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An example is the halting problem, which states computing cannot be solved by exhaustion, but which humans avoid trivially by becoming exhausted.

Humans typically give up what seems like a lost cause after a certain point, whereas a computer will just keep chugging along.

  • Do flaws have utility?

Can inability be a strength and will AGI require such limitations to achieve human-level intelligence? Humans are simply not capable of infinite loops, except arguably in cases of mental illness. Are there other problems similar to the halting problem where weakness is a benefit?

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    $\begingroup$ It's not clear to me why you claim that humans can solve the halting problem. If that was true, that would imply that there are functions that Turing machines cannot compute, so there are more powerful computers than Turing machines, which, as far as I know, has not yet been proven (see the Church-Turing thesis). $\endgroup$
    – nbro
    Commented Jun 5, 2021 at 1:22
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    $\begingroup$ I agree with nbro, I think you need to make it a little clearer that you don't mean "give up" = "solve". Other than that, I think this could be an interesting question about utility and embodiment (at least that would be my take on what leads to an answer) $\endgroup$
    – Neil Slater
    Commented Jun 5, 2021 at 8:04
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    $\begingroup$ Computers can also give up after a certain point. This is one way that algorithms are made to have guaranteed halting: by including a counter that ends the algorithm after a certain number of steps, if not halted before. A more physical analogy is running the computer off a battery. Then when it runs out of power it will stop through 'exhaustion' like a human. You said "give up what seem like a lost cause" which to me is very different from exhaustion -- it is more that the human has guessed their procedure does not halt and therefore terminates early. I don't really see that as a flaw. $\endgroup$
    – user7834
    Commented Jun 12, 2021 at 17:17
  • $\begingroup$ @NeilSlater & nbro — good point. I should have used "solved" and replaced it with "avoid". Basically, nature seems to produce that which is minimally optimal, and designs are often flawed but just adequate enough. Workarounds seem to be our holy grail in much of computer development. $\endgroup$
    – DukeZhou
    Commented Jun 17, 2021 at 22:44
  • $\begingroup$ @user7834 I think that's a solid answer, because workarounds have high utility in applied computing, even when not optimal solutions. Wondering if there are other "flaws" that would be useful too #FeatureNotABug $\endgroup$
    – DukeZhou
    Commented Jun 18, 2021 at 1:02

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