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>Training machine learning models on publicly available data is considered fair use across the machine learning community,” the Copilot page says. I love the s

>Training machine learning models on publicly available data is considered fair use across the machine learning community,” the Copilot page says. I love the sheer fucking hubris of this statement. It's fair use because "the machine learning community" wants it to be. What a terrible justification. I hope they get their ass kicked in court over this. Anyways, the problem here isn't that they're training on open-source code, it's that their LLM is outputting code that violates open-source licenses by not including the text of the license and the author's original copyright statement. That's not fair use and it never has been. Keep in mind that this is a subsidiary of Microsoft doing this. I'm sure M$ won't mind my new "Machine Learning platform" that outputs a copy of Windows with a piracy crack. After all, it's widely accepted as fair use by "the machine learning community".

nomel 3y ago
> I hope they get their ass kicked in court over this. I as a human can go read the code, learn, get inspiration, write it in my own style, and be fine. What's the big difference you see between my learning and the automated process for the AI? Is it just that cross between wet and dry storage and "understanding" that causes the problem?
- snickerbockers 3y ago
  You as a human will also get your ass kicked in court if you are caught copying code from an open-source project without complying with the terms of the license. >What's the big difference you see between my learning and the automated process for the AI? The root of the problem is that machine learning community wants AI to be treated as a human when that's convenient for them and as a machine when it's not.
  - nomel 3y ago
    I'm not suggesting the human or AI copies code. I'm talking about learning from the code that we read. There's a minimum sane syntax for every solution. At some point, you'll get what appears to be duplicates, but it's really just the fundamental logic of the problem being written down. Reading/writing more code, learning how to code, means you get better and identifying and writing that minimal logic. I guess my question is, where does learning end and copying begin? And, does this apply the same for humans and AI?
    - snickerbockers 3y ago
      In the situations I've seen, it's actually copying the code line-for-line, not merely making something similar. TFA has it copying code from some guy's github page. >And, does this apply the same for humans and AI? It shouldn't. For one thing, the process referred to as "training" would be more accurately described as "tuning parameters" and has no proven similarities to human cognition. For another thing, we operate in what could be termed a "human-supremacist" legal system in which computer programs have no rights, so there absolutely could be laws and court rulings that are discriminatory against computer programs.
      - prng2021 3y ago
        “ In the situations I've seen, it's actually copying the code line-for-line, not merely making something similar.” Those are mistakes and they will become more rare as the AI improves. If the system was designed to store chunks of code and output a copy of existing ones, the vast majority of output we see would be exact copies.
        snickerbockers 3y ago
        If it's a mistake then copilot (and by extension both Microsoft and everybody who uses copilot) needs to be held accountable when it makes a "mistake". It's not alright to steal code from open-source projects like this. This is what I was saying earlier about AI companies talking out of both sides of their mouth; when it's convenient for them they want AI to be treated as a human but whenever something goes wrong they talk about how it's not their fault, the system will get better at this, some problems are inevitable, etc. You don't get to have it both ways.
        anonymousab 3y ago
        > Those are mistakes They are not just mistakes, they are mistakes at scale. Mistakes en masse. Thus, they are mistakes that should carry a heavy weight and a heavy culpability for the wreckless carelessness that brought them about. If I made a mistake and my software enabled mass media piracy, lawyers can, would and should come after me regardless of me or my software's pledge to learn and make those mistakes "more rare". Especially if I keep committing those mistakes and cover up for them by adding individual specific blacklists rather than making expensive systemic fixes.
- jakelazaroff 3y ago
  The big difference is that you are a human with a full life and an unimaginable amount of experiences that have been accruing for decades. You have learned in school; played outside; read books and blog posts; listened to music; written code; had deep conversations with interesting people; fallen in love; gotten hurt. You have seen and smelled and touched and thought an almost infinite variety of things, you have experienced ecstasy and tragedy and everything in between, and all that comes together to make you an incredibly unique and special person. This colors your every experience, every idea, every sensation. GitHub Copilot is a machine and the sum total of everything it knows is code from GitHub. Literally its entire universe! There is absolutely no "experience" it has ever had that is not code from GitHub. There is no other fount of knowledge or inspiration from which it can draw. It is incapable of doing anything other than rearranging the Lego blocks in its brain — in fact, it doesn't even have a notion of what it's doing! Neural networks are a very complex math functions that take in some numbers, multiply them and spit out some other numbers. That's it.
