On the other side of the equation I've been spending much more time on code-review on an open source project I maintain, because developers are much more productive and I still code-review at the same speed.
The real issue is that I can't trust the AI generated code, or trust the AI to code-review for me. Some repeated issues I see:
- In my experience the AI doesn't integrate well with the code that there is already there: it often rewrites functionality and tend not to adhere to the project's conventions, but rather use what it is trained on.
- The AI often lacks depth into more complex issues. And because it doesn't see the broader implication of changes, it often doesn't write the tests that would cover them. Developers that wrote the PRs accept the AI tests without much investigation into the code-base. Since the changes passes the (also insufficient) tests, they send the PR to code-review.
- With AI I think (?) I'm more often the one careful deep diving into the project and re-designing the generated code in the code-review. In a way it's an indirect re-prompting.
I'm very happy with the increased PRs: they push the project forward, with great ideas of what to implement, and I'm very happy about AI increased productivity. Also, with AI developers are bolder in their contributions.
But this doesn't scale -- or I'll spend all my time code-reviewing :) I hope the AIs get better quickly.
imho that is just silly ... I can see various ways censorship and freedom and common good at the same time. Actually, I can imagine different set ups where this could work...
But then, you have to define these things. E.g.: freedom of person "A" to kill person "B" infringes on person "B" freedom of come and go and not be killed (by "A" or anyone else) ... so what is freedom. "Common good" is even more complicated ... who should defined it ? And how ?
On the other topic, I for one think that censorship of AI generated content and fake news, as well as AI generated ordering of results should be censored. But it's not that easy, and implementing that is an even bigger can of worms.
Of course one can generalize using the colloquial "Here in Europe". And generalization is useful -- one cannot go into all the complexity and details all the time, at some point one has to summarize/generalize an argument.
Yes, Europe is not a monolithic bloc, but there is a large fraction that is less sex focused, it's a fair generalization and comment to express that.
The real issue is that I can't trust the AI generated code, or trust the AI to code-review for me. Some repeated issues I see:
- In my experience the AI doesn't integrate well with the code that there is already there: it often rewrites functionality and tend not to adhere to the project's conventions, but rather use what it is trained on.
- The AI often lacks depth into more complex issues. And because it doesn't see the broader implication of changes, it often doesn't write the tests that would cover them. Developers that wrote the PRs accept the AI tests without much investigation into the code-base. Since the changes passes the (also insufficient) tests, they send the PR to code-review.
- With AI I think (?) I'm more often the one careful deep diving into the project and re-designing the generated code in the code-review. In a way it's an indirect re-prompting.
I'm very happy with the increased PRs: they push the project forward, with great ideas of what to implement, and I'm very happy about AI increased productivity. Also, with AI developers are bolder in their contributions.
But this doesn't scale -- or I'll spend all my time code-reviewing :) I hope the AIs get better quickly.