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Ownership of AI-Generated Code Hotly Disputed

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181–190 of 205 posts

Re: Ownership of AI-Generated Code Hotly Disputed

#181
post #16

“…modify[ing] its AI model so that it traces attribution and gives credit to the original authors of the code, adding the associated copyright notices and license terms in the process…Biderman says is technologically feasible.” Is it really feasible? What does “traces attribution” even mean here? It’s not emitting “code”, it’s emitting individual tokens that each were found throughout the input corpus. The “code” is…

This quote seems to fundamentally misunderstand what transformers are doing at all. Technically I suppose you could save all gradient updates from every input token, and do some weighted averaging to show what inputs affected the particular output the most, but saving all those gradient updates would be unimaginably space consuming. "Feasible" is doing a lot of work there. It's very hard for people to get away from t…

Even then, the presence of a next token is just as informative as the absence of another during training. That information also gets backpropagated. And during inference, good luck identifying which weights were responsible for a given next token (assuming we’re using greedy decoding, don’t even get started on beam search) let alone which samples contributed to that weight (hint: they all did).

Re: Ownership of AI-Generated Code Hotly Disputed

#182
post #3

Earlier quoted context omitted.

[flagged]

There used to be a concept called public domain. The purpose of copyright was to make increase the public domain. What's your point?

My point is that there is socioeconomic theories which were based on the goal of common ownership of all means of production (which in a digital society would often translate to code). I guess all movements that have tried to transition to such societies have failed (thus my comment: they are alternatives, the trick is to make them working). While public domain is (except maybe for government agency) is a model you chose, this is completely different. If we are talking about alternatives to ownership we cannot do this without thinking in political dimensions.

Re: Ownership of AI-Generated Code Hotly Disputed

#183
post #111

I think it’s silly to pretend that human programmers are emitting a lot of code with a high degree of originality either. We’re all remixing some long-forgotten influential code laying deep in latent memory just like the models.

Humans do remix stuff when we create, and copyright draws a kind of arbitrary line around when that becomes original and when it becomes derivative, mostly because if it didn't then it would be impossible for us to get new books, movies, and songs.

All copyright is a hack; it's not an ideological, internally consistent framework. It is a set of fallible legal rules we invented so that people would get paid for creating things we care about. That doesn't mean that comparisons aren't useful or that we can't extrapolate from the existing rules, but even where fair use is concerned, the actual justification isn't a logical one, it's: "if we didn't have this standard nobody would make anything." So the boundaries around fair use and what things fall into it are not being created purely based on logic or first principles.

The reason why we have copyright is because we want people to be paid for making creative work. The reason we have fair use and a standard of "originality" that treats coders/artists learning from other artists as acceptable is because if we didn't, the entire system would fall apart and nobody would be able to make new creative works.

Everything in copyright exists purely to get people to make more stuff in a sustainable way. It's an outcome-driven process.

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More recently, there are a lot of people who argue that IP is a real, fundamental property right, but frankly, IP doesn't stand up at all if you think about it too hard. The justifications for why IP theft is theft can't be consistently generalized in a way that applies outside of the IP space. The standards for what does and doesn't count as creative aren't really consistent or based on a straightforward definition of creativity.

A lot of people would love to say that IP rights are just property rights, but... it's not all that convincing, and the history of copyright doesn't really indicate to me that the people building the laws thought of them that way.

And again, that doesn't mean that there's no consistency in copyright rules or that copyright rulings don't have implications beyond the original rulings. But it is almost always easier to think about copyright and almost always easier to understand why copyright laws are the way that they are if you approach copyright as a means to an end, and understand the existing laws not as an attempt to create an internally consistent system, but as a series of attempts throughout US history to achieve a consistent publicly beneficial outcome.

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With that in mind, I suspect whether or not AI works count as remixing is largely going to be decided based on commercial interests, individual judges, and individual juries, possibly with input from US legislature.

"Everybody remixes" historically hasn't been the most useful argument during these debates? So I don't know how it's going to play out this time around. I vaguely suspect it's going to come down to whether or not individual pieces are recognizable? That's how we got wild copyright laws about some individual chord progressions being treated as derivative works in songs.

Re: Ownership of AI-Generated Code Hotly Disputed

#184
post #133

Earlier quoted context omitted.

I have never seen an ML researcher claim that understanding the effect of specific training inputs on outputs is straightforward given the size of these LLMs. Most view it as a very difficult if not impossible problem.

And yet it's a major part of the overall concept of being responsible with our use of AIs. Throwing our hands up in the air and prematurely declaring defeat is not an option long term. It's a non-starter for no other reason than potential copyright infringement means the government becomes involved, and they will stomp on the AI mouse with the force of an elephant - the opinions of amateurs and the anti-copyright mov…

Observability is great but it doesn’t give granular enough insights into what is actually happening.

Given a black box you can do two things: watch the black box for a while to see what it does, or take it apart to see how it works.

Observability is the former. Useful in many cases, just not here.

If you want to know what LLMs are actually doing, you’ll need the latter. Looking at weight activations for example, although with billions of parameters that’s infeasible.

