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> ChatGPT would be required to disclose copyright material ...Such an obligation would give publishers and content creators a new weapon to seek a share of prof

> ChatGPT would be required to disclose copyright material ...Such an obligation would give publishers and content creators a new weapon to seek a share of profits If somebody figures out how to do fine-grained profit sharing based on having created something that the AI references... that would be very cool. I love discovering the solution to a niche and difficult-to-describe problem, but I hate the extra work necessary to leave breadcrumbs for DenverCoder9 to find it 20 years later. If I could leave the matchmaking to an AI and get paid $0.25 when it's finally helpful to that person I don't know... Well I'd probably wouldn't make much money, but it would give me warm fuzzy feelings.

nullc 4y ago
In talking to friends that attempted to monetize their youtube, they found that works that were extremely popular and impactful (yet not millions of views viral) earned practically nothing and they were demoralized and discouraged from bothering to produce more.
- ajmurmann 4y ago
  What's the metric for "popular and impactful" without "not millions of views"? Were these videos with few views, but great ratings?
  - nullc 4y ago
    Imagine it's 30 years ago. You and your friends have a band. You put on shows regionally, sometimes hundreds or even a thousand people attend. You have dozens of regular fans who go to all your events, they make and share covers of your music and fan art. That isn't millions of views. It's tens of thousands. On youtube that's nothing. But 30 years ago you'd feel it was a great accomplishment, and if it was all you achieved you could be happy with that. As is has become more possible for a few of the most broadly appealing and unchallenged works to reach millions of people the goalpost has moved. Plenty of valuable content will never reach millions of viewers-- the appeal is too niche. It's a worthwhile contribution to the world none the less, but it isn't compensated as such on youtube.
kmeisthax 4y ago
The problem is that AI doesn't really "reference" data. When you "train" an AI on some data, you're adjusting billions of model parameters to make them closer to the desired output. Except you're also doing that on billions of pieces of other data, many times over, and every bit of data you train on is stepping on everything else. In order to pay people a share of the 'profits' of AI, you need a clear value chain from licensed training data to each output, through the magical linear algebra data blender that is gradient descent. Nobody knows if your training example helped for the same reason why we don't know if an LLM is lying or not. In lieu of that, you could pay everyone a fixed cut based on presence in the training set, but that then gives you the Spotify problem of a fixed pot being shared millions of different ways. For example, Adobe recently announced they were building an AI drawing tool trained on exclusively licensed sources - specifically, Adobe Stock contributors[0]. They're used to being paid when someone buys their image, which means that they have incentives to produce broadly relevant stock photography. But with a fixed "AI pot" paying you, now you have an incentive to produce as much output as possible as cheaply as possible purely to get a larger part of the pot. This is bad both for the stock photo market[1] AND the AI being trained. AI is extremely sensitive to bias in the dataset. Normally, when we talk about bias, we think about things like "oh if I type CEO into Midjourney all the output drawings are male"; but it goes a lot deeper. Gradient descent does not know how to recognize duplicate training set features, those features get more chances to adjust the model. Eventually that training example or image is common enough to make memorization 'worth it' in terms of parameters used[2]. Ironically that sort of thing would actually make attribution and profit-sharing 'easier', at the expense of the model being far less capable. [0] Who, BTW, I don't think actually have the ability to opt-in to this? Like, as far as I'm aware this is being done through the medium of contractual roofies being dropped into stock photographers' drinks. [1] Expect more duplicates and spam [2] This is why early Craiyon would give you existing imagery when you asked for specific famous examples and why Stable Diffusion draws the Getty Images watermark on things that look like a stock photo of a newsworthy event.
- ec109685 4y ago
  AI could be used to decide if a source should be included or not (or the benefit to the model could be the qualifier). That would solve your problem of people just peddling spam. No this is an unsolvable problem. The future also seems like less about making the model an all knowing oracle but instead making it smart enough to know how to lookup data it needs, so it could end up where licensed data is all that is needed for training. Lastly, what if you use model A to generate data for model B? Would B be tainted? There have been lots of examples where LLM’s are used to train simpler models by synthesizing training data.
WhereIsTheTruth 4y ago
I don't think ownership makes sense in the future we are building, optimizing society to achieve greatness as a multiplanetary species involve reinventing money and its purpose What society would be today if you had to pay a fee whenever you wanted to use the Pythagoras theorem, we'd be stuck in dark times
- __MatrixMan__ 4y ago
  Oh you're absolutely right, the notion that you can own information is absurd. Maybe it was necessary at one time as a kind of training-wheels for innovation, but we've long since outgrown it. It'll only ever get more and more absurd. But if somebody you don't know is doing something that's benefiting you, and you're not contributing to their ability to continue doing that thing in some way, then you might be shooting yourself in the foot. In any future worth pursuing, they'd be free to stop contributing if they felt like it, but wouldn't it be a shame if they did so without even knowing that their contributions were considered incredibly valuable by somebody? Like, imagine if Pythagoras couldn't afford food and had to give up geometry club and get a "real job". That would be to everybody's detriment. So while I think that "property" is the wrong tool here--we shouldn't be witholding access to our contributions for any reason--I do think we need something that's a little more impactful than an upvote for saying "more like this please".
- manuelmoreale 4y ago
  I appreciate your optimism but in the future we’re building, money and ownership seems to be more and more important unfortunately.
  - JieJie 4y ago
    Which is why we should be very careful when we consider creating a system that is going to funnel money to people who are already famous for writing, art, etc. How will new artists and writers get their works included in future AI — and then get people to prompt for them — so they can get their paycheck? Even spending a few minutes on this problem would lead to a realization that even if we could create a system that could a) determine rights to any particular portion of an AI-generated work, and b) extract payment and remunerate the artist; would essentially be building a moat around the next generation's intellectual property powerhouses. Generative AI is a revolutionary technology, and we need a revolution in compensation models for arts and letters to go with it.

