Midjourney is just a tool. It looks to me like the author is the one using the tool for copyright infringement.
I’ve seen this framing and don’t agree with it.
What does it mean for something to be “just a tool”? I think most people are trying to indicate that the tool itself is not of consequence, and that the issue is all with users who misuse it.
But by reducing generative AI to a low resolution category like “tool”, the way this tool works - arguably the subject of consequence - gets obscured.
It seems to me like these are “just tools” the way a highly sophisticated manufacturing facility capable of producing products is “just a tool”.
We’re not talking about paint brushes and screw drivers here.
In your mind, what distinguishes something that is "just a tool" from something that is "more than just a tool"?
To me, this framing is just not useful. It doesn't tell me anything about the implications of the existence of the tool. If I described an ICBM as "just a weapon" in a discussion about weapons that also includes bows and swords, I don't think it fits in the same category. To me, "just a tool" is fundamentally reductionist. It's anti-curious. It papers over the interesting parts of what's going on and leaves us with nothing to assess the situation. It forces some kind of artificial equivalence between things that are entirely unlike each other.
There are several implications of being a tool that can be explored, if one is interested. A printer manufacturer isnt liable if I use it to print and sell copies of Harry Potter, or some other copyrighted material. Just because I own the printer, doesnt mean I own unrestricted rights to anything that comes out of it.
Another interesting question is what commercial use of midjourney looks like if you cant trust it to produce content unencumbered by copyright? do you have to run everything it produces through a similarity engine? what are the appropriate thresholds that have been established for similarity?
The Orange Prince supreme court case was a fascinating exploration of the topic [1]. The SC case is quite an approachable read or listen and even humorous at times. [2]
1) https://en.wikipedia.org/wiki/Andy_Warhol_Foundation_for_the...
Can you clarify which thing is important/insightful? I want to make sure I’m understanding your comment.
I should also clarify that I do think AI is a tool. And I do think that the questions raised about other tools are interesting to ask relative to AI.
My main issue is with the “just a” framing, which usually comes with a strong implication that this tool status means AI should be treated no differently than a paintbrush.
> Another interesting question is what commercial use of midjourney looks like if you cant trust it to produce content unencumbered by copyright?
This is one of the key things that establishes a new category of concerns that is not present in other common tools. e.g. if I use a paintbrush to make counterfeit artwork, it is clear that the act of creating the specific output was deliberate (it would be hard to argue that I didn’t know what I was doing over 40 hours of detailed painting). I can’t be sure what will or won’t come of a generative image model.
I pointed out several thoughts it led me to in the post. Another is the tool framing Delinates infringement occurring during the manufacture of the tool, and the use of the tool. It also leads to other interesting points like your last one about the paintbrush. I have never heard of intent being used as a criteria of counterfeit. I don't think this is a new class however. I can use Google images and a printer to quickly produce infringing material. What conclusions can be drawn from viewing generative art models through this lens
Similarity is a prerequisite for infringement. No similarity means no infringement [1]. If a person painting with Photoshop produces something similar to an existing work and publishes the work to anyone else in a way not covered by fair use, then the painter bears the liability for the copyright infringement. Analogously, if a person using an ML model gives a prompt with a reference to an existing work, author, or strongly associated characteristic/style, gets an output similar to an existing work, and publishes the output to anyone else in a way not covered by fair use, then the user of the model should bear most of the liability for the copyright infringement. The model maker should take reasonable steps to prevent users from giving such prompts (or the model from accepting such prompts), but otherwise should bear no more than a minority of the liability (unless the model regularly gives infringing outputs for prompts with no references to any works, authors, or characteristics/styles).
[1] https://en.wikipedia.org/wiki/Substantial_similarity#Substan...
If this were true there would be no art, my friend.
Theoretically a painter can make art after having seen nothing but the real world or unedited photographs. Before people had the means to make and share paintings, they couldn't learn from paintings. They learned from the real world and their art styles. (One way of defining a painter's art style is "the opposite of what the painter can't paint".)
Painters today generally don't learn how to paint by restricting themselves to looking at just the real world and realistic depictions, and the exceptions are not relevant to the question of what is copyright infringement. This is an assumption I didn't realize I was making, and now I am making it explicitly: The painter using Photoshop has seen paintings before (complete or in progress, doesn't matter), and the painter's creations are influenced by those past paintings.
So I retract the following sentences from my previous comment:
>> Whoever's using Photoshop to paint, however, does need to have seen existing artwork.
>> A person using an ML model doesn't need to have seen existing works to ask for a generic output, but does need to have seen existing works to ask for an output similar to an existing work (outside of innocent name coincidences in the prompt like "a painting of a starry night").
And replace them with the following:
In order to use Photoshop to produce a painting similar to an existing one, a painter usually needs to have seen existing paintings. There may be coincidences, such as when the painter's art style produces results similar to another painter's.
In order to make a model produce an output similar to an existing work, the user usually needs to have seen existing works and subsequently give the model prompts referencing an existing work, author, or a characteristic/style strongly associated with a work/author. By strongly associated, I mean that a user who hasn't seen the Salvador Dalí painting "The Persistence of Memory" but has seen unrelated oil paintings might coincidentally give the prompt "oil painting of melting clocks" and get an output similar to that Dalí painting.
My response would be that much hinges on the word “usually”, as in, the artist must “usually” have seen existing Dali work to recreate a similar aesthetic.
