zlacker

>>fnbr+(OP)
The best approach to circumventing the nondisclosure agreement is for the affected employees to get together, write out everything they want to say about OpenAI, train an LLM on that text, and then release it.

Based on these companies' arguments that copyrighted material is not actually reproduced by these models, and that any seemingly-infringing use is the responsibility of the user of the model rather than those who produced it, anyone could freely generate an infinite number of high-truthiness OpenAI anecdotes, freshly laundered by the inference engine, that couldn't be used against the original authors without OpenAI invalidating their own legal stance with respect to their own models.

>>mwigda+OQ
Clever, but no.

The argument about LLMs not being copyright laundromats making sense hinges the scale and non-specificity of training. There's a difference between "LLM reproduced this piece of copyrighted work because it memorized it from being fed literally half the internet", vs. "LLM was intentionally trained to specifically reproduce variants of this particular work". Whatever one's stances on the former case, the latter case would be plain infringing copyrights and admitting to it.

In other words: GPT-4 gets to get away with occasionally spitting out something real verbatim. Llama2-7b-finetune-NYTArticles does not.

>>TeMPOr+0T
Seems absurd that somehow the scale being massive makes it better somehow

You would think having a massive scale just means it has infringed even more copyrights, and therefore should be in even more hot water

>>bluefi+kT
So, the law has this concept of 'de minimus' infringement, where if you take a very small amount - like, way smaller than even a fair use - the courts don't care. If you're taking a handful of word probabilities from every book ever written, then the portion taken from each work is very, very low, so courts aren't likely to care.

If you're only training on a handful of works then you're taking more from them, meaning it's not de minimus.

For the record, I got this legal theory from Cory Doctorow[0], but I'm skeptical. It's very plausible, but at the same time, we also thought sampling in music was de minimus until the Second Circuit said otherwise. Copyright law is extremely malleable in the presence of moneyed interests, sometimes without Congressional intervention even!

[0] who is NOT pro-AI, he just thinks labor law is a better bulwark against it than copyright

>>kmeist+SX
You don't even need to go this far.

The word-probabilities are transformative use, a form of fair use and aren't an issue.

The specific output at each point in time is what would be judged to be fair use or copyright infringing.

I'd argue the user would be responsible for ensuring they're not infringing by using the output in a copyright infringing manner i.e. for profit, as they've fed certain inputs into the model which led to the output. In the same way you can't sue Microsoft for someone typing up copyrighted works into Microsoft Word and then distributing for profit.

De minimus is still helpful here, not all infringments are noteworthy.

>>KoolKa+TY
MS Word does not actively collect and process all texts for all available sources and does not offer them in recombined form. MS Word is passive whereas the whole point of an LLM is to produce output using a model trained on ingested data. It is actively processing vast amounts of texts with intent to make them available for others to use and the T&C state that the user owns the copyright to the outputs based on works of other copyright owners. LLMs give the user a CCL (Collateralised Copyright Liability, a bit like a CDO) without a way of tracing the sources used to train the model.