[in-silico]

This post misses a very important point: humans aren't 100% correct either. This means that the bar for being useful (at tasks that humans usually do) isn't perfection, it's human-level correctness. If we can create AI models that make fewer mistakes than humans (which is almost certainly possible, even if not easily or soon), then we will actually need to spend less time double-checking for correctness than we do now.

> We see it with self-driving cars. It's really impressive what is possible. But they aren't true self-driving. A person needs to be sitting at the wheel, keeping their attention focussed on traffic as if they would be driving themselves, so they can intervene when the AI makes an inevitable mistake.

There are self-driving cars all over San Fransisco transporting people on public roads with no human at the wheel. This proves my point: those cars are not perfect, but they are human-level (or close), and that's all that's needed.

[sameers]

Not even "fewer mistakes than humans," just make the same mistakes but a lot faster and that's also good enough reason to keep it around (esp when you add parallelization) just from an efficiency/productivity point of view. There may still be other anti AI arguments, ofc.

[louwrentius]

All that output needs to be checked, thus why making mistakes faster doesn't seem valuable. How do we determine mistakes are made in the first place. Is it determined by people?

[throw310822]

> Is it determined by people?

Could be. Machines don't need to provide all the functions of human beings to replace many workers. You can concentrate the supervision and direction function in a single person and assign the rest of the grunt job to machines. You still have replaced most of your human workers.