I believe it was under British rule, they offered a reward for people bringing in dead cobras as proof of culling. Which worked until people started breeding them just to get the reward. Humans gamed the system and it made the problem worse.
I believe it was under British rule, they offered a reward for people bringing in dead cobras as proof of culling. Which worked until people started breeding them just to get the reward. Humans gamed the system and it made the problem worse.
The same oversight mechanism that applies to humans cannot correct the flaws of AI agents? What do you think is the catch?
I am not saying things are clearly defined in most settings. But my accounting agent ( real person) gets paid only when he files my tax returns.
If you finetune a model and it starts misbehaving, what are you going to do to it exactly? PIP it? Fire it? Of course not. AIs cannot be managed the same ways as humans (and I would argue that's for the best). Best you can do is try using a different model, but you have no guarantee that whatever issue your model has is actually solved in the new one.
There's no LLM equivalent.
What is the point of an agent running and you don't trust it?
That would be equivalent to calling this whole AI wave useless. May be it is, maybe it is not.
Your accountant has to build in margin that you pay for for clients who stiff him on the bill or who he has to take to court to argue he did the service as described in the contract. If you didn't hold that threshold over his head, he would be able to charge less. Would he? Maybe not, I don't know the guy, but he could.
I think that is the core of the argument. It is the risk-sharing between buyer and seller. If sold on outcomes, seller carries all risk. If sold on work-put-in, buyer carries all risk.
Add to that, in some scenarios, outcomes themselves are fuzzy.
Yes exactly. Your second paragraph hits the nail on the head. And I'm sure you agree that the AI companies aren't going to take on more risk for free.