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AI tooling must be disclosed for contributions

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Re: AI tooling must be disclosed for contributions

#311

Post by zahlman »

BobbyTables2 wrote: post #290
ineedasername wrote: post #72

Earlier quoted context omitted.

Courts (at least in the US) have already ruled that use of ingested data for training is transformative. There’s lots of details to figure, but the genie is out of the bottle. Sure it’s a big hill to climb in rethinking IP laws to align with a societal desire that generating IP continue to be a viable economic work product, but that is what’s necessary.

I’m curious … So “transformative” is not necessarily “derivative”? Seems to me the training of AI is not radically different than compression algorithms building up a dictionary and compressing data. Yet nobody calls JPEG compression “transformative”. Could one do lossy compression over billions of copyrighted images to “train” a dictionary?

> I’m curious … So “transformative” is not necessarily “derivative”?

(not legal advice)

Transformative works are necessarily derivative, but that transformation allows for a legal claim to "fair use" regardless of making a derived work.

https://en.wikipedia.org/wiki/Transformative_use

Re: AI tooling must be disclosed for contributions

#312

Post by inferiorhuman »

blurbleblurble wrote: post #205
inferiorhuman wrote: post #203

Earlier quoted context omitted.

but maybe those don't need to be about "whether or not you used LLMs" and might have more to do with "how well you understand the code you are opening a PR for" (or are reviewing, for that matter) AI is a great proxy for how much someone has. If you're writing a PR you're demonstrating some manner of understanding. If you're submitting AI slop you're not.

I've worked with 10x developers who committed a lot of features and a lot of bugs, and who got lots of accolades for all their green squares. They did not use LLM dev tools because those didn't exist then. If they had used AI, their PRs might have been more understandable / less buggy, and ultimately I would have preferred that.

  If they had used AI, their PRs might have been more understandable / less buggy, and ultimately I would have preferred that.
Sure, and if they had used AI pigs could depart my rectum on a Part 121 flight. One has absolutely nothing to do with the other. Submitting AI slop does not demonstrate any knowledge of the code in question even if you do understand the code.

To address your claim about AI slop improving the output of these mythical 10x coders: doubtful. LLMs can only approximate meaningful output if they've already indexed the solution. If your vaunted 10x coders are working on already solved problems you're likely wasting their time. If they're working on something novel LLMs are of little use. For instance: I've had the pleasure of working with a notoriously poorly documented crate that's also got a reputation for frequently making breaking changes. I used DDG and Google to see if I could track down someone with a similar use case. If I forgot to append "-ai" to the query I'd get back absolutely asinine results typically along the line of "here's an answer with rust and one of the words in your query". At best first sentence would explain something entirely unrelated about the crate.

Potentially LLMs could be improved by ingesting more and more data, but that's an arms race they're destined to lose. People are already turning to Cloudflare and Anubis en masse to avoid being billed for training LLMs. If Altman and co. had to pay market rate for their training data nobody could afford to use these AI doodads.

Re: AI tooling must be disclosed for contributions

#313

Post by mhh__ »

neilv wrote: post #26

There is also IP taint when using "AI". We're just pretending that there's not. If someone came to you and said "good news: I memorized the code of all the open source projects in this space, and can regurgitate it on command", you would be smart to ban them from working on code at your company. But with "AI", we make up a bunch of rationalizations. ("I'm doing AI agentic generative AI workflow boilerplate 10x gettin…

That's not really how LLMs are used, unless we're planning on classing gitignores as IP

LLMs are interesting because they can combine things they learn from multiple projects into a new language that doesn't feature in any of them, and pick up details from your request.

Unless you're schizophrenic enough to insist that you never even see other code it's just not a realistic problem

Honestly I've had big arguments about this IP stuff before and unless you actually have a lawyer specifically go after something or very obviously violate the GPL it's just a tactic for people to slow people they don't like down. People find a way to invent HR departments fractally.

Re: AI tooling must be disclosed for contributions

#314

Post by GCUMstlyHarmls »

j4coh wrote: post #305
raggi wrote: post #294

Earlier quoted context omitted.