  - horsawlarway 3y ago
    I think this is a pretty reductive way to look at what's happening. My personal take - it's more like the infinite monkey theorem. --- a monkey hitting keys at random on a typewriter keyboard for an infinite amount of time will almost surely type any given text, such as the complete works of William Shakespeare. In fact, the monkey would almost surely type every possible finite text an infinite number of times. --- except for each letter, we're jostling the monkey's hand a little based on the letters he's already hit, and the training data. Ex: There is a total problem space of "Valid Python" or "Valid JSON" and these machines are designed to explore parts of that problem space directed by the user and their training data. And just like it only takes 52 cards to make any given shuffle essentially an entirely new & never before seen section of the problem space "decks of cards" (see: https://www.mcgill.ca/oss/article/did-you-know-infographics/there-are-more-ways-arrange-deck-cards-there-are-atoms-earth#:~:text=No%20one%20has%2C%20and%20will,Just%20think%20about%20that https://www.mcgill.ca/oss/article/did-you-know-infographics/......) I don't really know of a clear way to distinguish what it's doing from "human inspiration & creativity" because those activities also tend to recombine previous experiences and data to create new but related works. Basically - we also tend to explore related problem spaces based on what is currently happening around us and our life experiences (This is why the arts have period specific themes and styles). This thing just does it a whole lot faster than we do. Whether that's good or bad is a different question.
- _8j50 3y ago
  Because it isn't understanding, it is derivative work
  - nomel 3y ago
    From my experience, GPT4 is able to decompose and rearrange the concepts of the problem statement, so they fit within the solution of the code, taking odd details into account. You can go as far as defining new words and have it use them, frame problems with odd contexts (like a program for boiling newts), and it, usually, comes up with reasonable solutions. Being able to stuff "new" things into an existing abstract framing is my definition of "understanding". This is also how most exams I've taken were constructed, to prove my comprehension of a subject. What is your litmus test for "understanding" and "comprehension"? I don't disagree that it's a derivative work. But, I think the majority of a humans day to day work is derivative.
    - _8j50 3y ago
      It's simple, GPT4 is using only the content on the internet to generate the output. Whether it used magic, understanding or fairy tales help it come up with the output is the irrelevant middle part. I can look at a bunch of faces, consider my interactions with other faces IRL that aren't copyrighted or restricted and my output can be original because while I am informed of all the faces I have seen, the mona lisa I draw is an expression of thoughts and views not a mere modification based on my understanding of the concept of faces. In other words, LLMs use a prompt to do stuff, they don't just say and do things because they want to express themsleves, therefore their output is not their expression or the expression of their owners but a processing of their input based on the prompt. To simplify this even more, if a script parses the Linux Kernel's code and outputs some video game because the programmer told it to, and it's only input is the Linux kernel then is that video game subject to GPL? If a human reads that same code and writes a video game, even if that human only knows the kernel's code we can say that since humans think and apply their own ideas, the kenrel code was merely informative. Now, if GPT4 is able to use it's training data (internet) to output arbitrary content without being prompted and the results of a prompt are based on it's normal thought process that wis independent of a human prompt then you can argue it is like an assistant helping the prompter human, but right now it is a tool that "understands" (i disagree but that's a different debate) publicly available internet content and processes prompts based on that "understanding" without applying it's own ideas, feelings or thoughts. It can be argued that its output is a mere processing of largley copyrighted content, similar to re-encoding a copyrighted movie. I would think what makes or breaks this in a US court is the question of "can a reasonable person who knows how chargpt works look at a prompt, output and conclude part of the output at least was a mere processing of, as opposed to original content that was inspired by the copy righted content?"
