In its submission to the Australian government’s review of the regulatory framework around AI, Google said that copyright law should be altered to allow for generative AI systems to scrape the internet.
In its submission to the Australian government’s review of the regulatory framework around AI, Google said that copyright law should be altered to allow for generative AI systems to scrape the internet.
An AI model is a derivative work of its training data and thus a copyright violation if the training data is copyrighted.
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This is stupid and I’ll tell you why.
As humans, we have a perception filter. This filter is unique to every individual because it’s fed by our experiences and emotions. Artists make great use of this by producing art which leverages their view of the world, it’s why Van Gogh or Picasso is interesting because they had a unique view of the world that is shown through their work.
These bots do not have perception filters. They’re designed to break down whatever they’re trained on into numbers and decipher how the style is constructed so it can replicate it. It has no intention or purpose behind any of its decisions beyond straight replication.
You would be correct if a human’s only goal was to replicate Van Gogh’s style but that’s not every artist. With these art bots, that’s the only goal that they will ever have.
I have to repeat this every time there’s a discussion on LLM or art bots:
The imitation of intelligence does not equate to actual intelligence.
Absolutely agreed! I think if the proponents of AI artwork actually had any knowledge of art history, they’d understand that humans don’t just iterate the same ideas over and over again. Van Gogh, Picasso, and many others, did work that was genuinely unique and not just a derivative of what had come before, because they brought more to the process than just looking at other artworks.
Yup. There seems to be a strong motive in many to not understand this concept as it makes their practices clearly ethically questionable.
My feeling is that the vast majority of pro-AI techbros come from a computer science, finance, or business background; undoubtedly intelligent people, but completely and utterly lacking in any appreciation or understanding of what actually goes into creative work. I’m sure they genuinely believe that there’s no difference between what a human does and what an AI does, because they think art (or writing, music, etc) are just the product of an algorithm.
Ironically, my background is in mathematics but I also happen to be a writer so I see both sides of the argument. I just see the utter lack of compassion people have for those who produce creative work and the same people believe that if it can be automated, it should be automated.
Likely. Which is weird because algorithms are only a subset of software engineering, which requires abstract and creative thought to perform well.
I really, really, really wish people would understand this.
AI can only create a synthesis of exactly what it’s fed. It has no life experience, no emotional experience, no nurture-related experiences, no cultural experiences that color it’s thinking, because it isn’t thinking.
The “AI are only doing what humans do” is such a brain-dead line of thinking, to the point that it almost feels like it’s 100% in bad faith whenever it’s brought up.
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I wasn’t talking about copyright law in regards to the model itself.
I was talking about what is/isn’t grounds for plagiarism. I strongly disagree with the idea that artists and art bots go through the same process. They don’t and it’s reductive to claim otherwise. It negatively impacts the perception of artists’ work to assert that these models can automate a creative process which might not even involve looking at other artists’ work because humans are able to create on their own.
A person who has never looked upon a single painting in their life can still produce a piece but the same cannot be said for an art bot. A model must be trained on work that you want the model to be able to imitate.
This is why ChatGPT required the internet to do what it does (the privacy violation is another big concern there). The model needed vast quantities of information to be sufficiently trained because language is difficult to decipher. Languages evolved by getting in contact with other languages and organically making new words. ChatGPT will never invent a new word because it’s not intelligent, it is merely imitating intelligence.
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Once again, being reductive about artists’ work. Jackson Pollock’s entire career was smashing colours on a canvas. If you want to argue that Pollock had to look at thousands of paintings before making his, I honestly can’t take you seriously at that point.
Yes and in the eyes of its creators, that was deemed a failure which is why Midjourney and Dall-E are the way they are. These bots don’t want to create art, they want to imitate it.
Children have barely any experiences and can still create something. You might not deem it worthy of calling it art but they created something despite their limited knowledge and life experience.
Of course, you’d need books to read and write. The words have to be written and you need to see the words in written form if you also want to write them. But one thing you don’t take into account is handwriting. Another thing that is unique to every individual. Some have worse handwriting than others and with practice (like any muscle) it can be improved but you haven’t had to have seen handwritten text before writing it yourself. You only need to be taught how to hold a pen and you can write.
Novels are complex structures of language just like poetry. In order to write novels, you have to consume novels because it’s well understood that to find your own narrative voice you must see how others express theirs. Stories are told in unique ways and it’s crucial as a writer to understand and break these concepts down. Intention and purpose form a core part of storytelling and an LLM cannot and will not be able to express those things.
They’re written in certain ways because the author intended them to be that way, such as Cormac McCarthy deciding to be very minimalist with his punctuation.