Re: Ownership of AI-Generated Code Hotly Disputed

#185

I would have thought that in the vast majority of current AI-generated code we are talking about single blocks and functions that are just Intellisense on steroids that only a rather self-deluding coder would consider original enough or "theirs" to attribute authorship to. There are no doubt grey areas and more serious cases as the technology improves and the generated content increases in length and functional value…

I can only speak to my experience using ChatGPT. But it’s doing a lot more than copying and pasting code snippets it finds on the internet. It actually is translating English to code. I had a “DevOps” project I was working on creating deployment process using AWS technologies (disclaimer: where I work in Professional Services). I needed a few relatively simple Python scripts. I first asked ChatGPT: “given a JSON file…

I understand what it is doing, and how impressive it is; the question is whether or not the normal use case is for stuff that requires the originality of thought that requires attribution, and I can't see that being the case except in a very small minority of instances.

Re: Ownership of AI-Generated Code Hotly Disputed

#186
post #6

https://en.m.wikipedia.org/wiki/Information_wants_to_be_free

I propose that information naturally wants to degrade. Paper decomposes. Bits flip. File formats are replaced and lost. Storage mediums degrade. It's all an extension of the universe trending towards entropy. It actually takes quite a bit of effort to store, then distribute information precisely and broadly. There's a lot of infrastructure, effort, and money involved, and still information degrades and disappears ove…

That's why it wants to be free. To survive by being copied and adapt by being freely built upon.

Re: Ownership of AI-Generated Code Hotly Disputed

#187
post #55

Earlier quoted context omitted.

That “presumably” is exactly what I’m trying to get past. How would it actually work? Once the input corpus has been chewed up and reduced to tokens, is there actually a representation of “the similar string in the corpus” any more? I don’t think people are even clear on the problem statement here. If I fed in three very similar functions from different sources, and I got a fourth, also very similar, output, what is…

There's a clear difference between an output string that matches 10's of tokens from training data and one that is synthesized from the statistical regularities of the training corpus as a whole and so will not match any input data past a few highly informative tokens (ie ignoring structural tokens). The computational dynamic of doing synthesis should be noticeably different from doing verbatim copying. For one, the…

I see, so the hypothesis is there's some way of determining "how much choice" it has for each output token. The less choice it has, the more we will call what it's doing "verbatim copying". Once the threshold is crossed and you want to "trace" it, though, I'm still not clear on how you can map back through the latent space and figure out where in the corpus it's copying from. Other than the technique suggested upthread, where you just literally search the corpus as a separate operation.

Re: Ownership of AI-Generated Code Hotly Disputed

#188
post #106

Earlier quoted context omitted.

That sounds exactly right to me, or at least this is one specific way to implement a solution to the problem. Good question on size. Speculating… I would guess the size of the index relates not to the size of the model, but to the size of the training data. If you built an extremely naive and straightforward uncompressed index like this, you could imagine building the complete list of known tokens, and for each one t…

I think you'd find that most code matches (some) other existing code. Some code, like the famous fast inverse square root, is widely shared. Even trivial code is often just copy-pasted from a popular SO answer. Other code is driven by something like convergent evolution. It ends up similar to other code because of the limits of well known algorithms, language syntax, APIs, boilerplate, common coding styles, etc. In o…

If true, how do you think these things should reflect on copyright or AI policies? Does it matter whether “most” human written code meets the same standard that we have for AI, and if so, why?

It’s hard to discuss unverifiable claims of “most” code. A lot of code, maybe most, or maybe not, is proprietary and kept within corporate walls, so we have no idea how much is or is not copied. SO answers are allowed to be copied, by definition. (And at least with SO answers, the code is publicly accessible, and attribution tracking after the fact is closer to possible, right?)

You do have a good point that attribution for some code could be practically impossible to track. This might get a lot worse if we allow AI to remix and republish it, that could even cause feedback loops if we’re not more careful about tracking attributions.

Re: Ownership of AI-Generated Code Hotly Disputed

#189

Earlier quoted context omitted.

What kind of platform can detect what variables or instructions I added? It can be very difficult to reverse engineer the prompt from the output.

That's not the problem though. The onus would be on you to prove that your machine generated the output and that it wasn't based on the training data but just on your input. Otherwise the generated work isn't yours.

That's the moral aspect of the problem. First thing that I am concerned is that the search engines will be flooded by the bots creating ai content and engines won't have a way to identify it.

Re: Ownership of AI-Generated Code Hotly Disputed

#190
post #188

Earlier quoted context omitted.

I think you'd find that most code matches (some) other existing code. Some code, like the famous fast inverse square root, is widely shared. Even trivial code is often just copy-pasted from a popular SO answer. Other code is driven by something like convergent evolution. It ends up similar to other code because of the limits of well known algorithms, language syntax, APIs, boilerplate, common coding styles, etc. In o…

If true, how do you think these things should reflect on copyright or AI policies? Does it matter whether “most” human written code meets the same standard that we have for AI, and if so, why? It’s hard to discuss unverifiable claims of “most” code. A lot of code, maybe most, or maybe not, is proprietary and kept within corporate walls, so we have no idea how much is or is not copied. SO answers are allowed to be cop…

Copyright requires an element of creativity and originality. The easiest code snippets for AI to reproduce are things like language syntax (loops, definitions, etc), implementations of common algorithms, and boilerplate, and an index would probably find a lot of matches for those, but are they original or creative?

So the challenge for an index would be finding a rare case of creative, important code in a sea of trivial matches.

Incidentally, answers on SO are licensed cc-by-sa, so it's easy to violate copyright when copying them; but no one seems to care, suggesting that small code snippets are indeed "trivial".

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