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The whole point of fair use is that it allows people to copy things even when the copyright holder doesn't want them to. For example, if I am writing a critici

The whole point of fair use is that it allows people to copy things even when the copyright holder doesn't want them to. For example, if I am writing a criticism of an article, I can quote portions of that article in my criticism, or modify images from the article in order to add my own commentary. Fair use protects against authors who try to exert so much control over their works that it harms the public good.

Tainnor 5y ago
Fair Use is specific to the US, though. The picture could end up being much more complicated when code written outside the US is being analyzed.
- Hamuko 5y ago
  The messier issue is probably using the model to write code outside the US. Americans can probably analyze code from anywhere in the world and refer to Fair Use if a lawyer comes knocking, but I can't refer to Fair Use if a lawyer knocks on my door after using Copilot.
- krzyk 5y ago
  It is not US specific, we have it in EU. And e.g. in Poland I could reverse engineer a program to make it work on my hardware/software if it doesn't. This is covered by fair use here.
IncRnd 5y ago
This isn't the same situation at all. The copying of code doesn't seem to be for a limited or transformative purpose. Fair use might cover parody or commentary & criticism but not limitless replication.
- zarzavat 5y ago
  They are not replicating the code at all. They are training a neural network. The neural network then learns from the code and synthesises new code. It's no different from a human programmer reading code, learning from it, and using that experience to write new code. Somewhere in your head there is code that someone else wrote. And it's not infringing anybody's copyright for those memories to exist in your head.
  - jaimeyap 5y ago
    We can't yet equivocate ML systems with human beings. Maybe one day. But at the moment, it's probably better to compare this to a compiler being fed licensed code. The compilation output is still subject to the license. Regardless of how fancy the compiler is. Also, a human being that reproduces licensed code from memory - because they read that code - would constitute a license violation. The line between derivative work, and authentic new original creation is not a well defined one. This is why we still have human arbiters of these decisions and not formal differential definitions of it. This happens in music for example all the time.
  - blibble 5y ago
    surely that depends on the size of the training set? I could feed the Linux kernel one function at a time into a ML model, then coerce its output to be exactly the same as the input this is obviously copyright infringement whereas in the github case where they've trained it on millions of projects maybe it isn't? does the training set size become relevant legally?
  - IncRnd 5y ago
    It is replication, maybe not of a single piece of code - but creating a synthesis is still copying. For example, constructing a single piece of code of three pieces of code from your co-workers is still replication of code. Your argument would have some merit if something were created instead of assembled, but there is no new algorithm that is being created. That is not what is happening here. On the one hand, you call this copying in fair use. On the other hand, you say this is creating new code. You can't have it both ways.
    - caconym_ 5y ago
      > Your argument would have some merit if something were created instead of assembled, but there is no new algorithm that is being created. That is not what is happening here. If you're going to set such a high standard for ML tools like this, I think you need to justify why it shouldn't apply to humans too. When a human programmer who has read copyrighted code at some point in their life writes new code that is not a "new algorithm", are they in violation of the copyrights of every piece of code they've ever read that was remotely similar in any respect to the new work? I mean, I hope not! > On the one hand, you call this copying in fair use. On the other hand, you say this is creating new code. You can't have it both ways. I'm not a lawyer, but this actually sounds very close to the "transformative" criterion under fair use. Elements of existing code in the training set are being synthesized into new code for a new application. I assume there's no off-the-shelf precedent for this, but given the similarity with how human programmers learn and apply knowledge, it doesn't seem crazy to think this might be ruled as legitimate fair use. I'd guess it would come down to how willing the ML system is to suggest snippets that are both verbatim and highly non-generic.

Tainnor 5y ago

Fair Use is specific to the US, though. The picture could end up being much more complicated when code written outside the US is being analyzed.

Hamuko 5y ago
The messier issue is probably using the model to write code outside the US. Americans can probably analyze code from anywhere in the world and refer to Fair Use if a lawyer comes knocking, but I can't refer to Fair Use if a lawyer knocks on my door after using Copilot.
krzyk 5y ago
It is not US specific, we have it in EU. And e.g. in Poland I could reverse engineer a program to make it work on my hardware/software if it doesn't. This is covered by fair use here.

IncRnd 5y ago

This isn't the same situation at all. The copying of code doesn't seem to be for a limited or transformative purpose. Fair use might cover parody or commentary & criticism but not limitless replication.

zarzavat 5y ago
They are not replicating the code at all. They are training a neural network. The neural network then learns from the code and synthesises new code. It's no different from a human programmer reading code, learning from it, and using that experience to write new code. Somewhere in your head there is code that someone else wrote. And it's not infringing anybody's copyright for those memories to exist in your head.
- jaimeyap 5y ago
  We can't yet equivocate ML systems with human beings. Maybe one day. But at the moment, it's probably better to compare this to a compiler being fed licensed code. The compilation output is still subject to the license. Regardless of how fancy the compiler is. Also, a human being that reproduces licensed code from memory - because they read that code - would constitute a license violation. The line between derivative work, and authentic new original creation is not a well defined one. This is why we still have human arbiters of these decisions and not formal differential definitions of it. This happens in music for example all the time.
- blibble 5y ago
  surely that depends on the size of the training set? I could feed the Linux kernel one function at a time into a ML model, then coerce its output to be exactly the same as the input this is obviously copyright infringement whereas in the github case where they've trained it on millions of projects maybe it isn't? does the training set size become relevant legally?
- IncRnd 5y ago
  It is replication, maybe not of a single piece of code - but creating a synthesis is still copying. For example, constructing a single piece of code of three pieces of code from your co-workers is still replication of code. Your argument would have some merit if something were created instead of assembled, but there is no new algorithm that is being created. That is not what is happening here. On the one hand, you call this copying in fair use. On the other hand, you say this is creating new code. You can't have it both ways.
  - caconym_ 5y ago
    > Your argument would have some merit if something were created instead of assembled, but there is no new algorithm that is being created. That is not what is happening here. If you're going to set such a high standard for ML tools like this, I think you need to justify why it shouldn't apply to humans too. When a human programmer who has read copyrighted code at some point in their life writes new code that is not a "new algorithm", are they in violation of the copyrights of every piece of code they've ever read that was remotely similar in any respect to the new work? I mean, I hope not! > On the one hand, you call this copying in fair use. On the other hand, you say this is creating new code. You can't have it both ways. I'm not a lawyer, but this actually sounds very close to the "transformative" criterion under fair use. Elements of existing code in the training set are being synthesized into new code for a new application. I assume there's no off-the-shelf precedent for this, but given the similarity with how human programmers learn and apply knowledge, it doesn't seem crazy to think this might be ruled as legitimate fair use. I'd guess it would come down to how willing the ML system is to suggest snippets that are both verbatim and highly non-generic.