4 ms·

I don't see how this is a double standard. Comparing a person interacting with their culture is not comparable in any way. IMHO, it's kind of a wacky argument t

I don't see how this is a double standard. Comparing a person interacting with their culture is not comparable in any way. IMHO, it's kind of a wacky argument to make.

crazygringo 2y ago
Can you elaborate on how it's not comparable? It seems obvious to me that it is -- they both learn and then create -- so what's the difference? If I can hire an employee who draws on knowledge they learned from copyrighted textbooks, why can't I hire an AI which draws on knowledge it learned from copyrighted textbooks? What makes that argument "wacky" in your eyes?
- homarp 2y ago
  most probably your employee actually 'paid' for their textbook.
- tekno45 2y ago
  you're asking why you have to treat people differently than you treat tools and machines.
  - crazygringo 2y ago
    Well obviously not in general. But when it comes to copyright law specifically, yes absolutely. That is the question I'm asking.
    - salawat 2y ago
      You're not going to get an answer you find agreeable, because you're hoping for an answer that allows you to continue to treat the tool as chattel, without conferring to it the excess baggage of being an individuated entity/laborer. You're either going to get: it's a technological, infinitely scalable process, and the training data should be considered what it is, which is intellectual property that should be being licensed before being used. ...or... It actually is the same as human learning, and it's time we started loading these things up with other baggage to be attached to persons if we're going to accept it's possible for a machine to learn like a human. There isn't a reasonable middle ground due to the magnitude of social disruption a chattel quasi-human technological human replacement would cause.
      - philwelch 2y ago
        No, you’re missing the point of copyright. The point of copyright is to protect an exclusive right to copy, not the right to produce original works influenced by previous works. If an LLM produces original works that are influenced by the training data, that is not a violation of copyright. If it reproduces the training data verbatim, it is.
        dijksterhuis 2y ago
        i weirdly agree with you, but also want to point out that “influenced by the training data” is doing some very heavy lifting there. exactly how the new work is created is important when it comes to derivative works. does it use a copy of the original work to create it, or a vague idea/memory of the original work’s composition? when i make music it’s usually vague memories. i’d argue that LLMs have an encoded representation of the original work in their weights (along with all the other stuff). but that’s the legal grey area bit. is the “mush” of model weights an encoded representation of works, or vague memories?
        philwelch 2y ago
        I don’t really think it matters because you can just compare the output to the input and apply the same standard, treating the process between the two as a black box.
        dijksterhuis 2y ago
        did you just call me a black box? :/ not sure how i feel about being reduced down to that as a human being.
        philwelch 2y ago
        As far as I’m concerned you are a black box. Just as I’m a black box from your perspective. In principle I could come over and vivisect your brain if you’d like, but I doubt you’d be interested, and I wouldn’t really want to incur the legal liability even if you were. Besides, “black box” just means that your internal mental life and cognitive mechanism is opaque to me. It’s not like I’m calling you a p-zombie.
    - cmiles74 2y ago