- gumballindie 3y ago
  This feels a bit like back in the day when we had to push back against folks claiming 5g is causing covid and other looney toon fantasies. AI is not a human. It doesnt learn or get inspiration. It’s software that ingests data. There’s nothing human about it. Even if it were, humans cant just steal tiny bits of other people’s work, reassemble it and call it something new. It would be like stealing a thousand paintings, cropping tiny bits out of each and making a “new” painting. It would still be made of stolen bits even if there are millions of such bits that mixed anew resemble none of the originals.
  - mock-possum 3y ago
    In your painting example though, surely the end result would be far too obviously transformative to ever be in any danger of accusations of copyright infringement, copying, piracy, stealing, or any of that? I mean look at Madeon’s Pop Culture song - wouldn’t “stealing tiny bits of other people’s work; reassembling it and calling it something new” describe it pretty completely? Except that track is a masterwork in the mashup genre. The bits aren’t ‘stolen’ they’re just ‘used’ and the entire concept of the song revolves around them being immediately recognizable.
randombits0 3y ago
You don’t understand copyright. This use doesn’t need to consider “fair use” at all. Only creative expressions are copyrightable. Purely functional expressions are not protected. If the output of an AI is purely functional, there is no copyright concern as the AI did not use any copyrightable content in determining the output.
- snickerbockers 3y ago
  That's cute but code has been copyrightable for decades, especially when it's Microsoft's code. >as the AI did not use any copyrightable content in determining the output. uuhhhhhh...didn't it? I thought we were talking about AI systems that are outputting code from their training sets verbatim. I don't see how you could possibly argue that the code it copies from its training set wasn't used to copy that same exact code from its training set.
- weare138 3y ago
  But that doesn't address code licensing. GitHub is attempting to dance the around licensing issue by reframing the argument as a pure copyright issue. There's is no such thing as 'fair use' when it comes to licensed code unless it's implicitly granted by the license. For example you can't take GPLv3 licensed code, copypasta it into your proprietary app and call it 'fair use'. Github can't legally indemnify devs from using 3rd party licensed code.
  - randombits0 3y ago
    The license is entirely based on the rights of owning the copyright. You cannot (effectively) license that which cannot be copyrighted. I can certainly take GPLv3 code and plop it into my app if the code is not subject to copyright. Without the copyright, there is no license.

nomel 3y ago

> I hope they get their ass kicked in court over this. I as a human can go read the code, learn, get inspiration, write it in my own style, and be fine. What's the big difference you see between my learning and the automated process for the AI? Is it just that cross between wet and dry storage and "understanding" that causes the problem?

snickerbockers 3y ago
You as a human will also get your ass kicked in court if you are caught copying code from an open-source project without complying with the terms of the license. >What's the big difference you see between my learning and the automated process for the AI? The root of the problem is that machine learning community wants AI to be treated as a human when that's convenient for them and as a machine when it's not.
- nomel 3y ago
  I'm not suggesting the human or AI copies code. I'm talking about learning from the code that we read. There's a minimum sane syntax for every solution. At some point, you'll get what appears to be duplicates, but it's really just the fundamental logic of the problem being written down. Reading/writing more code, learning how to code, means you get better and identifying and writing that minimal logic. I guess my question is, where does learning end and copying begin? And, does this apply the same for humans and AI?
  - snickerbockers 3y ago
    In the situations I've seen, it's actually copying the code line-for-line, not merely making something similar. TFA has it copying code from some guy's github page. >And, does this apply the same for humans and AI? It shouldn't. For one thing, the process referred to as "training" would be more accurately described as "tuning parameters" and has no proven similarities to human cognition. For another thing, we operate in what could be termed a "human-supremacist" legal system in which computer programs have no rights, so there absolutely could be laws and court rulings that are discriminatory against computer programs.