nullc 4y ago

In talking to friends that attempted to monetize their youtube, they found that works that were extremely popular and impactful (yet not millions of views viral) earned practically nothing and they were demoralized and discouraged from bothering to produce more.

ajmurmann 4y ago
What's the metric for "popular and impactful" without "not millions of views"? Were these videos with few views, but great ratings?
- nullc 4y ago
  Imagine it's 30 years ago. You and your friends have a band. You put on shows regionally, sometimes hundreds or even a thousand people attend. You have dozens of regular fans who go to all your events, they make and share covers of your music and fan art. That isn't millions of views. It's tens of thousands. On youtube that's nothing. But 30 years ago you'd feel it was a great accomplishment, and if it was all you achieved you could be happy with that. As is has become more possible for a few of the most broadly appealing and unchallenged works to reach millions of people the goalpost has moved. Plenty of valuable content will never reach millions of viewers-- the appeal is too niche. It's a worthwhile contribution to the world none the less, but it isn't compensated as such on youtube.

kmeisthax 4y ago

The problem is that AI doesn't really "reference" data. When you "train" an AI on some data, you're adjusting billions of model parameters to make them closer to the desired output. Except you're also doing that on billions of pieces of other data, many times over, and every bit of data you train on is stepping on everything else. In order to pay people a share of the 'profits' of AI, you need a clear value chain from licensed training data to each output, through the magical linear algebra data blender that is gradient descent. Nobody knows if your training example helped for the same reason why we don't know if an LLM is lying or not. In lieu of that, you could pay everyone a fixed cut based on presence in the training set, but that then gives you the Spotify problem of a fixed pot being shared millions of different ways. For example, Adobe recently announced they were building an AI drawing tool trained on exclusively licensed sources - specifically, Adobe Stock contributors[0]. They're used to being paid when someone buys their image, which means that they have incentives to produce broadly relevant stock photography. But with a fixed "AI pot" paying you, now you have an incentive to produce as much output as possible as cheaply as possible purely to get a larger part of the pot. This is bad both for the stock photo market[1] AND the AI being trained. AI is extremely sensitive to bias in the dataset. Normally, when we talk about bias, we think about things like "oh if I type CEO into Midjourney all the output drawings are male"; but it goes a lot deeper. Gradient descent does not know how to recognize duplicate training set features, those features get more chances to adjust the model. Eventually that training example or image is common enough to make memorization 'worth it' in terms of parameters used[2]. Ironically that sort of thing would actually make attribution and profit-sharing 'easier', at the expense of the model being far less capable. [0] Who, BTW, I don't think actually have the ability to opt-in to this? Like, as far as I'm aware this is being done through the medium of contractual roofies being dropped into stock photographers' drinks. [1] Expect more duplicates and spam [2] This is why early Craiyon would give you existing imagery when you asked for specific famous examples and why Stable Diffusion draws the Getty Images watermark on things that look like a stock photo of a newsworthy event.

ec109685 4y ago
AI could be used to decide if a source should be included or not (or the benefit to the model could be the qualifier). That would solve your problem of people just peddling spam. No this is an unsolvable problem. The future also seems like less about making the model an all knowing oracle but instead making it smart enough to know how to lookup data it needs, so it could end up where licensed data is all that is needed for training. Lastly, what if you use model A to generate data for model B? Would B be tainted? There have been lots of examples where LLM’s are used to train simpler models by synthesizing training data.

WhereIsTheTruth 4y ago

I don't think ownership makes sense in the future we are building, optimizing society to achieve greatness as a multiplanetary species involve reinventing money and its purpose What society would be today if you had to pay a fee whenever you wanted to use the Pythagoras theorem, we'd be stuck in dark times

__MatrixMan__ 4y ago
Oh you're absolutely right, the notion that you can own information is absurd. Maybe it was necessary at one time as a kind of training-wheels for innovation, but we've long since outgrown it. It'll only ever get more and more absurd. But if somebody you don't know is doing something that's benefiting you, and you're not contributing to their ability to continue doing that thing in some way, then you might be shooting yourself in the foot. In any future worth pursuing, they'd be free to stop contributing if they felt like it, but wouldn't it be a shame if they did so without even knowing that their contributions were considered incredibly valuable by somebody? Like, imagine if Pythagoras couldn't afford food and had to give up geometry club and get a "real job". That would be to everybody's detriment. So while I think that "property" is the wrong tool here--we shouldn't be witholding access to our contributions for any reason--I do think we need something that's a little more impactful than an upvote for saying "more like this please".
manuelmoreale 4y ago
I appreciate your optimism but in the future we’re building, money and ownership seems to be more and more important unfortunately.
- JieJie 4y ago
  Which is why we should be very careful when we consider creating a system that is going to funnel money to people who are already famous for writing, art, etc. How will new artists and writers get their works included in future AI — and then get people to prompt for them — so they can get their paycheck? Even spending a few minutes on this problem would lead to a realization that even if we could create a system that could a) determine rights to any particular portion of an AI-generated work, and b) extract payment and remunerate the artist; would essentially be building a moat around the next generation's intellectual property powerhouses. Generative AI is a revolutionary technology, and we need a revolution in compensation models for arts and letters to go with it.