      It has never been argued that copyright law should apply to information the people learn, whether that be from reading books or newspapers, watching television or appreciating art like paintings or photographs. Unlike a person, an large language model is product built by a company and sold by a company. While I am not a lawyer, I believe much of the copyright arguments around LLM training revolve around the idea that copyrighted content should be licensed by the company training the LLM. In much the same way that people are not allowed to scrape the content of the New York Time website and then pass it off as their own content, so should OpenAI be barred from scraping the New York Times website to train ChatGPT and then sell the service without providing some dollars back to the New York Times.
- _DeadFred_ 2y ago
  One is a collection of highly dithered data generated by machines paid for by a business in order to financially gain from the copyrighted works in order to replace any future need for copyrighted text books. The other is a person learning from a copyrighted textbook in the legally protected manner, and whom and use the textbook was written for.
- groby_b 2y ago
  Unless you are making an argument for personhood, one is a machine, the other is a human. Different standards apply, end of discussion.
- cmiles74 2y ago
  I don't think this question really makes any sense... In my opinion, it's kind of mish-mashing several things together. "Can you elaborate on how it's not comparable?" The process of individual people interacting with their culture is a vastly different process than that used to train large language models. In what ways to you think these processes have anything in common? "It seems obvious to me that it is -- they both learn and then create -- so what's the difference?" This doesn't seem obvious to me (obviously)! Maybe you can argue that an LLM "learns" during training, but that ceases once training is complete. For sure, there are work-arounds that meet certain goals (RAG, fine-tuning); maybe your already vague definition of "learning" could be stretched to include these? Still, comparing this to how people learn is pretty far-fetched. AFAICT, there's no literature supporting the view that there's any commonality here; if you have some I would be very interested to read it. :-) Do they both create? I suspect not; an LLM is parroting back data from it's training set. We've seen many studies showing that tested LLMs perform poorly on novel problem sets. This article was posted just this week: https://news.ycombinator.com/item?id=42565606 https://news.ycombinator.com/item?id=42565606 The court is still out on the copyright issue, for the perspective of US law we'll have to wait on this one. Still, it's clear that an LLM can't "create" in any meaningful way. And so on and so forth. How is hiring an employee at all similar to subscribing to an OpenAI ChatGPT plan? Wacky indeed!
  - crazygringo 2y ago
    Obviously, on the inside, the process that a person goes through in learning and creating, and the process that a LLM goes through in learning and creating, is very different. Nobody will dispute that. But if they're learning from the same kinds of materials, and producing the same kind of output, then obviously the comparison can be made. And your idea that LLM's don't create seems obviously false. So I have to conclude the two seem comparable, and someone would have to show why different legal principles around copyright ought to apply, when it's a simple question of input/output. Why should it matter if it's a human or algorithm doing the processing, from a copyright perspective? Nothing "wacky" about the question at all.
rob_c 2y ago
That's a little simplistic. You're almost trying to say blank and white sands gray can't be compared which is a bit weird. Strangely like the situation itself. The question is just looked to how can we guarantee a model is influenced rather than memorising an input? And then is a human who is influenced simply relying on a faulty or less than perfect memory?