For a large LLM I think the science in the end will demonstrate that verbatim reproduction is not coming from verbatim recording, as the structure really isn’t setup that way in the models under question here. This is similar to the ruling by Alsup in the Anthropic books case that the training is “exceedingly transformative”. I would expect a reinterpretation or disagreement on this front from another case to be both…

So if you can get an LLM to produce music lyrics, for example, or sections from a book, those would be considered novel works given the encoding as well?

Depends if the music is represented by the RIAA or not :)

Re: AI tooling must be disclosed for contributions

#315

Post by jrvarela56 »

This seems misguided. The human submitter is accountable for the code submitted. Doesn’t matter if the AI built it, a contractor in another timezone, or ten thousand monkeys typing away.

Github provides a profile but it’s not meant to make this kind of assessment. Basically a trust badge/metrics of some sort you could check before engaging with someone’s PR.

Re: AI tooling must be disclosed for contributions

#316

Post by mhh__ »

philjohn wrote: post #54

I like the pattern of including each prompt used to make a given PR, yes, I know that LLM's aren't deterministic, but it also gives context of the steps required to get to the end state.

Doesn't work. People will include fake prompts, the real ones are way too personal. You can learn a lot from how people use these tools.

Re: AI tooling must be disclosed for contributions

#317

Post by inferiorhuman »

Filligree wrote: post #209
bsder wrote: post #171

Earlier quoted context omitted.

> Courts (at least in the US) have already ruled that use of ingested data for training is transformative. If you have code that happens to be identical to some else's code or implements someone's proprietary algorithm, you're going to lose in court even if you claim an "AI" gave it to you. AI is training on private Github repos and coughing them up. I've had it regurgitate a very well written piece of code to do a p…

How is that obviously proprietary? Aren't you implicitly assuming that the AI couldn't have written it on its own?

The idea that something that can't handle simple algorithms (e.g. counting the number of times a letter occurs in a word) could magically churn out far more advanced algorithms complete with tests is… well it's a bit of a stretch.

Re: AI tooling must be disclosed for contributions

#318

Post by potsandpans »

hombre_fatal wrote: post #310

I see two things here. 1. The world has fundamentally changed due to LLMs. You don't know where a code submission falls between "written thoroughly with eternal vigilance" vs "completely vibe-coded" since it's now trivially to generate the later. There's no going back. And a lot of comments here seem stuck on this point. 2. The maintainer naively or stubbornly imagines that he can get everyone to pre-sort their code…

In a nondismissive way, I see things like this (the gh issue) as part of the reactionary movement / counter culture of our time.

People want to feel agency and will react to mainstream pressures. And make up whatever excuses along the way to justify what theyre feeling.

Re: AI tooling must be disclosed for contributions

#319

Post by kentm »

geodel wrote: post #295
ToucanLoucan wrote: post #111

Earlier quoted context omitted.

Of all the things I would absolutely not trust the stock market to evaluate, "technical competence" is either near or at the top. The people deciding how much OpenAI is worth would probably struggle to run first-time setup on an iPad.

I agree. Seems like people took my comment above as my opinion. It was supposed to be argument of Linkedin type AI hype generators.

It seemed like a normative statement, to be honest, so I misunderstood your point.

Re: AI tooling must be disclosed for contributions

#320

Post by blurbleblurble »

sho_hn wrote: post #287
blurbleblurble wrote: post #240

Earlier quoted context omitted.

Can't tell if you're responding in earnest or not here? LLMs are trained to be steerable at inference time via context/prompting. Fine tuning is also possible and often used. Both count as "feedback" in my book, and my point is that both can be effective at "changing the LLM" in terms of its behavior at inference time.

And also clearly not what the OP means, who was trying to make a point that tuning the prompt to an otherwise stateless LLM inference job is nothing at all like teaching a human being. Mechanically, computationally, morally or emotionally. For example, humans aren't just tools; giving feedback to LLMs does little to further their agency.

The false equivalence I pointed at earlier was "LLM code => no human on the other side".

The person driving the LLM is a teachable human who can learn what's what's going on and learn to improve the code. It's simply not true that there's no person on the other side of the PR.

The idea that we should be comparing "teaching a human" to "teaching an LLM" is yet another instance of this false equivalence.

It's not inherently pointless to provide feedback on a PR with code written using an LLM, that feedback goes to the person using the LLM tools.

People are swallowing this b.s. marketing mystification of "LLMs as non human entities". But really they're fancy compilers that we have a lot to learn about.

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