Replying to an earlier post

Torvalds was careful to frame this as a correction of language rather than a rejection of the technology itself.

Ok…

A maintainer burden few are talking about

Alongside the productivity gains, Torvalds described a less-discussed cost: a rising flood of low-effort, AI-generated bug and vulnerability reports hitting open source projects, including the kernel’s own security channels. He said it has become common for someone to run an AI tool against a codebase, file a report flagging a “possible” issue, and then vanish when a maintainer follows up asking for more detail or a fix.

Everyone is talking about that and it is surprising to me that he doesn’t recognize that as two side of the same coin. Why are you rejecting the low-effort, Ai generated bug reports, Linus, isn’t AI just a productivity tool? What’s wrong? Is it not being productive?

I say “surprising”, it’s not that surprising. It’s a “guns don’t kill people, people kill people” attitude. It’s willfully excluding the impact that technology has on people, and framing the outcome as coming purely from people and the existence of the technology not affecting the outcome.

Replying to an earlier post

Why are you rejecting the low-effort, Ai generated bug reports, Linus, isn’t AI just a productivity tool?

Because they are low effort. Good software engineering is never low effort, whether you use AI or not.

If you let AI replace people, and let them mess with software or report issues without understanding what’s going on, without putting in the effort to understand what’s going on, you’re not adding any value; just noise.

But if you use AI to find issues, then investigate the issue, reproduce it, document it, etc, then you’ve got something meaningful that someone can do something with.

Replying to an earlier post

But if you use AI to find issues, then investigate the issue, reproduce it, document it, etc, then you’ve got something meaningful that someone can do something with.

In principle that is sound, but LLMs can’t do that, yet, if ever. Sounds like anthropomorphism. The ‘hallucination’ thing is intrinsic. What you can do is point it at easily verifiable problems like searching for security flaws, and then verify them. Whether that’s cost effective in wasted energy and human time is still an open question, especially as token cost ramps up pre IPO.