I don't see how this is a double standard. Comparing a person interacting with their culture is not comparable in any way. IMHO, it's kind of a wacky argument to make.

crazygringo 2y ago

Can you elaborate on how it's not comparable? It seems obvious to me that it is -- they both learn and then create -- so what's the difference? If I can hire an employee who draws on knowledge they learned from copyrighted textbooks, why can't I hire an AI which draws on knowledge it learned from copyrighted textbooks? What makes that argument "wacky" in your eyes?

homarp 2y ago
most probably your employee actually 'paid' for their textbook.
tekno45 2y ago
you're asking why you have to treat people differently than you treat tools and machines.
- crazygringo 2y ago
  Well obviously not in general. But when it comes to copyright law specifically, yes absolutely. That is the question I'm asking.
  - salawat 2y ago
    You're not going to get an answer you find agreeable, because you're hoping for an answer that allows you to continue to treat the tool as chattel, without conferring to it the excess baggage of being an individuated entity/laborer. You're either going to get: it's a technological, infinitely scalable process, and the training data should be considered what it is, which is intellectual property that should be being licensed before being used. ...or... It actually is the same as human learning, and it's time we started loading these things up with other baggage to be attached to persons if we're going to accept it's possible for a machine to learn like a human. There isn't a reasonable middle ground due to the magnitude of social disruption a chattel quasi-human technological human replacement would cause.
    - philwelch 2y ago
      No, you’re missing the point of copyright. The point of copyright is to protect an exclusive right to copy, not the right to produce original works influenced by previous works. If an LLM produces original works that are influenced by the training data, that is not a violation of copyright. If it reproduces the training data verbatim, it is.
      - dijksterhuis 2y ago
        i weirdly agree with you, but also want to point out that “influenced by the training data” is doing some very heavy lifting there. exactly how the new work is created is important when it comes to derivative works. does it use a copy of the original work to create it, or a vague idea/memory of the original work’s composition? when i make music it’s usually vague memories. i’d argue that LLMs have an encoded representation of the original work in their weights (along with all the other stuff). but that’s the legal grey area bit. is the “mush” of model weights an encoded representation of works, or vague memories?
        philwelch 2y ago
        I don’t really think it matters because you can just compare the output to the input and apply the same standard, treating the process between the two as a black box.
        dijksterhuis 2y ago
        did you just call me a black box? :/ not sure how i feel about being reduced down to that as a human being.
        philwelch 2y ago
        As far as I’m concerned you are a black box. Just as I’m a black box from your perspective. In principle I could come over and vivisect your brain if you’d like, but I doubt you’d be interested, and I wouldn’t really want to incur the legal liability even if you were. Besides, “black box” just means that your internal mental life and cognitive mechanism is opaque to me. It’s not like I’m calling you a p-zombie.
  - cmiles74 2y ago
    It has never been argued that copyright law should apply to information the people learn, whether that be from reading books or newspapers, watching television or appreciating art like paintings or photographs. Unlike a person, an large language model is product built by a company and sold by a company. While I am not a lawyer, I believe much of the copyright arguments around LLM training revolve around the idea that copyrighted content should be licensed by the company training the LLM. In much the same way that people are not allowed to scrape the content of the New York Time website and then pass it off as their own content, so should OpenAI be barred from scraping the New York Times website to train ChatGPT and then sell the service without providing some dollars back to the New York Times.
_DeadFred_ 2y ago
One is a collection of highly dithered data generated by machines paid for by a business in order to financially gain from the copyrighted works in order to replace any future need for copyrighted text books. The other is a person learning from a copyrighted textbook in the legally protected manner, and whom and use the textbook was written for.
groby_b 2y ago
Unless you are making an argument for personhood, one is a machine, the other is a human. Different standards apply, end of discussion.
cmiles74 2y ago
I don't think this question really makes any sense... In my opinion, it's kind of mish-mashing several things together. "Can you elaborate on how it's not comparable?" The process of individual people interacting with their culture is a vastly different process than that used to train large language models. In what ways to you think these processes have anything in common? "It seems obvious to me that it is -- they both learn and then create -- so what's the difference?" This doesn't seem obvious to me (obviously)! Maybe you can argue that an LLM "learns" during training, but that ceases once training is complete. For sure, there are work-arounds that meet certain goals (RAG, fine-tuning); maybe your already vague definition of "learning" could be stretched to include these? Still, comparing this to how people learn is pretty far-fetched. AFAICT, there's no literature supporting the view that there's any commonality here; if you have some I would be very interested to read it. :-) Do they both create? I suspect not; an LLM is parroting back data from it's training set. We've seen many studies showing that tested LLMs perform poorly on novel problem sets. This article was posted just this week: https://news.ycombinator.com/item?id=42565606 https://news.ycombinator.com/item?id=42565606 The court is still out on the copyright issue, for the perspective of US law we'll have to wait on this one. Still, it's clear that an LLM can't "create" in any meaningful way. And so on and so forth. How is hiring an employee at all similar to subscribing to an OpenAI ChatGPT plan? Wacky indeed!
- crazygringo 2y ago
  Obviously, on the inside, the process that a person goes through in learning and creating, and the process that a LLM goes through in learning and creating, is very different. Nobody will dispute that. But if they're learning from the same kinds of materials, and producing the same kind of output, then obviously the comparison can be made. And your idea that LLM's don't create seems obviously false. So I have to conclude the two seem comparable, and someone would have to show why different legal principles around copyright ought to apply, when it's a simple question of input/output. Why should it matter if it's a human or algorithm doing the processing, from a copyright perspective? Nothing "wacky" about the question at all.

rob_c 2y ago

That's a little simplistic. You're almost trying to say blank and white sands gray can't be compared which is a bit weird. Strangely like the situation itself. The question is just looked to how can we guarantee a model is influenced rather than memorising an input? And then is a human who is influenced simply relying on a faulty or less than perfect memory?