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Ownership of AI-Generated Code Hotly Disputed

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Re: Ownership of AI-Generated Code Hotly Disputed

#131

Post by jacquesm »

remus wrote: post #124
jacquesm wrote: post #61

To me AI code generators are the equivalent of crypto tumblers or mixers for digital coins. You can pretend all you want that the output is 'clean' but we all know it came from somewhere else and wasn't actually generated by the software, just endless little snippets that other people made.

I don't think that's entirely true. When I've tested codepilot it also knows something about the context in which it's working, so it can use relevant variable names in it's suggestions. To me that's a step beyond rote regurgitation of other code.

That may be so, but the process is automated and copyright law has something to say about mechanical transformation.

As an example: if I take a piece of code you wrote and substitute all of the identifiers that does not create an original work.

Re: Ownership of AI-Generated Code Hotly Disputed

#132

Post by system2 »

jacquesm wrote: post #61

To me AI code generators are the equivalent of crypto tumblers or mixers for digital coins. You can pretend all you want that the output is 'clean' but we all know it came from somewhere else and wasn't actually generated by the software, just endless little snippets that other people made.

ChatGPT output is very clean and precise especially when variables provided in detail. I doubt you can trace it back if you make the prompt very elaborate.

Re: Ownership of AI-Generated Code Hotly Disputed

#133

Post by Rekksu »

falcolas wrote: post #91
visarga wrote: post #81

Earlier quoted context omitted.

I think harder, as it is spammed around in all directions. It's easier to attribute a unique piece of code that appears in a single repo. But boilerplate functions don't deserve copyright protection as they are not creative. Can I copyright print('hello world!') if I post it in my repo? Do I deserve a citation from now on?

For better or worse, AI is a combination of machine learning algorithms. And these algorithms are black boxes solely because we don't add observability to them - we aren't looking. But there is a desire to understand why an AI provided the output it did (to increase trust in AI generated output), and so there's a lot of study and work going into adding that observability. Once that's in place, it becomes pretty strai…

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.

Re: Ownership of AI-Generated Code Hotly Disputed

#134

Post by amelius »

ProlificInquiry wrote: post #109
wrs wrote: 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…

> The reality is, to get the exact artifact which produced the code in question, you need "Call me Ishmael" from Moby Dick just as much as the Linux kernel source.

Not always. Sometimes it just copies code without modification.

It never tells you when it does that, though. So to be on the safe side, better assume that it always does.

Re: Ownership of AI-Generated Code Hotly Disputed

#135

Post by logicallee »

Filligree wrote: post #26
wrs wrote: 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…

It sounds like nonsense. The most plausible solution would be to provide credit to every single author whose code was used in the original training set; of course, that would run into gigabytes just for the credits.

But GPL requires the resulting derivative code to be open-sourced under GPL, not just attributed. So if you did that then copilot could only emit code under a GPL license. Maybe that is okay, but it is not what copilot is trying to do at the moment. (And not everyone wants to open-source all their code under GPL.)

Re: Ownership of AI-Generated Code Hotly Disputed

#136

Post by johnfn »

dahart wrote: post #54
wrs wrote: 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…

Why wouldn’t it be feasible? (Maybe this depends on what you mean by ‘feasible’.) There’s no technical reason you can’t back-track the weights and make a list of which tokens from which training data were sampled. The list might be long, it could be impractical, but that has little bearing on whether it’s technically possible, right? The problem here happens when the same source is sampled for many tokens in a row be…

The failure mode I see here, which seems quite likely, is that attribution would almost always list tens of thousands of source files, or more. They doesn’t seem particularly useful or meaningful.

Re: Ownership of AI-Generated Code Hotly Disputed

#137

Post by tester457 »

odessacubbage wrote: post #129
oehpr wrote: post #73

Earlier quoted context omitted.

>A closer parallel would be the industrialisation of painting duplication But they directly reproduce the source material. AI art they clearly does not. The luddites seem a better parallel when it comes to scale. Where a machine comes along capable of producing in much higher quantities and in much greater efficiencies. Or perhaps photography? Also a fear of scale. For a long time photographers were not considered ar…

photography is actually a very good example of how this talking point breaks down. there are a great deal of laws and social codes around where you can and cannot film and take photographs. photography is explicitly disallowed in most museums and art galleries. filming in public requires permits and waivers in many places, especially if the filming is done with a commercial interest. 'but how is capturing an image wi…

I had the same thoughts.

Finally, someone has put into words the logical end of the trite photography analogy.

It's a refreshingly sane perspective to see in this thread.

Re: Ownership of AI-Generated Code Hotly Disputed

#138

Post by scarface74 »

mellosouls wrote: post #12

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 like this [{“company”:”${company}”} replace the word surrounded by ${} with the equivalent environment variables using Python”.

It worked perfectly. But it hardcoded the input file.

“Modify the script to accept the input file using a command line argument -json-file using argparse”

That worked and used the “required=true” parameter.

“Instead of skipping replacement if an environment variable is not found, raise an exception”.

And it seems to understand the AWS SDK. I told it to convert a script I wrote to a CloudFormation custom resource using the cfnresponse module and it knew the correct Lambda event structure, the event format etc.

I have seen reports and have witnessed it making up functions occasionally.

But, I believe with the right prompts, it should be able to create simple CRUD scripts.

Re: Ownership of AI-Generated Code Hotly Disputed

#139

Post by inkcapmushroom »

oehpr wrote: post #73
dbspin wrote: post #40

Earlier quoted context omitted.

In a word scale. Scale matters. How is one locust different to a million? How is hand copying a manuscript (highly controlled in medieval Europe) different to a printing press. These models will and are already having a profound economic impact on the creative sectors they mimic. Whether existing law applies is a specialist question. But they're not remotely comparable from a pragmatic perspective with pieces manuall…

>A closer parallel would be the industrialisation of painting duplication But they directly reproduce the source material. AI art they clearly does not. The luddites seem a better parallel when it comes to scale. Where a machine comes along capable of producing in much higher quantities and in much greater efficiencies. Or perhaps photography? Also a fear of scale. For a long time photographers were not considered ar…

>AI art they clearly does not.

https://twitter.com/kortizart/status/1588915427018559490

I would think these are close enough that any human that produced that output could be claimed to have plagiarized.

Re: Ownership of AI-Generated Code Hotly Disputed

#140

Post by falcolas »

Rekksu wrote: post #133
falcolas wrote: post #91

Earlier quoted context omitted.

For better or worse, AI is a combination of machine learning algorithms. And these algorithms are black boxes solely because we don't add observability to them - we aren't looking. But there is a desire to understand why an AI provided the output it did (to increase trust in AI generated output), and so there's a lot of study and work going into adding that observability. Once that's in place, it becomes pretty strai…

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 movement notwithstanding.

As such, AI Observability is a problem that's both under active research, and the basis for B2B companies.

https://censius.ai/wiki/ai-observability

https://towardsdatascience.com/what-is-ml-observability-29e8...

https://whylabs.ai/observability

https://arize.com/

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