> We must take the same attitude in computing: use abstractions, refactor, refine scope, invent and adopt higher-level languages, until we can hold the code in our head.
I want to believe this is true. But as an counterexample, do we need to hold machine code or assembly, generated from our C or Golang programs, in our heads? Or rather the Golang code is a high-level abstraction which is good enough?
If that's the case, does it mean we should go even further and treat design docs as the code suitable to hold in head and treat Golang program as a derivative? Or maybe design docs are also too low-level and the general vibe "create me an app, make no mistakes" is actually enough?
What's the right abstraction level? How to find it?
I agree there is a spectrum, but we at least have to be honest with ourselves: are we really sure AI generated code is following the spec? On the other hand, with progress in proof automation, it is now feasible to formally verify AI generated code, and that allows us to specify program behavior formally, and a formal specification is again a program in itself.
I'm not sure the comparison with Hilbert's dictum holds up in our field. Yes, Godel made a mockery of it, and mathematics is now known to be limited by incompleteness, but only at the theoretical horizon. Working mathematicians will not run into it as a problem that blocks their work in other areas.
In computing, though, the halting problem hoses us every time we have to hit ctrl-c to break an accidental infinite loop. Our tools can't always flag those situations ahead of time, so we often have to find them the hard way.
It seems clear that in software development, the specification is the program. To the extent there's something that the spec doesn't cover, that's a bug in the spec, not in the AI that turns the spec into code. Just as you wouldn't blame a compiler for your infinite loop, we will eventually reach the point where blaming a clanker for generating imperfect high-level code sounds just as bogus.
"Build me a Super Mario Bros. clone, make no mistakes" is the new hello_world.c. For anything innovative -- anything with commercial value -- the spec will have to be a lot more elaborate. There are plenty of specs that are already too complex for any one person to hold in their head, except perhaps for a few godlike prodigies. Look at the MPEG-4 document collection, or for that matter our tax and legal systems. I think the lesson is that language alone can't save us from complexity, any more than a better set of axioms can save us from incompleteness.
This is a indeed an important reminder that there is still progress to be made in the realm of software development. By raising the bar of abstractions, perhaps by guiding agents toward them, we might be able to follow along better. It is too tempting to take allow the growing capabilities of ai to lower the standards on software developmenbt.
Unfortunately it's very easy (and tempting) to get lost in the sauce, we as a society gave up our heads to social media and look where it got us. I'm afraid we're going the same route with software development and computer science.
> We must take the same attitude in computing: use abstractions, refactor, refine scope, invent and adopt higher-level languages, until we can hold the code in our head.
I want to believe this is true. But as an counterexample, do we need to hold machine code or assembly, generated from our C or Golang programs, in our heads? Or rather the Golang code is a high-level abstraction which is good enough?
If that's the case, does it mean we should go even further and treat design docs as the code suitable to hold in head and treat Golang program as a derivative? Or maybe design docs are also too low-level and the general vibe "create me an app, make no mistakes" is actually enough?
What's the right abstraction level? How to find it?
I agree there is a spectrum, but we at least have to be honest with ourselves: are we really sure AI generated code is following the spec? On the other hand, with progress in proof automation, it is now feasible to formally verify AI generated code, and that allows us to specify program behavior formally, and a formal specification is again a program in itself.
I'm not sure the comparison with Hilbert's dictum holds up in our field. Yes, Godel made a mockery of it, and mathematics is now known to be limited by incompleteness, but only at the theoretical horizon. Working mathematicians will not run into it as a problem that blocks their work in other areas.
In computing, though, the halting problem hoses us every time we have to hit ctrl-c to break an accidental infinite loop. Our tools can't always flag those situations ahead of time, so we often have to find them the hard way.
It seems clear that in software development, the specification is the program. To the extent there's something that the spec doesn't cover, that's a bug in the spec, not in the AI that turns the spec into code. Just as you wouldn't blame a compiler for your infinite loop, we will eventually reach the point where blaming a clanker for generating imperfect high-level code sounds just as bogus.
"Build me a Super Mario Bros. clone, make no mistakes" is the new hello_world.c. For anything innovative -- anything with commercial value -- the spec will have to be a lot more elaborate. There are plenty of specs that are already too complex for any one person to hold in their head, except perhaps for a few godlike prodigies. Look at the MPEG-4 document collection, or for that matter our tax and legal systems. I think the lesson is that language alone can't save us from complexity, any more than a better set of axioms can save us from incompleteness.
This is a indeed an important reminder that there is still progress to be made in the realm of software development. By raising the bar of abstractions, perhaps by guiding agents toward them, we might be able to follow along better. It is too tempting to take allow the growing capabilities of ai to lower the standards on software developmenbt.
Unfortunately it's very easy (and tempting) to get lost in the sauce, we as a society gave up our heads to social media and look where it got us. I'm afraid we're going the same route with software development and computer science.