> We need to find way to make sure the access to this data the models were trained on, and the resulting models, is open and fair

Agreed. The irony is that all the current anti-machine-learning lawsuits will make it so only big companies with deep pockets will be able to continue to make & use them.

I mean we never seem to care about the downward pressures we put on others, so this seems a contrived place to do it now.

My take on the matter is that facts aren't copyrightable. A LLM is basically recording facts.

I have a background in stylometry where you basically determine authorship by recording statistics on known pieces of writing to try to find the author of another piece of writing. So just extracting facts. You could easily now generate random sentences and filter ones that pass a certain threshold. LLMs are basically this on steroids. So it's just facts and data, not copyright infringement.

Otherwise, you'd have to argue that software reading the text contents of a book are copyright infringement.

> I have a background in stylometry where you basically determine authorship by recording statistics on known pieces of writing to try to find the author of another piece of writing. So just extracting facts

The logical jumping happens around this period symbol is spectacular.

I was assuming people were familiar with the process and handwaving the rest.

You measure things like:

* What average sentence length?

* What is the ratio of adjectives to nouns?

* What percentage of sentences are in a passive voice?

* What is the distribution of words used?

* Is "the" used more often by the other than in general usage?

* "whence" vs "when".

* "tyre" vs "tire". Etc.

This could all be printed out and sold as a book and each measure would be a very boring fact that is not copyrightable and contains no copyrightable content.

I could give you a word frequency list from the A Song of Fire and Ice series and George RR Martin could do nothing about it. (Technically, he might have the rights to "Arya" and "Lannister", but to say "the word 'Lannister' appears 1,337 times in the series" would clearly fall under fair-use).

Sorry it's nonsense. You're basically saying:

1. Anything existing is considered a fact.

2. Stating a fact doesn't infringe copyright.

The only conclusion your logic can infer to is copyright doesn't exist.

For example, I can say "the first sentence of A Song of Fire and Ice series is <insert the first sentence>, the second sentence is <insert the second sentence>, the third sentence is...". It's still just a list of facts, so no copyright infringement, right?

I think it that case if you went through the whole book like that a judge would argue that you are infringing because you can recover the whole book like that.

But if you went by and grabbed the very first sentence from each chapter that's is sufficiently in the clear. Especially when you are doing something transformative with it. Like for example analysing what makes for an effective opening sentence.

With copyright you always get to ugly slippery slope arguments, Tom Scott has a great video on it.

But if you cannot extract something the replaces the original work you should be already in the clear. I'm pretty sure Cole's Notes don't need the original author's permission to print and they are arguably a substitute for reading the original work. I've skimmed through entire series by reading the individual episode summaries on Wikipedia. These are in the clear.

The fact that a machine speeds up a human process does not change legality.

>Otherwise, you'd have to argue that software reading the text contents of a book are copyright infringement.

How so?

Because that's all the ai model is doing. It's reading the books.

How an entity (human or not) changes after reading those books is not in the purview of copyright.

It has not shared them (copied). It has read them, learned from them, and changed itself in response.

Why is an AI model allowed to read a book without paying for access to it, but I as a human have to pay for it to read it?

That's not the argument being made, is it? If the AI is trained on pirated data, it's a completely different case than the underlying principle of AI meaning all generated content is copyright infringement.

But I thought they were being trained on pirated data...

Seems like a problem to me.

They're being trained on copyrighted data that was publicly accessible. The lawsuits focus on whether or not this is copyright violation, not the legality of accessing the material (AFAICT).

So the world is just ignoring the legality of accessing the material in the way that they did?

Man, I wish as a human I could use the defense of "but it was publicly accessible in a torrent" as a valid reason that I acquired and consumed some content.

Sorry, do you have some proof that they pirated content that the scrupulous copyright holders themselves don't? That's not the issue at hand and, AFAICT, nobody is accusing them of doing it.

