7 ms·

Not sure copyright of a Audio version of a book include to use for other uses such as training models. If this is not mentioned in copyright, I would still assu

Not sure copyright of a Audio version of a book include to use for other uses such as training models. If this is not mentioned in copyright, I would still assume publisher can a make a strong case about it is used for not the intended purpose.

MatekCopatek 7y ago
I don't see a practical way to prove this though. The software is developed behind closed doors and unless someone explicitly leaks this information, it's just a caption feature working really well. Amazon could claim they trained it on a legit data set they had all the necessary rights for. Or am I missing something and they're openly admitting they used it?
- deleted 7y ago
  [deleted]
- dillonmckay 7y ago
  Just because it is difficult to prove does not make it less of a violation.
chii 7y ago
> Not sure copyright of a Audio version of a book include to use for other uses such as training models. it must. I am using the audio book to train my meat-brain implementation of a neural network. This is no different than training an electron-brain neural network. I have purchased the book and the information contained within must be usable in any form i desire, except for copying and redistributing the text.
- new299 7y ago
  Legally I believe this distinction is quite clear (IANAL) between these two cases. You can memorize a whole book, and it's not copyright infringement. If you, create a compressed zip of book you that infringes if you don't own the copyright. If a trained model really doesn't infringe, then that's it copyright is dead. Because it's not difficult to overfit a model such that it can replicate the original work. And if that model is no longer under the original copyright it can be shared without restriction.
  - chii 7y ago
    > If you, create a compressed zip of book you that infringes if you don't own the copyright. of course you don't - a compresssed zip, or any transformation of the text is a derivative work. But the neural network you use the text to train is not a derivative work unless you intentionally only used this single book to train it for the express purpose of reproducing the original text. In which case, that is no different than doing a format transformation, and that is protected under copyright. What i m saying is that any book that is used as a source of knowledge cannot claim derivative work on the resulting culmination of knowledge.
    - new299 7y ago
      Why do you believe it's not a derivative work? Let's say a neural network was trained on two books, and it ends up reproducing large fragments of text from those two books. Is that a derivative work? Or 3 Or 4... And reproducing how much of the original work exactly, under what conditions. Does the size of the model factor in to the analysis? It doesn't seem as clear cut as you suggest to me.
      - roywiggins 7y ago
        Yeah, if you trained an AI to write Harry Potter fanfic (and remove all the trademarks by hand, no Harry Potter(TM) etc), is the result a derivative work? It seems like it could be, even if it's generic child wizards at a generic wizarding school. Fanfic is generally a derivative work.
new299 7y ago
In at least some cases, it would be considered fair use. The wikipedia page on fair use has this to say, regarding Google's book scanning for example: As part of the ruling that found the book digitisation project was fair use, the judge stated "Google Books is also transformative in the sense that it has transformed book text into data for purposes of substantive research, including data mining and text mining in new areas" [1] To me it feels like a continuum. On one end of the scale, the model has been informed by copyrighted data. The model has learned something about the structure of the data, which generalizes to new examples easily. On the other end of the spectrum it's just an efficient encoding of the corpus dataset (in this case mappings of sounds to text). It's not learned anything... How do you distinguish these cases? Can the second type of "machine learning" be used to circumvent copyright in some cases, and is it? [1] https://en.wikipedia.org/wiki/Fair_use#Fair_use_in_particular_areas https://en.wikipedia.org/wiki/Fair_use#Fair_use_in_particula...
- __Joker 7y ago
  Indeed. One particular argument in Authors Guild, Inc. v. Google, Inc. is about search functionality, which may be little similar. If I understand correctly google books lets search the book. But not sure, if they improved or modeled their search engine on copyrighted books. On the same line, if I remember correctly google used classic and out of copyright material to teach its translation models. Which will resonate more to the current case.

MatekCopatek 7y ago

I don't see a practical way to prove this though. The software is developed behind closed doors and unless someone explicitly leaks this information, it's just a caption feature working really well. Amazon could claim they trained it on a legit data set they had all the necessary rights for. Or am I missing something and they're openly admitting they used it?

deleted 7y ago
[deleted]
dillonmckay 7y ago
Just because it is difficult to prove does not make it less of a violation.

chii 7y ago

> Not sure copyright of a Audio version of a book include to use for other uses such as training models. it must. I am using the audio book to train my meat-brain implementation of a neural network. This is no different than training an electron-brain neural network. I have purchased the book and the information contained within must be usable in any form i desire, except for copying and redistributing the text.

new299 7y ago
Legally I believe this distinction is quite clear (IANAL) between these two cases. You can memorize a whole book, and it's not copyright infringement. If you, create a compressed zip of book you that infringes if you don't own the copyright. If a trained model really doesn't infringe, then that's it copyright is dead. Because it's not difficult to overfit a model such that it can replicate the original work. And if that model is no longer under the original copyright it can be shared without restriction.
- chii 7y ago
  > If you, create a compressed zip of book you that infringes if you don't own the copyright. of course you don't - a compresssed zip, or any transformation of the text is a derivative work. But the neural network you use the text to train is not a derivative work unless you intentionally only used this single book to train it for the express purpose of reproducing the original text. In which case, that is no different than doing a format transformation, and that is protected under copyright. What i m saying is that any book that is used as a source of knowledge cannot claim derivative work on the resulting culmination of knowledge.
  - new299 7y ago
    Why do you believe it's not a derivative work? Let's say a neural network was trained on two books, and it ends up reproducing large fragments of text from those two books. Is that a derivative work? Or 3 Or 4... And reproducing how much of the original work exactly, under what conditions. Does the size of the model factor in to the analysis? It doesn't seem as clear cut as you suggest to me.
    - roywiggins 7y ago
      Yeah, if you trained an AI to write Harry Potter fanfic (and remove all the trademarks by hand, no Harry Potter(TM) etc), is the result a derivative work? It seems like it could be, even if it's generic child wizards at a generic wizarding school. Fanfic is generally a derivative work.

new299 7y ago

In at least some cases, it would be considered fair use. The wikipedia page on fair use has this to say, regarding Google's book scanning for example: As part of the ruling that found the book digitisation project was fair use, the judge stated "Google Books is also transformative in the sense that it has transformed book text into data for purposes of substantive research, including data mining and text mining in new areas" [1] To me it feels like a continuum. On one end of the scale, the model has been informed by copyrighted data. The model has learned something about the structure of the data, which generalizes to new examples easily. On the other end of the spectrum it's just an efficient encoding of the corpus dataset (in this case mappings of sounds to text). It's not learned anything... How do you distinguish these cases? Can the second type of "machine learning" be used to circumvent copyright in some cases, and is it? [1] https://en.wikipedia.org/wiki/Fair_use#Fair_use_in_particular_areas https://en.wikipedia.org/wiki/Fair_use#Fair_use_in_particula...

__Joker 7y ago
Indeed. One particular argument in Authors Guild, Inc. v. Google, Inc. is about search functionality, which may be little similar. If I understand correctly google books lets search the book. But not sure, if they improved or modeled their search engine on copyrighted books. On the same line, if I remember correctly google used classic and out of copyright material to teach its translation models. Which will resonate more to the current case.