“AI sucks at X, but sometimes useful at Y… use with caution.” = astroturfing
“AI SUCKS AT LITERALLY EVERY TASK!!! ITS ALL SLOP!!! SLOP SLOP SLOPPITTY SLOP!!!” = only organic discussion and reasonable take…
Look, there are 100s of valid reasons why AI sucks and is unethical… in fact, it’s pretty much 100% built on unethical methods, no doubt…
But “AI sucks at everything and literally has zero good use cases” is not a real argument, but it seems to be the most popular opinion around here.
I disagree with 90% of the pro-AI stuff out there, i’m just pointing out that its rare to hear a reasonable discussin on the topic here that isnt just 100% hate
If AI actually adds value, it should be trivial to demonstrate that value-add in a way that passes scientific rigor.
The underlying problem is that we don’t have a good way to measure code value. Software quality is most closely coporable to a weird combination of scientific paper, mechanical diagnostic, and toy instructuon. And we don’t have good ways to measure those, either.
Note that the headline is misleading – stanford apparently trainded an AI model to “rate code” in a way that agreed with some of their staff and then ran that on a bunch of projects. The “good at simple and new, bad at complex and old” matches my intuition, but isn’t really a stronger test than counting minutes spent in a project or dollars spent on programming with or without AI.
And all AI output is slop. It’s just that for some things slop is good enough.
~Which really should be an argument more for discarding those things than boiling oceans to generate more of them, but capitalism loves doing wasteful things~
“AI IS AMAZING AND INEVITABLE!!!” = astroturfing
“AI sucks at X, but sometimes useful at Y… use with caution.” = astroturfing
“AI SUCKS AT LITERALLY EVERY TASK!!! ITS ALL SLOP!!! SLOP SLOP SLOPPITTY SLOP!!!” = only organic discussion and reasonable take…
Look, there are 100s of valid reasons why AI sucks and is unethical… in fact, it’s pretty much 100% built on unethical methods, no doubt…
But “AI sucks at everything and literally has zero good use cases” is not a real argument, but it seems to be the most popular opinion around here.
I disagree with 90% of the pro-AI stuff out there, i’m just pointing out that its rare to hear a reasonable discussin on the topic here that isnt just 100% hate
If AI actually adds value, it should be trivial to demonstrate that value-add in a way that passes scientific rigor.
The underlying problem is that we don’t have a good way to measure code value. Software quality is most closely coporable to a weird combination of scientific paper, mechanical diagnostic, and toy instructuon. And we don’t have good ways to measure those, either.
There was apparently one study from Stanford:
https://medium.com/@manusf08/does-ai-really-boost-developer-productivity-a-stanford-study-of-100-000-devs-has-answers-4f64c64ebe97
Note that the headline is misleading – stanford apparently trainded an AI model to “rate code” in a way that agreed with some of their staff and then ran that on a bunch of projects. The “good at simple and new, bad at complex and old” matches my intuition, but isn’t really a stronger test than counting minutes spent in a project or dollars spent on programming with or without AI.
And all AI output is slop. It’s just that for some things slop is good enough.
~Which really should be an argument more for discarding those things than boiling oceans to generate more of them, but capitalism loves doing wasteful things~