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The key factor of Feist v Rural is whether there was any original or creative process in the way the facts were arranged. Here, there's a whole lot of creative

by mlyle 3y ago

The key factor of Feist v Rural is whether there was any original or creative process in the way the facts were arranged. Here, there's a whole lot of creative decisions in labelling and guiding of training that produces the weights, so it's reasonable to think it might be copyrightable. That is, the numbers are a whole lot more original than the issuance of phone numbers or part numbers.

mft_ 3y ago
IANAL, but I’d wonder whether ‘creativity’ is really present in labelling - and indeed, mightn’t it be the last thing you want? I’d argue labelling should be strictly factual and reproducible, and ideally following a logical structure… maybe akin to how addresses of buildings might appear in a phone directory… (Agree that the skill in knowing how to code and guide the training of a model is probably very different though. It’s not just access to compute time that separates me from OpenAI :) )
dragonwriter 3y ago
> Here, there's a whole lot of creative decisions in labelling and guiding of training that produces the weights Often, labelling is part of large public datasets that are chosen for use for that exact reason, and/or is otherwise not the work of the party claiming copyright in the model.
deleted 3y ago
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Retric 3y ago
The requirement for expertise doesn’t necessarily imply that that setting up perimeters for training AI is necessarily copyrightable. A normal brick wall for example needs skills to create but doesn’t qualify as the goal is not creative. If so the mechanical output of a process that doesn’t qualify for copyright is not going to qualify. Labeling training data may qualify for copyright, but if the underlying training data doesn’t taint the output as a derivative work then labeling isn’t going to qualify by itself. Thus without some new and very generous interpretation AI companies are at best not going to benefit from copyright and at worst may be forced to create all training data in house. My suspicion is this generation of AI companies are in a very difficult situation.
- mlyle 3y ago
  > but if the underlying training data doesn’t taint the output as a derivative work then labeling isn’t going to qualify by itself. It depends. If each individual training item has a small impact on the output coefficients, then perhaps it's not a derivative work of them. But if there's a large creative process in determining model training procedure, deciding labelling strategies, and applying those-- perhaps those numbers are strongly derived from those things.
  - Retric 3y ago
    That sounds like wishful thinking, individual training items have significant impact on the result. Anyway, suppose you’re building an AI to walk, there’s nothing creative about selecting 9.8m/s/s for gravity that’s simply the ideal value to achieve a desired goal. Labeling an elephant as “Elephant” rather than “coat hanger” is similarly a functional choice. Just because a person is holding a camera and taking a photo doesn’t mean the result is copyrightable.
    - mlyle 3y ago
      > Anyway, suppose you’re building an AI to walk, there’s nothing creative about selecting 9.8m/s/s for gravity that’s simply the ideal value to achieve a desired goal. Suppose you're not building a strawman, but instead building an AI to be an LLM. The exact sequence of what you choose to do for instruction tuning, and the metrics and labels that you choose, the prompt/response pairs you write, and the loss functions you employ are quite creative. They greatly affect the coefficients and are not simple mechanical steps and are the result of a large amount of creative choice. We are nowhere near a point where they are an uncreative, mechanical recipe to follow. > Just because a person is holding a camera and taking a photo doesn’t mean the result is copyrightable. No, but in the overwhelming majority of circumstances it is. What it depends upon is whether the person holding the camera is making a significant, original creative choice. I am not sure what courts will decide, but I am certain that there is more creativity and originality employed than you are giving OpenAI et al. credit for.

by mlyle 3y ago

mft_ 3y ago

IANAL, but I’d wonder whether ‘creativity’ is really present in labelling - and indeed, mightn’t it be the last thing you want? I’d argue labelling should be strictly factual and reproducible, and ideally following a logical structure… maybe akin to how addresses of buildings might appear in a phone directory… (Agree that the skill in knowing how to code and guide the training of a model is probably very different though. It’s not just access to compute time that separates me from OpenAI :) )

dragonwriter 3y ago

> Here, there's a whole lot of creative decisions in labelling and guiding of training that produces the weights Often, labelling is part of large public datasets that are chosen for use for that exact reason, and/or is otherwise not the work of the party claiming copyright in the model.

deleted 3y ago

[deleted]

Retric 3y ago

The requirement for expertise doesn’t necessarily imply that that setting up perimeters for training AI is necessarily copyrightable. A normal brick wall for example needs skills to create but doesn’t qualify as the goal is not creative. If so the mechanical output of a process that doesn’t qualify for copyright is not going to qualify. Labeling training data may qualify for copyright, but if the underlying training data doesn’t taint the output as a derivative work then labeling isn’t going to qualify by itself. Thus without some new and very generous interpretation AI companies are at best not going to benefit from copyright and at worst may be forced to create all training data in house. My suspicion is this generation of AI companies are in a very difficult situation.

mlyle 3y ago
> but if the underlying training data doesn’t taint the output as a derivative work then labeling isn’t going to qualify by itself. It depends. If each individual training item has a small impact on the output coefficients, then perhaps it's not a derivative work of them. But if there's a large creative process in determining model training procedure, deciding labelling strategies, and applying those-- perhaps those numbers are strongly derived from those things.
- Retric 3y ago
  That sounds like wishful thinking, individual training items have significant impact on the result. Anyway, suppose you’re building an AI to walk, there’s nothing creative about selecting 9.8m/s/s for gravity that’s simply the ideal value to achieve a desired goal. Labeling an elephant as “Elephant” rather than “coat hanger” is similarly a functional choice. Just because a person is holding a camera and taking a photo doesn’t mean the result is copyrightable.
  - mlyle 3y ago
    > Anyway, suppose you’re building an AI to walk, there’s nothing creative about selecting 9.8m/s/s for gravity that’s simply the ideal value to achieve a desired goal. Suppose you're not building a strawman, but instead building an AI to be an LLM. The exact sequence of what you choose to do for instruction tuning, and the metrics and labels that you choose, the prompt/response pairs you write, and the loss functions you employ are quite creative. They greatly affect the coefficients and are not simple mechanical steps and are the result of a large amount of creative choice. We are nowhere near a point where they are an uncreative, mechanical recipe to follow. > Just because a person is holding a camera and taking a photo doesn’t mean the result is copyrightable. No, but in the overwhelming majority of circumstances it is. What it depends upon is whether the person holding the camera is making a significant, original creative choice. I am not sure what courts will decide, but I am certain that there is more creativity and originality employed than you are giving OpenAI et al. credit for.