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by democracy 62 days ago
tbh if the change works and the code is ok who cares what was used to build it? ChatGPT or C++ code generator. If the code looks crap - reject PR, why drama?
3 comments

Because to decide if it's crap, you still have to read it.And because AI respect coding guidelines, you have to actually understand what the code does to detect crap. Also the sheer number is unmanageable.
Oh no, reading the code, so before AI era noone was reading the code? Unless you have automated checks done by AI to red flag AI submissions... what else can you do? Ask 100 times not to submit AI code or click a checkbox or add this really serious terms and conditions paragraph?
Don't be daft, the issue is the number of PR having to be reviewed, not to have to review PRs.

I'll be even more truthful about what I felt this past few months: AI emboldened bad or inexperienced devs to push a huge amount of code, way more than what they were able to, and of higher quality that they used to produce. Still, if the overseer is bad, the code won't be great (LLM are inconsistent when it comes to code quality, sometimes they find nice tricks but don't generalize them, and you have to steer them or to modify the code yourself, and sometimes they take baffling decisions, especially when the code is OOP heavy).

Those devs use to be way less visible (and I'm not saying only in the open source world, in enterprise it was the same), or grew out of their inexperience. Nowadays they produce a lot of code, often good enough, sometimes very dumb, but almost never of the quality you want to find in open source, and they are _very_ tiring to speak to because they do not understand what they have produced, and don't seem to understand plain English.

Don't get me wrong: I like the tool. It improved my life in a lot of ways, the main way it did was cure my imposter syndrome by making those less visible developers more visible. I like the fact that this tier of developers exists, especially in the corporate world. Still I think a way to filter their contribution to avoid reviewers burning out,at least for now, is necessary.

And the solution is...?
In the Monkey Selfie case - https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput... - courts decided that copyright requires a human author and a human merely setting the conditions for a copyrighted work to appear is not enough.

This reasonably means AI contributions where a human has guided the AI are not subject to copyright, and thus can't be supported by a project's license.

That's quite a stretch, and untested in court.

At least a monkey is an unambiguous autonomous entity. A LLM is a - heck of a complicated - piece of software, and could very well be ruled a tool like any other

Tested all the way up to the Supreme Court, who declined to hear an appeal, so the precedent stands in the context of AI output.

https://www.reuters.com/legal/government/us-supreme-court-de...

It's still early, but this is absolutely going to be precedent used in a software related case, and it's going to lead to fun times with SOX/PCI style compliance issues, where developers will have to attest that merges did not use AI so compliance can ensure repos don't pass a threshold where there's too much LLM code.

I mean, aren't we all bragging about autonomous agents doing the coding for us? I don't see how that's remotely a stretch.

The legal question was "did a human author the work"?

From a less self-centered viewpoint there are plenty of reasons to be critical of LLMs and their use.