Comment by Scubabear68
7 hours ago
"Contrast that with a knowledge worker that's more of an artisan in this analogy. For them they aren't running a factory but instead watching a robot do the work they used to do while they sit idle and watch it".
I think your general thesis about how AI is used of agents vs. the general chat interface is true, but not the rest.
Your knowledge worker example is where people fail when using AI, and it is usually very obvious.
Knowledge workers who know what they're doing recognized very quickly that AI often goes down very bad rabbit holes, often cites incorrect sources, makes up sources, or will use a random Facebook source or Reddit post as an authority on some topic. In legal circles you have to fight it to understand what venue(s) apply and to get it to stick to the right ones, in medical research it will sometimes pull in crackpot papers from left field and intermix them with well defined research.
People in the knowledge realm caught on very quickly that you have to use AI iteratively and constantly back check what you get and correct it. Let it run on its own and it will give you a legal theory based on some weird case in Kentucky that has no bearing to your issue with a court in Vermont.
This is not that much different in programming, it just takes longer to find out.
Using AI is like using adaptive cruise control: you're still in charge of where the vehicle will ultimately end up and if you decide to go take a nap you will wake up in the hospital or end up in the morgue.
It's true though that the 'time between interventions' is lengthening steadily.
>This is not that much different in programming, it just takes longer to find out.
The primary difference is that it's much easier for the AI to figure out itself if it's wrong on the programming side. Knowledge workers don't have automated testing for example.
The end result is the knowledge worker needs to be more heavily involved in the process and be more mindful of mistakes which makes it a worse experience for the user and generally less productive than it is for programmers.
That's true. And: as long as you don't hit production mistakes are cheap and quick to fix. Not so in many other fields.
It is more that knowledge workers are less sophisticated at using AI. It is not that hard to check whether sources are real, using AI or other tools, for example. Something like functional testing will come to non programming tasks.
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The major difference is that people routinely ship shoddy, broken products in the world of software with few consequences, beyond needing to patch it later. Try the same thing with a court filing and you’re out on your ass.
This was true before AI too.
In practice, lawyers generally don't ever disbarred except if they lie to clients or steal from them.
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We're still early in AI.
All of this will sort itself out and eventually bio, legal, software will all just work.
Don't hold onto any single assumption about the world. Things are going to be weird.
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"People in the knowledge realm caught on very quickly that you have to use AI iteratively and constantly back check what you get and correct it."
If lawyers and article writers are in the knowledge realm. Then your thesis has plenty of counter-examples of people who just use AI to create stuff and don't correct it.