alt Hacker NewsTo me the key point was:
> One way of looking at this is that we rediscovered that bureaucracy matters. Although some might chafe against procedures and checklists, they exist for a reason: providing a kind of institutional memory that helps employees avoid common screwups at work.
That's why we want machines in our systems - to eliminate human errors. That's why we implement strict verifiable processes - to minimize the risk of human errors when we need humans in the loop.
Having a machine making human errors is the exact opposite of what we want. How would we even fix this if the machines are trained on human input?
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I don’t think they really want to fix human errors with LLMs. Rather, they want a “human” who works 24x7 for dirt cheap
There’s no other input to train on
Humans are still the current best at doing everything humans want to do
The ultimate goal is to transfer all possible human behavior into machine behavior such that they can simulate and iterate improvements on it without the constraints of human biology
The fact that humans are bad to each other means that we’re going to functionally encode all the bad stuff also and so there is no solution to fixing it if the best data that we can get is poisoned.
Like everything it’s a problem with humans not machines
I generally agree with you, but am trying to see the world through the new AI lens. Having a machine make human errors isn't the end of the world, it just completely changes the class of problems that the machine should be deployed to. It definitely should not be used for things that need those strict verifiable processes. But it can be used for those processes where human errors are acceptable, since it will inevitably make those some classes of error...just without needing a human to do so.
Up until modern AI, problems typically fell into two disparate classes: things a machine can do, and things only a human can do. There's now this third fuzzy/brackish class in between that we're just beginning to explore.