    - prng2021 3y ago
      “ In the situations I've seen, it's actually copying the code line-for-line, not merely making something similar.” Those are mistakes and they will become more rare as the AI improves. If the system was designed to store chunks of code and output a copy of existing ones, the vast majority of output we see would be exact copies.
      - snickerbockers 3y ago
        If it's a mistake then copilot (and by extension both Microsoft and everybody who uses copilot) needs to be held accountable when it makes a "mistake". It's not alright to steal code from open-source projects like this. This is what I was saying earlier about AI companies talking out of both sides of their mouth; when it's convenient for them they want AI to be treated as a human but whenever something goes wrong they talk about how it's not their fault, the system will get better at this, some problems are inevitable, etc. You don't get to have it both ways.
      - anonymousab 3y ago
        > Those are mistakes They are not just mistakes, they are mistakes at scale. Mistakes en masse. Thus, they are mistakes that should carry a heavy weight and a heavy culpability for the wreckless carelessness that brought them about. If I made a mistake and my software enabled mass media piracy, lawyers can, would and should come after me regardless of me or my software's pledge to learn and make those mistakes "more rare". Especially if I keep committing those mistakes and cover up for them by adding individual specific blacklists rather than making expensive systemic fixes.
jakelazaroff 3y ago
The big difference is that you are a human with a full life and an unimaginable amount of experiences that have been accruing for decades. You have learned in school; played outside; read books and blog posts; listened to music; written code; had deep conversations with interesting people; fallen in love; gotten hurt. You have seen and smelled and touched and thought an almost infinite variety of things, you have experienced ecstasy and tragedy and everything in between, and all that comes together to make you an incredibly unique and special person. This colors your every experience, every idea, every sensation. GitHub Copilot is a machine and the sum total of everything it knows is code from GitHub. Literally its entire universe! There is absolutely no "experience" it has ever had that is not code from GitHub. There is no other fount of knowledge or inspiration from which it can draw. It is incapable of doing anything other than rearranging the Lego blocks in its brain — in fact, it doesn't even have a notion of what it's doing! Neural networks are a very complex math functions that take in some numbers, multiply them and spit out some other numbers. That's it.
- horsawlarway 3y ago
  I think this is a pretty reductive way to look at what's happening. My personal take - it's more like the infinite monkey theorem. --- a monkey hitting keys at random on a typewriter keyboard for an infinite amount of time will almost surely type any given text, such as the complete works of William Shakespeare. In fact, the monkey would almost surely type every possible finite text an infinite number of times. --- except for each letter, we're jostling the monkey's hand a little based on the letters he's already hit, and the training data. Ex: There is a total problem space of "Valid Python" or "Valid JSON" and these machines are designed to explore parts of that problem space directed by the user and their training data. And just like it only takes 52 cards to make any given shuffle essentially an entirely new & never before seen section of the problem space "decks of cards" (see: https://www.mcgill.ca/oss/article/did-you-know-infographics/there-are-more-ways-arrange-deck-cards-there-are-atoms-earth#:~:text=No%20one%20has%2C%20and%20will,Just%20think%20about%20that https://www.mcgill.ca/oss/article/did-you-know-infographics/......) I don't really know of a clear way to distinguish what it's doing from "human inspiration & creativity" because those activities also tend to recombine previous experiences and data to create new but related works. Basically - we also tend to explore related problem spaces based on what is currently happening around us and our life experiences (This is why the arts have period specific themes and styles). This thing just does it a whole lot faster than we do. Whether that's good or bad is a different question.
_8j50 3y ago
Because it isn't understanding, it is derivative work
- nomel 3y ago
  From my experience, GPT4 is able to decompose and rearrange the concepts of the problem statement, so they fit within the solution of the code, taking odd details into account. You can go as far as defining new words and have it use them, frame problems with odd contexts (like a program for boiling newts), and it, usually, comes up with reasonable solutions. Being able to stuff "new" things into an existing abstract framing is my definition of "understanding". This is also how most exams I've taken were constructed, to prove my comprehension of a subject. What is your litmus test for "understanding" and "comprehension"? I don't disagree that it's a derivative work. But, I think the majority of a humans day to day work is derivative.