Nobody is ignoring it, that would be a crime if they did, but since there's no evidence of it... you're being upset at your own hypothetical.

I'm really confused.

I see articles all over that LLMs for example used books3, which the creator himself has admitted came from torrenting from bibliotik, and which contains at least some books that are not otherwise freely available.

The issue that content creators have with LLMs is not getting proper attribution for their creations and source material that went into training these LLMs, and it seems pretty clear to me that some of the content that was used to train LLMs was not legally obtained and licensed to consume.

The AI should, no doubt, pay to read the book!

In technical terms, these companies are trying to avoid the need to consider content licensing, which is a major violation to content creators.

You aren't licensing it. You are reading it. A machine reading it is no different than a human. I mean it really shouldn't be. Should a visually impaired person using a screen reader have to "license" the book?

But not all the works that have been consumed by LLMs are available to read without a license to do so.

That particular transformation of the book does well on a fair use analysis. If the blind person were to use the screen reader to put the book on Spotify, it would almost certainly fail a fair use analysis.

People come up with the most bizarre corner cases to justify freeloading on other’s intellectual property.

Content is obviously being relicensed as the models are not fully open.

On top of that, it is also being exposed as pay-for-use subscription models without paying anything to original authors. How is that fair use?

You can check the book out at the library and read it. Someone has to buy it, but not necessarily you personally.

You can check out some books at libraries for free, sure.

LLMs are trained on tons of books and papers that are not available to humans for free anywhere.

Can you give an example of something that they are trained on that a human can't somehow read without buying?

Textbooks for 1 example.

You are telling me that all the books in books2 and books3 can be acquired and read by myself completely free of charge legally without piracy?

If humans can get these books for free legally, why are so many people paying so much to buy them for their college courses?

I thought it's well known that LLMs are being trained on pirated content.

Textbooks aren't somehow banned from libraries. You'll find lots of textbooks in public libraries, school libraries, and other libraries where they can be read without paying for the book.

Now if you are saying they obtained the book from illegal sources that is a valid argument. But the issue there is orthogonal feeding the contents of the books into an LLM. It is legal for me to view and photograph the Mona Lisa. If I break into he Louvre to view the Mona Lisa, the issue isn't that I viewed the artwork. The issue is that I broke into the museum.

Yes but then the issue isn't whether copyrighted works can be used as training data, but how you can obtain those works to use them as training data. I agree that you can't justify copyright infringement based on the fact you are using it as training data. But I do not agree with those that say using a legally borrowed book as training data violates copyright.

But if you have an example of some types of books that it is impossible to borrow from anywhere on the planet please share. Textbooks are readily available from libraries.

No, they aren't banned, but not being able to find one at a library is not a legal justification for me to go and torrent it. It shouldn't be for a corporation training an LLM either.

It's widely known that some of the big LLMs were trained on book datasets that were acquired via torrents. And that those datasets do contain at least some books that are not available anywhere freely via legal channels.

There is nothing illegal about reading a book that you haven't paid for.

What's illegal is making and distributing copies of a book.

But the reader isn't in trouble for reading a book they don't own.

Really?

So I am free to torrent all the books that I want, and there is no legal action that can ever be taken against me?

If so that would be news to me.

If you start distributing torrents and copies to other people?

No of course not.

Creating copies, and distributing them to other people is against the law.

That has nothing to do with what I said though.

What I said is that it is not illegal for a reader to read something that they havent paid for.

Do you see how that is different from distributing copies of something to other people?

That's not what I am asking though...

I am asking about reading content that is not available through any free means, and pirating it in order to read it instead of paying for it from the author.

> I am asking about reading content that is not available through any free means, and having to pirate it in order to read it.

Reading it is legal.

Distributing torrents is not though. That is the part of piracy that is illegal. The illegal part is when you create and distributing copies.

Copyright law has nothing to do with reading stuff that you have not paid for.

Instead, it is about the illegality of creating and distributing copies.

