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Exactly. A human would usually make "acceptably incorrect" decisions, such as not indicating, or speeding. But these mistakes generally don't end in disaster. Only occasionally making a really bad mistake ending in an accident. So out of those 13%, it might only end up with <0.1% overall as accidents, the rest being recoverable.

Whereas the uncontrolled randomness of computer mistakes could be horrendous. Hence why I'm saying an interesting avenue to look at in AI, might be to achieve acceptably incorrect answers (acceptable negatives), rather than just aiming for high true-positive and low false-positive rates.




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