A group of authors filed a lawsuit against Meta, alleging the unlawful use of copyrighted material in developing its Llama 1 and Llama 2 large language models....
I appreciate your enthusiasm here, but the law (and precedent reading of the law) simply does not bear out a clear interpretation like you’re suggesting.
It bears relationship to the end product when the end product reproduces the original work.
This is not how copyright has been applied when speaking of other machine learning processes using logical regression that is considered fair use, as in Text and Data Mining classifications(TDM) (proposed class 7(a) and 7(b) (page 102) in Recommendation of the Register of Copyrights 2021). The model itself is simply a very large regression model, that has created metadata analysis from unstructured data sources. When determining weather an LLM fits into this fair use category, they will look at what the model is and how it is created, not to whether it can be prompted to recreate a similar work. To quote from Comments in Response of Notice of Inquiry on the matter:
Understanding the process of training foundation models is relevant to the generative AI systems’ fair use defenses because the scope of copyright protection does not extend to “statistical information” such as “word frequencies, syntactic patterns, and thematic markers.” Processing in-copyright works to extract “information about the original [work]” does not infringe because it does not “replicat[e] protected expression.
Granted, what is novel about this particular case (LLM’s generally) is their apparent ability to re-construct substantially similar works from the same overall process of TDM. Acknowledged, but to borrow again from the same comments as above:
Yet, in limited situations, Generative AI models do copy the training data.24 So unlike prior copy-reliant technologies that courts have held are fair use, it is impossible to say
categorically that inputs and outputs of Generative AI will always be fair use. We note in addition that some have argued that the ability of Generative AI to produce artifacts that could pass for human expression and the potential scale of such production may have implications not seen in previous non-expressive use cases. The difficulty with such arguments is that the harm asserted does not flow from the communication of protected expression to any human audience.
Basically, they are asserting that applying copyright to this use that falls outside of its explicit scope would not prevent the same harm caused by that same technology created without the use of the copyrighted works. Any work sufficiently described in publicly available text data could be reconstructed by a sufficiently weighted regression model and the correct prompting. E.g. - if I described a desired output sufficiently enough in my input to the model, the output could be substantially similar to a protected work, regardless of its lack of representation in the training data.
I happen to agree that these AI models represent a threat to the work and livelihoods of real artists, and that the benefit as currently captured by billion-dollar companies is a substantial problem that must be addressed, but I simply do not think the application of copyright in this manner is appropriate (as it will prevent legitimate uses of the technology), nor do i think it is sufficiently preventative in future consolidation of wealth by the use of these models.
Nevermind my personal objections to copyright law on the basis of my worldview - I just don’t think copyright is the correct tool to use for the desired protection.
This is not how copyright has been applied when speaking of other machine learning processes using logical regression that is considered fair use, as in Text and Data Mining classifications(TDM) (proposed class 7(a) and 7(b) (page 102) in Recommendation of the Register of Copyrights 2021).
Your link is merely proposed recommendations. That is not legislation nor case law. Also, the sections on TDM that you reference clearly state (my emphasis):
for the purpose of scholarly research and teaching.
I think this is even more abundantly clear that the research exemption does not apply. AI “research” is in no way “scholarly”, it is commercial product development and thus does not align with fair use copyright exemptions.
It’s also not talking about building AI, but circumventing DRM in order to preserve art. They’re saying that there should be an exemption to the illegal practice of circumventing DRM in certain, limited circumstances. However, they’re still only suggesting this! So not only does this not apply to your argument, it isn’t even actually in force.
To put your other link into context, this also is not law, but comments from legal professors.
Understanding the process of training foundation models is relevant to the generative AI systems’ fair use defenses because the scope of copyright protection does not extend to “statistical information” such as “word frequencies, syntactic patterns, and thematic markers.” Processing in-copyright works to extract “information about the original [work]” does not infringe because it does not “replicat[e] protected expression.
The flaw here is that the work isn’t processed in situ, it is copied into a training database, then processed. The processing may be fine, but the copying is illegal.
If they had a legitimate license to view the work for their purpose, and processed in situ, that might be different.
The difficulty with such arguments is that the harm asserted does not flow from the communication of protected expression to any human audience.
The argument here is that, while it sometimes infringes copyright, the harm it causes isn’t primarily from the infringing act. Not always, though that depends. If AI is used to pass off as someone else, then the AI manufacturer has built a tool that facilitates an illegal act, by copying the original work.
However, this, again, ignores the fact that the commercial enterprise has copied the data into their training database without duly compensating the rightsholder.
I appreciate your enthusiasm here, but the law (and precedent reading of the law) simply does not bear out a clear interpretation like you’re suggesting.
This is not how copyright has been applied when speaking of other machine learning processes using logical regression that is considered fair use, as in Text and Data Mining classifications(TDM) (proposed class 7(a) and 7(b) (page 102) in Recommendation of the Register of Copyrights 2021). The model itself is simply a very large regression model, that has created metadata analysis from unstructured data sources. When determining weather an LLM fits into this fair use category, they will look at what the model is and how it is created, not to whether it can be prompted to recreate a similar work. To quote from Comments in Response of Notice of Inquiry on the matter:
Granted, what is novel about this particular case (LLM’s generally) is their apparent ability to re-construct substantially similar works from the same overall process of TDM. Acknowledged, but to borrow again from the same comments as above:
Basically, they are asserting that applying copyright to this use that falls outside of its explicit scope would not prevent the same harm caused by that same technology created without the use of the copyrighted works. Any work sufficiently described in publicly available text data could be reconstructed by a sufficiently weighted regression model and the correct prompting. E.g. - if I described a desired output sufficiently enough in my input to the model, the output could be substantially similar to a protected work, regardless of its lack of representation in the training data.
I happen to agree that these AI models represent a threat to the work and livelihoods of real artists, and that the benefit as currently captured by billion-dollar companies is a substantial problem that must be addressed, but I simply do not think the application of copyright in this manner is appropriate (as it will prevent legitimate uses of the technology), nor do i think it is sufficiently preventative in future consolidation of wealth by the use of these models.
Nevermind my personal objections to copyright law on the basis of my worldview - I just don’t think copyright is the correct tool to use for the desired protection.
Your link is merely proposed recommendations. That is not legislation nor case law. Also, the sections on TDM that you reference clearly state (my emphasis):
I think this is even more abundantly clear that the research exemption does not apply. AI “research” is in no way “scholarly”, it is commercial product development and thus does not align with fair use copyright exemptions.
It’s also not talking about building AI, but circumventing DRM in order to preserve art. They’re saying that there should be an exemption to the illegal practice of circumventing DRM in certain, limited circumstances. However, they’re still only suggesting this! So not only does this not apply to your argument, it isn’t even actually in force.
To put your other link into context, this also is not law, but comments from legal professors.
The flaw here is that the work isn’t processed in situ, it is copied into a training database, then processed. The processing may be fine, but the copying is illegal.
If they had a legitimate license to view the work for their purpose, and processed in situ, that might be different.
The argument here is that, while it sometimes infringes copyright, the harm it causes isn’t primarily from the infringing act. Not always, though that depends. If AI is used to pass off as someone else, then the AI manufacturer has built a tool that facilitates an illegal act, by copying the original work.
However, this, again, ignores the fact that the commercial enterprise has copied the data into their training database without duly compensating the rightsholder.