Comment by cryptonector
4 hours ago
On the other hand AI used well, and use of AI taught well, could really help. Instead of one teacher trying to teach 23 kids in a classroom they can teach them how to get the AI to teach each one in an individualized way. The problem will lie in making sure that each student does that rather than waste time.
Imho, this will be the key goal of gen 1.5 AI products that start delivering real-world efficiency at scale: multiplying output rather than full human replacement.
In almost every transformational AI use case, the economics don't distinguish between automating 80% of the work and 100% of the work, because there are upstream or downstream limitations that will take a decade to work out.
And at 80% automation, you're already 5x'ing someone's productivity (naive assumptions, etc etc), which translates into either 5x the supply of a good (same labor pool) or 1/5 labor costs (same output).
Granted, Amdahl's law applies [0], and there are going to be fractions unsuitable to automation.
But it feels like AI tech is relearning a computing lesson that's always been true: do the easy things first (cooperative systems with humans) and then tackle the harder things (100% end to end automation).
[0] https://en.wikipedia.org/wiki/Amdahl%27s_law