That's why it's called "copyright" law. Because it is about copies.

It is not "readright law".

No, there is nothing illegal about reading something that you havent paid for.

I didn't know it was legal to download books from torrents that are normally only available from the author for a cost.

What about movies and tv shows? I can download them via torrents to view without paying as well, completely legally?

Nobody can ever take any legal action against me ever for doing this?

How though would the creator of the content ever get paid for it if everyone can read and view it completely free? Why would they go through all the work of creating it with no gain to themselves?

Torrents are a somewhat special case since, by protocol, downloading and sharing happen at the same time. So by running a torrent of pirated media, you are necessarily infringing copyright (there are hacked clients that report bogus information that allow you to download only without sharing, but they are easily detectable and ~nobody uses them).

As far as I know, nobody in this country has ever been successfully prosecuted for the mere act of downloading, or even having obviously-illicitly-acquired pirated media in their possession.

As to your final question, the actual answer is because people are lazy. It requires more effort and technical sophistication to maintain a movie file collection than it does to run Netflix. Nearly any piece of remotely popular content is available for free with a bit of knowledge, but it's less hassle to just subscribe to services. There is no world in which piracy actually endangers creators.

I should have used an example other than torrenting, one that doesn't automatically distribute back.

Also, I'd say there is a difference between being illegal and whether someone has been successfully prosecuted or not.

I don't understand though how piracy doesn't endanger creators though. If a small time creator creates something, say a video game, and everyone pirates it instead of buys it, how has that not endangered him? Simply because you don't think it's plausible that enough people would refrain from paying?

Pretty much. For the simple reason that the "legitimate" way is always easier and the people that pirate are always a minority as a result.

> Nobody can ever take any legal action against me ever for doing this?

They can if you create or distribute copies.

That part is illegal and will get you in trouble, and is why people get in trouble for torrenting.

Just reading or watching other people's content isn't the illegal part.

I think it's safe to assume that AI has to pay for the book as well, sooner or later, as shown in the deals OpenAI has made with content publishers such as AP [0]. The question is how much they should pay.

[0] - https://www.pymnts.com/digital-payments/2023/58percent-of-co...

In order to present a book to a ML algorithm you need to copy it, either using a camera, or using other means (eg as a file). In USA that copying might be Fair Use, it's almost certainly not allowed in UK law AIUI.

Copying a webpage into a cache that allows presentation of the page to a user is only allowed because it is part of rendering the page to a user. Even if a computer only copies two words at a time from a source text, if it copies a substantial part overall then it still copied.

Honestly, I don't think slurping data to train ML models is allowed by copyright (but, I do, probably think it should be, as long as any significant reproductions are then prosecuted as infringements [also we should reduce copyright terms to ~7 years!]).

This is all my own opinion, unrelated to my employment.

> In order to present a book to a ML algorithm you need to copy it, either using a camera, or using other means

Almost all modern books are available as ebooks for the Kindle or otherwise. You aren't doing anything to the content itself that could be a violation.

So, you copy the Kindle book from a server to your local host to feed into your training algo (ie other means). Or you stream it piecewise into a buffer, still copying.

As long as you only train the network and never use it for inference, I suppose that's a reasonable argument. But a person is restricted in action by copyright regardless of the writing implement they choose to use. Whether they use a pencil or an LLM, they cannot freely reproduce copyrighted works in whole or in part, excepting some narrow conditions.

IMHO, an LLM is not "reading" a book in any way, certainly there is no parallel with how people read. It is encoding the book. That's how it can regurgitate chunks of that book later, including, in some contexts, by providing verbatim spans of text from the book.

'we' who?

How would reproduction of fictional works or the creation of derivative works based on fictional training inputs constitute “a recording of facts”?

LLMs - as in the models, the weights - do not contain "reproduction of fictional works or the creation of derivative works based on fictional training inputs" in any meaningful sense. "Reproduction of fictional works" is what is present in the training data. "Creation of derivative works based on fictional training inputs" is what you might be doing as a user of a LLM. The models themselves are, like GP said, recordings of statistical properties of text, just taken up to 11.