I would love to see you make a point that an LLM without being specifically prompted to do so would make that stylistic decision. An LLM can’t make that decision because unless you specify a style it is aware of, it won’t organically do it.
I am also a writer. I’ve written a short story. One of my stylistic choices is that I don’t use dialogue tags like “said”. An LLM won’t make that choice because it isn’t designed to do so, it won’t decide to minimise its use of dialogue tags to improve the flow of the narrative unless you told it to.
Yes, in order to learn a spoken language you have to have heard it. However, languages evolve over time. You develop regional accents and dialects. All of the UK speaks English but no two towns speak the same way.
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An LLM or art creation tool is barely equatable to one person. The difference between a child and an art creation tool is that you could show a child a single picture of a bunny, a bike and a carrot then ask them to draw an orange bunny riding a bike and they could draw something resembling that. An art bot would require hundreds to thousands of images of each object to understand what it is before it can even make a reasonable attempt. It’s not even comparable the level of training required.
At least the child’s drawing will have some personality in it, every output from an art bot ends up looking soulless. The reason for that is the simple concept that an art bot only imitates what it’s been trained on and an artist draws on inspiration before applying the two things an art bot will never have; intent or purpose.
Not sure why you think anyone would read anything if that’s how you start it.
a human does not copy previous work exactly like these algorithms, whats this shit take?
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Neither does AI?
But considering that humans do get copyright strikes when they do something too similar that should also applies to AI, doesn’t matter if it’s not exact.
That should tell you something about how companies act. They’re fine with these LLMs plagiarising content but when someone gets marginally close to their own trademarks, they get slammed.
Humans and AI are not the same and an equivalence should never be drawn.
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And LLMs and related technologies, by themselves, are artificial but not intelligent. So, the facts are not in favor of your argument to allow commercial parasitism on creative works.
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Nah. You’re missing the forest for the trees. Let’s get abstract:
Person A makes a living by making product X and selling it.
Person B makes a living by making product Y and selling it.
Both A and B are in the same industry.
Person C uses a machine to extract the essence of product X and Y and blend them. Person C then claims authorship and sells it as product Z, which they sell in competition to X and Y.
Person C has not created anything. Their machine does not have value in the absence of products X and Y, yet received no permission, offers no credit nor compensation. In addition, they are competing for the same customers and harming the livelihoods of A and B. Person C is acting in a purely parasitic manner that cannot be seen as ethical in any widely accepted definition of the word.
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First, feeding something into a machine is not the same as looking at it. Person C literally creates nothing. They are a parasite. There’s far more to creating than using statistical modeling algorithms. One cannot claim that that’s what people studying a style and then creating someone are doing because it is empirically false.
Second, the scope of the discussion is not just “can someone legally get in trouble”.
The scope here is not limited to “can someone legally get in trouble under current law” (which, seems likely but is still working its way through courts). The discussion is specifically discussing ethics. Person C has created nothing. They should have no product to sell, if not for persons A and B. Their competition with those that their product is derived from is a parasitic relationship, plain and simple. They are performing an act of exploitation with measurable harm both to persons A and B but also to further development of their craft by destroying any incentive to continue it.
Now, in some sort of alternate economic system, where one’s livelihood is not tied to their vocation, sure, it’s possibly not problematic because the economic harm is removed. However, in current capitalist systems that are in place where LLMs are heavily hyped, it’s an ethically bankrupt action to take.
ETA: No amount of mental gymnastics can change the fact that use of others’ works without their consent to train a model, then claiming authorship and competing IS plainly theft of the labor that went into creating the original works.
That’s not too say that LLMs and they like don’t have value or often require effort to produce something worthwhile. Just that they need to be used in an ethical manner that improves the human condition, not as another tool to rob others of the fruit of their labors.
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The goal of AI is fictional, and there’s no solid evidence today that it will ever stop being fiction.
What at have today are stupid learning algorithms that are surprisingly good at mimicing intelligent people.
The most apt comparison today is a particularly clever parrot.
I’m all for having the discussion about how to handle AI when we have it, but it’s bad faith to apply it to what we have today.
Critically, what we have today will never ever go on strike, or really make any kind of correct moral decision on it’s own. We must treat it like dumb automation, because it is dumb automation.
…says who? That’s absolutely your feeling and not facts.
Derivative works are only copyright violations when they replicate substantial portions of the original without changes.
The entirety of human civilization is derivative works. Derivative works aren’t infringement.
That’s just not true
It absolutely is. There’s nothing out there in the past thousand years that isn’t based on other prior art, copyright law only replies to direct copies, and there are explicit cutouts past that that allow you to directly copy some things if your work is transformative.
