AB’s post is inspiring because it touches on an intuition I’ve had that I haven’t seen discussed too much in the technological unemployment debate.

The thing that we think humans are good at is actually what they are terrible at. Namely: reason, logic, strict formal rule-following.

As Kahneman or Baumeister or any psychologist will tell you, something thinking through a lot of math equations is extremely hard for us. Multiplying 3,464,900 by 4,562 in your head without recourse to pen and paper puts a strain on you, and it doesn’t take many such math problems before your capabilities are compromised and you start giving inaccurate answers.

Once we have the concepts of numbers and multiplication, automating that process just makes sense. A cheap computer can give you the right answer to the above question in a fraction of a second. Human laborers will never outperform automation once the algorithm-makers have isolated the nature of what needs to be done over and over.

But that brings us back to AB’s post. Computers aren’t so great at discovery. As AB put it:

But where do these algorithms come from? Who tells the robot how to make a better hamburger? I’ll tell you one thing, it sure isn’t going to be a computer programmer who can’t make anything fancier than ramen noodles himself.

Substitute for “hamburger” the next great X. In AB’s post, it’s the next great line of Toyotas. But X can be just about anything. And it’s hard to believe that finding it will always or even mostly take PhD level skills. The lion’s share of the advancements from the Industrial Revolution came from tinkerers discovering through rote trial and error. Perhaps Tyler Cowen is correct that we have used up all the low hanging fruit in this regard (I’m skeptical), but it seems unlikely that we have exploited many of the possibilities of combining this discovery process with after the fact automation.