> do not contain "reproduction of fictional works or the creation of derivative works based on fictional training inputs" in any meaningful sense.

Except it does, and it's in a quite literal sense.

You painted a painting. I took a picture of it and compress it as .jpeg. Byte-wise the .jpeg file has no similarity to your original painting. For someone who doesn't know .jpeg, it's just garbage bytes.

So I didn't infringe your copyright by selling this .jpeg file. The user who decodes the .jpeg file and displays it on a monitor does.

Does it sound right? This is how "weights do not contain training data" argument works.

And before "how about artists who store this information in their brains?" Well human being is a special case for every law in every country. Just like selling a cow's liver is never the same as selling a man's, even they're both organic tissues. A human's brain is always going to be treated differently than a hard drive.

My argument is that the modes are somewhere between your JPEG example and "artists' brains" example. Now legally, it's usually not the bytes themselves that matter, but their colour (provenance). But this doesn't make the case of AI models any more clear - the training process is also somewhere between zipping up a folder full of JPEGs, and a human practicing their art through fuck ton of repetitive reproductions of existing works until they grok the style.

I agree.

The thing I hate about this whole situation is that it's going to be decided solely on which side has more lobbying power[1], since just as you said, it's something in between.

[1]: One could say all the policies are decided this way...

> [1]: One could say all the policies are decided this way...

The silver lining here is that lobbyists can only afford to care about finite number of things at a time - so even if they get some laws their way, other factions can push laws mitigating the damage somewhat.

I currently believe (weakly) that the outcome of more and better lobbying isn't laws getting directly worse for society, but rather the regulatory system grinding to a halt under increasing number of laws that exist to cancel out parts of other laws...

> LLMs - as in the models, the weights - do not contain "reproduction of fictional works or the creation of derivative works based on fictional training inputs" in any meaningful sense.

Since portions of such works can be recovered in inference, they contain at least a lossily-compressed copy of the collection of works used in training. Reproduction isn’t pure coincidence.

Indeed, but learning is effectively[0] a form of lossy compression too. DNN weights are somewhere between zipping up a truckload of JPEGs and deriving facts from first principles. Where exactly are they on this spectrum and how it affects copyright, it's not obvious to me - at least not when trying to argue from fundamental principles. I feel the DNN copyright issues will be ruled on from purely pragmatic position: what's the legal status that upends existing markets the least, and/or is most favored by lobbyists.

--

[0] - I believe it's actually fundamentally the same thing.

> Indeed, but learning is effectively a form of lossy compression

Yeah, that copies in the brain of a human who has experienced the work and not reduced to any othe media are neither “copies” nor “phonorecords” as covered by US copyright law is pretty clear, and that this does not apply to data stored by clever algorithms in computer storage is also pretty clear, so I’m not sure what your point is.

If you want to argue LLMs are people to escape this, then, sure, copyright stops being a problem for their training data, but it still is for their output plus you end up a whole set of new legal problems with using them as people do now, starting with 13th Amendment problems.

There's a pretty big jump from "machine learning is not inherently different from human learning" to "machine learning models are people".

There's not a big jump from “human learning isn't treated as a copyright violation because it happens in people and not in external media” plus “machine learning should be legally treated like human learning” to “your argument depends on treating ML models as people”.

The fact that people making the second part of the first argument often either are ignorant of or deliberately ignore why human learning is treated the way it is doesn't change the essence of the situation.

That applies to both sides though: people arguing that machine learning should not be treated like human learning often justify it with "ML models aren't people, they're software on a computer". But that argument is also missing the point, and invites this kind of philosophical discussion. The essence of the matter is that there is no high-level principle involved - humans get special treatment because humans write the law. So we can legally round all machine learning down to "zipping a folder full of JPEGs" for pragmatic reasons, and get away with it until we actually create sentient AIs and recognize them as people.

