Comment by ethbr1

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