. 2023The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practicecited by 86
  18. 2024AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policiescited by 69
  19. 2024On the Societal Impact of Open Foundation Modelscited by 64
  20. 2023The Gradient of Generative AI Release: Methods and Considerationscited by 63
  21. 2023Black Box Adversarial Prompting for Foundation Modelscited by 62
  22. 2022Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learningcited by 47
  23. 2020Behavioral Use Licensing for Responsible AIcited by 46
  24. 2023The History and Risks of Reinforcement Learning and Human Feedbackcited by 42
  25. 2024AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policiescited by 34
  26. 2024Participation in the age of foundation modelscited by 32
  27. 2023Ecosystem Graphs: The Social Footprint of Foundation Modelscited by 31
  28. 2023Democratising AI: Multiple Meanings, Goals, and Methodscited by 29
  29. 2024Risks from Language Models for Automated Mental Healthcare: Ethics and Structure for Implementationcited by 27
  30. 2024Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Datacited by 20
  31. 2022Reward Reports for Reinforcement Learningcited by 18
  32. 2023The Ethical Implications of Generative Audio Models: A Systematic Literature Reviewcited by 18
  33. 2024The Social Impact of Generative AI: An Analysis on ChatGPTcited by 18
  34. 2024AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Researchcited by 13
  35. 2024STAR: SocioTechnical Approach to Red Teaming Language Modelscited by 13
  36. 2023Where's the Liability in Harmful AI Speech?cited by 12
  37. 2024Risks and Opportunities of Open-Source Generative AIcited by 11
  38. 2024What's documented in AI? Systematic Analysis of 32K AI Model Cardscited by 10

50 most cited of 65 All 65 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 6; 2026: 5.

12 papers.