(Which, knowing history and observing how we treat animals, will happen only when the sentient AIs coerce us to recognize them, through violence or the threat of it...)

> The essence of the matter is that there is no high-level principle involved - humans get special treatment because humans write the law.

“The purpose of law is to advance the collective interests of humans in a society” is, I would argue, a high-level principal, and (with variations as to whether it applies to all humans or some subset, and which interests are considered privileged relative to others) nearly universal. Yes, the fact that humans are writing the laws is a reason that principle is chosen, but the idea that there are not high-level principle is just false.

>“your argument depends on treating ML models as people”

They would be "legal people" in the sense that corporations are "people".

> that this does not apply to data stored by clever algorithms in computer storage is also pretty clear,

I'm sorry, this is far from "clear", otherwise we wouldn't be having this discussion. Fair use is a thing. Does fair use apply in this situation? No one knows at this point.

I think you're conflating two issues. As I understand it, this justification is about whether the training itself is fair-use. The discussion on whether the outputs are derivative or transformative is separate. Analogously, if I publish a copy of copyrighted poems from memory that would be infringement, but there's nothing infringing about me just reading and memorizing them.

> We need to find way to make sure the access to this data the models were trained on, and the resulting models, is open and fair.

Hear, hear. Unfortunately this is more or less impossible given current copyright law.

Suppose you scrape libgen and turn it into training data, then you release the training data publicly. Since the vast majority of every book appears verbatim in the training data, is this sufficiently transformative?

I think yes, it is, because nobody is going to read those books from the training data. When I made books3, I felt it was important to render each book into high quality text. But it turns out that when you convert Jurassic Park into a text file, there's no good way to read it anymore. Good luck trying to bookmark wherever you left off -- it's all one gigantic file.

But nobody seems to agree. The Danish Rights Alliance (https://rettighedsalliancen.com/) aggressively DMCA'ed anyone that hosted books3, even going so far as to DMCA The Pile from academictorrents: https://academictorrents.com/details/0d366035664fdf51cfbe9f7... with the justification that ~100 copyrighted books appear in the training data, so therefore they have the right to DMCA. Right now most of the world seems to agree, but I'm hoping that opinion will shift as the years tick by. Surely no one can believe that a plain text document poses a serious threat of economic harm to the original author. So the question is whether the original author should be allowed to deny everyone else the right to transform their work into a form that machines can read.

For my part, I've been planning a books4 dataset, but this time similar to LAION: it's a script that spiders libgen torrents (https://libgen.gs/torrents/libgen/) and converts all the epubs into text files. That way, if LAION isn't infringing, then books4 can't be infringing either. (Of course, hosting the actual training data anywhere is pretty hard nowadays, but it should only take a few days to convert 38TB of libgen into ~2TB of plain text.)

This is the only way to create an open source competitor to ChatGPT.

I'm actually on your side because I think copyright laws should be radically nerfed and things like books3 are greatly beneficial to society, but I wouldn't buy your argument about "no good way to read plain text files".

The text file contents all the text in the book in an (at the very least) machine-readable way, it is perfectly feasible to write a program to put it in ebook form or to play it as an audiobook, and then the text file becomes desirable for laypeople to read.

Unfortunately this is true of any encoding scheme, short of scrambling the order of the paragraphs. And although scrambling the order might seem tempting, it destroys the ability to train large context windows — 32k context tokens is enough to fit most of a book into a prompt, and this window will only grow bigger.

If your (quite reasonable) argument holds water, then it sinks our ability to ever share copyrighted training data with large context windows. That’s why it seemed important to justify a plain text training format, since anything on top of it would be equivalent.

Indeed, one alternate training format would be to ship the raw html from every epub file, then process it into text at runtime. But this makes it trivial to reconstruct the original epub file and use it in an actual book reader.

