[ac42dgu]

Related question: What are the adversarial examples for human intelligence? We know some for the visual and auditory systems, but what about the arguably general intelligence of humans?

Maybe we can work our way backwards from the adversarial examples to the inductive biases?

[sdenton4]

'Thinking Fast and Slow' is basically all about the rough edges of human thinking.

The interesting tradeoff with ML systems is that you trade lots of individual human crap for one big pile of machine crap. The advantage of the machine crap is that you can actually go in and find systemic problems and work on fixing them at a 'global' level. On the human side, you're always going to be stuck with an unknown array of individual human biases which are incredibly difficult to correct.

[opwieurposiu]

I think fractional reserve banking has done a pretty good job of fooling everyone.