While that’s certainly true, it’s also true that similar art evolves in different places at similar times. Which is to say, while “usually” is accurate, “always” is not.
AI requires “always”. In the same way a photocopier, or a collage of existing works, requires the prior art to exist inside it in order to produce similar output.
I don’t think it’s unreasonable to ask for compensation, if a tool is unable to produce the desired result without including your existing oeuvre of completed, copyrighted work.
I agree, but I think there should be bounds to how much compensation the authors of the existing works are entitled to, because there is a well-established context in which relying on someone else's work doesn't entitle that person to compensation.
Suppose that I review a book I bought legally and post my review online for anyone to see. I couldn't have come up with the review without reading the book. I would've been unable to produce my book review without putting the author's expression in the existing, copyrighted book into my mind. I don't need to claim that human minds and machine learning models are any more similar than the fact that they can take in information. Without specific information from a particular copyrighted work, I couldn't have made the book review. But as long as I legally obtained the information in the book (by buying the book), I don't need to pay the author for the book review itself because a book review likely is fair use. Due to the first sale doctrine, I don't owe the author anything for my book review even if I bought the book secondhand at a higher price than the original seller charged i.e. 1. I didn't compensate the original author for the book and 2. the person I bought the book from profited from selling the book to me.
I've read the argument that the very scale of what an AI process can do (e.g. be trained on 1000s of books, can then summarize just as many books) means that humans using AI models should compensate authors in cases where a human manually performing the same kind of task doesn't have to compensate authors. That's an important argument, but figuring out the bounds for compensation with respect to scale is not clean either. Suppose that I make a training set consisting entirely of OCRed [1] scans I make of all of the books I own, including a 100 or so books that my friends gave to me. Here are a few versions of how I use the training set, in increasing order of complexity:
EX1. I make a non-ML word counter, and the training is counting the frequency of each word across the sum of the books. I can can make the program predict the next word in a given prompt: pick a random word from the sum of the training set and the prompt; a word gets additional weight in the random selection according to the frequency of the word within the training set and also gets additional weight according to the frequency of the word within the prompt.
EX2. Like EX1, except the program also takes into account the frequency of pairs of adjacent words in the text.
EX3. Like EX2, except the program rates pairs of possibly non-adjacent words in the text according to frequency and the number of words between every two given words in the text.
And so on. At a much later stage such as EX58, I switch to making machine learning versions of the program, which started as a word counter and became more of a word predictor. I think EX1 shouldn't require compensation to the authors of the books, but I'm not sure about EX57. How complex can the capabilities and accuracy (two separate but important factors) of a program trained on copyrighted works be until I need to pay compensation? There is definitely a difference between a sand grain (EX1) and a sand pile (EX??), but a law regulating AI has to consider where to place the boundaries to balance freedom of expression (which includes writing/sharing code and machine learning weights) and obligation to compensate authors. (I also think this is a problem beyond the scope of copyright. Copyright in the US doesn't reward the "sweat of the brow" [2] and doesn't apply in cases without substantial similarity, so I think AI compensation should be treated as completely separate from, not even ancillary to, copyright.)
I don't have answers, but at the very least I don't want a hard line of "no AI model of any complexity without compensating authors". Predictive LLM that can write books (dubious quality, but possibly coherent)? The expected uses of such a model scale very easily in complexity and size, so the authors should get compensation, unless whoever makes the LLM only uses it for private personal purposes. A predictive LLM that can't remember more than 100 words at a time? Probably can't write a coherent book, so no compensation even if the training set includes entire books.
[1] https://en.wikipedia.org/wiki/Optical_character_recognition
[2] https://en.wikipedia.org/wiki/Sweat_of_the_brow#United_State...
Agreed. A review is generally a personal reaction to a piece of art, and therefore inherently new work.
However, if you’re selling summarized versions of the book as a service, it’s a bit trickier.
When AI exists that is capable of a personal reaction to a work of art, along with the capability of earning money and therefore being able to purchase the book, these questions will be more pertinent. Until that time, we are dealing with people/companies who have included whole cloth existing work into the technology they’re selling to others as a service — a situation well within the realm of licensing laws, which appear to have been utterly ignored in an attempt to force convenient legislation (similarly to the various scooter companies who littered cities with their product and demanded legislation be enacted to their wishes, rather than those of the existing, law-abiding society).
NB: the AI producing books is not the main concern I’m addressing. Most books sold to humans are simply read, not used as fodder for further work — but they still require compensation for merely ingesting the material in the first place. AI is not a human, it is a product. The fact that it can produce further data in no way negates the need to license the data upon which its foundations are built.
The fact that you can now tell a tool what to do illustrates my point. You can’t “tell” your paintbrush what to do, and what your paintbrush does is wholly based on your personal ability. If you use your paintbrush to create counterfeit currency, there is no question as to whether or not you deeply participated in the creation of the output.
Prior to the introduction of generative AI features in photoshop, you couldn’t “tell” photoshop what to do either.
There is myriad of deep and fundamental differences between manipulating these earlier generations of tools directly and verbally instructing a black box to execute its algorithms.
I think this difference is similar to the difference that would exist if we could build Star Trek style replicators and if we were comparing the act of preparing a meal from scratch vs. asking the replicator to print a meal.
Is the replicator a tool? Yes, but a tool for which the mental models associated with a kitchen full of cooking and baking implements do not apply.