It’s frustrating that we can’t share the epub files, because there are so many advantages: you can scrape the metadata, you can tweak the rendering to plain text, you can get semantic info from the images (and even OCR them — it turns out that lots of coding epubs show code examples as screenshots, because epub html rendering is so primitive, so this would be the only way to let your model learn from those).

All of that is why I’m leaning towards "make a script to spider all of libgen and cache the epub files locally". But I haven’t finished calculating how much disk space this would require.

I’m sad that researchers will have to wait days for their training data instead of downloading it in a few hours from a high speed cache, but it seems like any such cache would be swiftly DMCA’ed, so there’s no alternative.

I don't know if this is tangential or not, but thank you. You've helped me progress my armchair understanding of how we might give the concept of copyright more finesse in the digital age.

The insight is that encoding content is not functionally the same as copying verbatim a work which is the original intent of the concept.

For example: if I have legally obtained a copy of e.g. https://archive.org/details/free_culture, then I am at liberty to encode it in whatever format I need to be able to feed it to a machine/tool for whatever purpose I want. I am not infringing on copyright because I legally obtained the work, and the machine is not because machines can't.

I think at least this much OpenAI has in their favor. If they can prove they legally obtained all the training material (I do think it's fair for them to be required to pay once for it) then I don't think there's any world in which it makes sense to try and allow content creators to further extract royalties from that process alone.

If a user asks an AI for a copyrighted poem, for instance, and the user goes and republishes that poem as their own, I do think it may make sense to grant the original author royalties under current law.

I really hope we can legally pick these two concepts apart and focus on each scenario independently. I see a lot of people here arguing that giving a work that you have legally obtained the rights to view to a machine model is inherently copyright infringement because you had to copy the work and yada yada is it fair use? I really think this is wrong both in the interpretation of copyright and practically as ideas can't be owned and it makes no sense to limit which ideas were used to make what commercial product etc. (we don't do that today and AI doesn't change that).

>If your (quite reasonable) argument holds water, then it sinks our ability to ever share copyrighted training data with large context windows

Only if the training data is under copyright! How about data that is in the public domain, or granted license specifically for training - Mozilla's commonvoice is an example.

Maybe someday there will be a rulings that do for ML training datasets what earlier ones did to legalize cleanroom design.

Sadly there just isn’t enough public domain data. It would mean that it’ll be impossible to catch up to ChatGPT.

One way to see this is to imagine a Midjourney competitor trained solely on public domain images. The visual quality of the model will always be worse.

As for licensing, I agree for commercial entities, but there should be exceptions. If a model is open source, it benefits everyone, and so it shouldn’t need to have been licensed. There are a few reasons why this is pretty important, but the main one is that without it, the open source community has no chance whatsoever of creating cutting edge models.

I think you can reasonably imagine that if content is available in a library then everyone could organize an effort to check out the content and add it to the model. That effort sounds like useless theatre at that point so just let the commons keep an `all-booksN.zip` corpus around for the purpose.

You know, you could probably even argue traditionally that taking all the books in the world and adding them to a corpus for the purpose of creating an LLM would be a transformative work since it doesn't compete with or detract from any of the originals…

Why can't I read or bookmark a huge text file? I can and have. Books3 (though this is the first time I'm hearing of it) shouldn't be fair use because it's inconvenient to read, it should be fair use because reading is not the intent. The intent is to train computers with it.

It does contain copies of copyrighted works.

Well, yes, otherwise you wouldn't need fair use, you'd just use it.

I would like to get in touch with you related to books4. Do you happen to have discord? or would twitter be ok?

There's currently multiple attempts at creating what you describe as books4.

Please do! Twitter DM is the most reliable. Or if you put some contact info in your profile I can reach out.

Added, and reached out on Twitter.

Technically, the money comes from people who pay to use AI (customers), or alternatively to buy art from artists.

To the extent they are out-competing artists, it's diverting a money flow from artists to somewhere else. But a lot of that money might be from people who would never have bought that art to begin with?

