But they should! The code is the best source of truth on what the software is doing after all.
Instead of giving up on that, we should make it easier to read generated code, e.g. by generating less code in a higher level language.
On the flip side, forcing myself to read all the code also resulted in a smaller, higher quality code base.
Zooming out (but only a little) from the impetus to formalize a commitment to a particular class of result candidate (what the author here is calling "spec elucidation"), we can also imagine this same evolution of concerns being applied in order to cause what we currently term "AI safety" into something more like "AI ethics".
For example, if we can elucidate the specifications for things like peace and justice to ensure that the class of results is formally verified as non-participation in war (or perhaps, further in the future, non-participation in state activities whatsoever), we may be able to throw cold water on all the vitriolic arguments about model capabilities and which need to be banned or delayed lest we accelerate the apocalypse (or whatever is actually on the mind of the ban-this-model constituency).
I like how the author ends tersely with:
> If you have a formal language with the closure properties above — we suspect you would be surprised how many do — we would very much like to hear from you.
That's certainly not me, but I bet it's true that it's somebody.
There are very few things that cannot be stated as dual use, with one totally benign and one totally screwed up. It's like wanting a hammer to distinguish if it's striking a nail for a roof vs. a nail for an illegal animal pen. That's the wrong application of constraints. The hammer shouldn't care.
> This is also why we do not believe PICK becomes less useful as models improve. Better models do not make user intent more articulate — asked for “a regex matching countries of North America”, a more capable model still cannot tell you whether you want the Caribbean included, or where you want to stop heading south. Better models produce better candidates, faster — which shifts user effort precisely toward the work PICK is built to support.
I am honestly heartbroken to live in a world where reading the code is seen as an unreasonable ask by either students or by professional working programmers.
I'm just upset that we are throwing away the original prompts for generated code in such a cavalier fashion.
An LLM prompt, even a huge one, is an incredibly vague document that leaves out most of the edge cases. And even Fable 5 happily ignores clear instructions in its prompt.
Now, to be fair, I absolutely expect the buggy slop to win, and to drive out the people that either write their own code or at least read the output. This will, in turn, make customers less willing to spend money on software after they get burnt a few times by buggy garbage. I think this is pretty much inevitable once Fable returns. It's just too damn good at long time horizon tasks, generating far more mostly sorta working code than any human could reasonably read.