When does generative AI qualify for fair use?
essay by Suchir Balaji
Facts
11 properties- Instance of
- essay
- Author
- Suchir Balaji[2]
- Publication date
- October 23, 2024[4]
- Copyright status
- copyrighted[10]
- First line
- While generative models rarely produce outputs that are substantially similar to any of their training inputs, the process of training a generative model involves making copies of copyrighted data.[8]
- Imported from
- wholeness_audit_2026-05-02
- Last line
- That being said, none of the arguments here are fundamentally specific to ChatGPT either, and similar arguments could be made for many generative AI products in a wide variety of domains.[9]
- Main subject
- generative artificial intelligence, fair use[5][6]
- Quotation or excerpt
- The basic intuition behind this bound is that low-entropy model outputs are more likely to be including information from the model’s training data. In the extreme case, this is the problem of regurgitation, where a model deterministically outputs parts of its training data. But even nondeterministic samples can still use information from the training data to some degree -- the information may just be mixed in throughout the sample instead of directly copied.Note that there’s no fundamental reason why the entropy of a model’s outputs needs to be lower than the true entropy, but in practice model developers tend to choose training and deployment procedures that favor low-entropy outputs. The basic reason for this is that high-entropy outputs involve more randomness in their sampling process, which can cause them to be incoherent or contain hallucinations.[11]
- Title
- When does generative AI qualify for fair use?[7]
🏷️ Also known as
en When does generative AI qualify for fair use?
🔖 Identifiers · 1
- Work available at URL
- suchir.net
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Summary
When does generative AI qualify for fair use? is an essay[1].