In any case, the money never belonged to the artists. It never got to them. The people it actually belongs to (the customers) get to make the decision about what to buy.

I think I agree but that never stopped the trade associations from coming after pirates for lost revenue. Then again, that wasn't really a winning strategy since they spent more on legal fees than they ever recovered from broke college kids and single moms.

Just tax the use of the technology and give back to humanity in terms of less work/ubi/etc.

I'm really curious about the political expediancy of this - the right wing tends to hate UBI but they also resent Big Tech and are probably not fans of algorithms taking their jobs, so maybe we can come to a compromise.

> they will soon be good enough that they will be able to replace the work of the people that produced the content the AI was trained on

Let assume this is true. It then follows that if we train LLM on all books that are out of copyright, the LLM would be able to replace the "work of the people that produced the content" that is just about to go out of copyright. Feed this body of work back into the LLM and you should end up with something just as advance as what you get by feeding in works that are under copyright.

I'm not sure the assumption is true. But if it is true, using copyrighted material or only non-copyrighted material shouldn't result in a different situation.

So we need new legislation.

Edit: To be more explicit, on my view both the parent and the op are right, and they don't contradict each other: We don't need new copyright legislation. We need new legal concepts.

I think both people are right: There is an overwhelming need to address the situation of artists and writers ("content creators"). Copyright is not being used because it's the right tool to do so, but because it's the only even vaguely plausible one. It's also clear that it's not sufficient.

We have legal concepts that fit. Ideas cannot be copyrighted. The particular expression of an idea can be copyrighted, but an idea itself is in the public domain. The ideas you or an LLM get from reading a book are in the public domain while the book (the expression of those ideas) is not.

In what way is that not sufficient?

There is no legal concept for a machine to have ideas. I agree with you that the current legal framework is clear, but I disagree as to the outcome: without new legislation, the creation of an LLM on unlicensed content seems to be the creation of a derived work without permission of the owners whose work you are deriving from, so the creation of the LLM itself is copyright infringement.

But we already have a way to deal with derived work. Reading a bunch of books and then writing with the ideas you learned is perfectly fine. Copying a paragraph without citing it is not. Mimic the style of authors you want to emulate is fine. Passing off their book as your own is not.

If creating an LLM is copyright infringement, then we could say that a human reading a book is copyright infringement.

And thus copyright is not a good framework for LLMs...

It's obvious that this technology was not considered when developing current legal concepts, so if the concepts produce unsatisfactory outcomes, they need to be reevaluated.

But a human reading !== A computer "reading".

Why do people so easily and readily conflate the two? Is it just because it makes the AI hype sound more real, if you compare it 1:1 with a human brain?

Machines and humans are not equal or even in the ballpark of being similar in any way other than superfluous ones, and should (and already are) held by different standards, both legal and otherwise.

I don't understand your argument. I concur with the GP (https://news.ycombinator.com/item?id=37780772) that there are legitimate issues around LLMs that need addressing. I say that current legal principles seem inadequate to address these issues. Your "counterpoint" seems to merely reiterate the latter. You seem to agree that these concepts can not be used effectively to address issues around LLMs pointed out, as what the LLM extracts is not copyrightable.

Do you simply disagree that there are issues worth addressing?

Also, typically the entity that carries ideas can not be owned by a cooperation. So there is a completely new relationship between property and ideas at play.

I'm okay with the idea of no copyrights at all on works that are fully or partially AI derived. Of course, that introduces even more thorny arguments (what legally constitutes "AI"), but the courts can work that out.

It's clear already that companies are going to be want to have their cake and eat it too. When they leverage AI to produce content, they don't want to be forced to pay licensing fees on the inputs to their models. But on the flip side, they absolutely don't want their content being used in models leveraged by other people.

Not allowing copyrights on wholly or partially AI-generated work is probably the lesser evil path to take.