[js8]

Maybe, you know, humans are simply not Chinese rooms.

Recently there was an article about recognition of bullshit: https://news.ycombinator.com/item?id=17764348

To me the article brought great insight - I realized that humans do not just pattern match. They also seek understanding, which I would define as an ability to give a representative example.

It is possible to give somebody a set described by arbitrarily complex conditions while the set itself is empty. Take any satisfiability problem (SAT) with no solution - this is a set of conditions on variables, yet there is no global solution to these.

So if you were a Chinese room and I would train you on SAT problems, by pure pattern matching, you would be willing to give solutions to unsolvable instances. It is only when you actually understand the meaning behind conditions you can recognize that these arbitrary complex inputs are in fact just empty sets.

So perhaps that's the flaw with our algorithms. There is no notion of I understand the input. Perhaps it is understandable, because understanding (per above) might as well be NP-hard.

[int_19h]

Humans can do more than pattern-match. But they often just pattern-match anyway, because it's far easier and quicker, and doing more than that for all the brief day-to-day interactions is virtually impossible.

So at some point you need to decide when you pattern-match and accept the result for granted, and when you decide to dig into it further to understand why the pattern matched the way it did, and whether it's relevant. But that is itself a choice, and it's also going to be biased (for example, towards people you personally know, and against random strangers).

[adrianN]

There is no indication that brains are better at solving NP hard problems than computers.

[js8]

That is not my argument at all. What I argue is that brains attempt to resolve the problem, while computers (when they pattern match in typical ML algorithm) do not.

It is possible that brain has specialized circuits to solve small instances of SAT, and it just gives up on large enough instance. I am sure you know the feeling that you get when you understand something - it's very much like the pieces of the puzzle that suddenly perfectly fit to each other.