It is not a derivative work, the model does not contain any recognizable part of the original material that it was trained on.
Except when it produces exact copies of existing works, or when it includes a recognisable signature or watermark?
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The point is that if the model doesn’t contain any recognisable parts of the original material it was trained on, how can it reproduce recognisable parts of the original material it was trained on?
That’s sorta the point of it.
I can recreate the phrase “apple pie” in any number of styles and fonts using my hands and a writing tool. Would you say that I “contain” the phrase “apple pie”? Where is the letter ‘p’ in my brain?
Specifically, the AI contains the relationship between sets of words, and sets of relationships between lines, contrasts and colors.
From there, it knows how to take a set of words, and make an image that proportionally replicates those line pattern and color relationships.
You can probably replicate the Getty images watermark close enough for it to be recognizable, but you don’t contain a copy of it in the sense that people typically mean.
Likewise, because you can recognize the artist who produced a piece, you contain an awareness of that same relationship between color, contrast and line that the AI does. I could show you a Picasso you were unfamiliar with, and you’d likely know it was him based on the style.
You’ve been “trained” on his works, so you have internalized many of the key markers of his style. That doesn’t mean you “contain” his works.
Just because you can’t point to a specific part of your brain that contains the letter ‘p’ doesn’t mean it isn’t in there somewhere. If you didn’t contain the letter ‘p’, or Getty watermark, or Picasso’s work, you wouldn’t be able to recognise them when you saw them or tried to replicate them. The act of recognising something that is familiar is basically the brain comparing what the eye sees with what is stored in the memory. The brain stores it differently to an exact copy on a hard drive, but it does, nevertheless, contain everything that it remembers.
I disagree that recognition implies you contain it. It’s much closer to a description than the actual thing, and a description isn’t the same as the thing. This is evidenced by you being able to look at a letter P in a font you’ve never seen before and recognize it without issue. If it was just comparison, you couldn’t do that.
Ah, this old paper again. When it first came out it got raked over the coals pretty thoroughly. The authors used an older, poorly-trained version of Stable Diffusion that had been trained on only 160 million images and identified 350,000 images from the training set that had many duplicates and therefore could potentially be overfitted. They then generated 175 million images using tags commonly associated with those duplicate images.
After all that, they found 109 images in the output that looked like fuzzy versions of the input images. This is hardly a triumph of plagiarism.
As for the watermark, look closely at it. The AI clearly just replicated the idea of a Getty-like watermark, it’s barely legible. What else would you expect when you train an AI on millions of images that contain a common feature, though? It’s like any other common object - it thinks photographs often just naturally have a grey rectangle with those white squiggles in it, and so it tries putting them in there when it generates photographs.
These are extreme stretches and they get dredged up every time by AI opponents. Training techniques have been refined over time to reduce overfitting (since what’s the point in spending enormous amounts of GPU power to produce a badly-artefacted copy of an image you already have?) so it’s little wonder there aren’t any newer, better papers showing problems like these.
Nevertheless, the Getty watermark is a recognisable element from the images the model was trained on, therefore you cannot state that the models don’t spit out images with recognisable elements from the training data.
Take a close look at the “watermark” on the AI-generated image. It’s so badly mangled that you wouldn’t have a clue what it says if you didn’t already know what it was “supposed” to say. If that’s really something you’d consider “copyrightable” then the whole world’s in violation.
The only reason this is coming up in a copyright lawsuit is because Getty is using it as evidence that Stability AI used Getty images in the training set, not that they’re alleging the AI is producing copyrighted images.
I said “recognisable”, and it is clearly recognisable as Getty’s watermark, by virtue of the fact that many people, not only I, recognise it as such. You said that the models don’t use any “recognizable part of the original material that it was trained on”, and that is clearly false because people do recognise parts of the original material. You can’t argue away other people’s ability to recognise the parts of the original works that they recognise.
I said that models don’t contain any recognizable part of the original material. They might be able to produce recognizable versions of parts of the original material, as we’re seeing here. That’s an important distinction. The model itself does not “contain” the images from the training set. It only contains concepts about those images, and concepts are not something that can be copyrighted.
If you want to claim copyright violations over specific output images, sure, that’s valid. If I were to hit on exactly the right set of prompts and pseudorandom seed values to get a model to spit out an image that was a dead ringer for a copyrighted work and I was to distribute copies of that resulting image, that’s copyright violation. But the model itself is not a copyright violation. No more than an artist is inherently violating copyright because he could potentially pick up his paint brush and produce a copy of an existing work that he’s previously seen.
In any event, as I said, Getty isn’t suing over the copyright to their watermark.