  - _8j50 3y ago
    It's simple, GPT4 is using only the content on the internet to generate the output. Whether it used magic, understanding or fairy tales help it come up with the output is the irrelevant middle part. I can look at a bunch of faces, consider my interactions with other faces IRL that aren't copyrighted or restricted and my output can be original because while I am informed of all the faces I have seen, the mona lisa I draw is an expression of thoughts and views not a mere modification based on my understanding of the concept of faces. In other words, LLMs use a prompt to do stuff, they don't just say and do things because they want to express themsleves, therefore their output is not their expression or the expression of their owners but a processing of their input based on the prompt. To simplify this even more, if a script parses the Linux Kernel's code and outputs some video game because the programmer told it to, and it's only input is the Linux kernel then is that video game subject to GPL? If a human reads that same code and writes a video game, even if that human only knows the kernel's code we can say that since humans think and apply their own ideas, the kenrel code was merely informative. Now, if GPT4 is able to use it's training data (internet) to output arbitrary content without being prompted and the results of a prompt are based on it's normal thought process that wis independent of a human prompt then you can argue it is like an assistant helping the prompter human, but right now it is a tool that "understands" (i disagree but that's a different debate) publicly available internet content and processes prompts based on that "understanding" without applying it's own ideas, feelings or thoughts. It can be argued that its output is a mere processing of largley copyrighted content, similar to re-encoding a copyrighted movie. I would think what makes or breaks this in a US court is the question of "can a reasonable person who knows how chargpt works look at a prompt, output and conclude part of the output at least was a mere processing of, as opposed to original content that was inspired by the copy righted content?"
gumballindie 3y ago
This feels a bit like back in the day when we had to push back against folks claiming 5g is causing covid and other looney toon fantasies. AI is not a human. It doesnt learn or get inspiration. It’s software that ingests data. There’s nothing human about it. Even if it were, humans cant just steal tiny bits of other people’s work, reassemble it and call it something new. It would be like stealing a thousand paintings, cropping tiny bits out of each and making a “new” painting. It would still be made of stolen bits even if there are millions of such bits that mixed anew resemble none of the originals.
- mock-possum 3y ago
  In your painting example though, surely the end result would be far too obviously transformative to ever be in any danger of accusations of copyright infringement, copying, piracy, stealing, or any of that? I mean look at Madeon’s Pop Culture song - wouldn’t “stealing tiny bits of other people’s work; reassembling it and calling it something new” describe it pretty completely? Except that track is a masterwork in the mashup genre. The bits aren’t ‘stolen’ they’re just ‘used’ and the entire concept of the song revolves around them being immediately recognizable.

randombits0 3y ago

You don’t understand copyright. This use doesn’t need to consider “fair use” at all. Only creative expressions are copyrightable. Purely functional expressions are not protected. If the output of an AI is purely functional, there is no copyright concern as the AI did not use any copyrightable content in determining the output.

snickerbockers 3y ago
That's cute but code has been copyrightable for decades, especially when it's Microsoft's code. >as the AI did not use any copyrightable content in determining the output. uuhhhhhh...didn't it? I thought we were talking about AI systems that are outputting code from their training sets verbatim. I don't see how you could possibly argue that the code it copies from its training set wasn't used to copy that same exact code from its training set.
weare138 3y ago
But that doesn't address code licensing. GitHub is attempting to dance the around licensing issue by reframing the argument as a pure copyright issue. There's is no such thing as 'fair use' when it comes to licensed code unless it's implicitly granted by the license. For example you can't take GPLv3 licensed code, copypasta it into your proprietary app and call it 'fair use'. Github can't legally indemnify devs from using 3rd party licensed code.
- randombits0 3y ago
  The license is entirely based on the rights of owning the copyright. You cannot (effectively) license that which cannot be copyrighted. I can certainly take GPLv3 code and plop it into my app if the code is not subject to copyright. Without the copyright, there is no license.