7 Revealing Ways AIs Fail
Artifical Intelligence could perform more quickly, accurately, reliably, and impartially than humans on a wide range of problems, from detecting cancer to deciding who receives an interview for a job. But AIs have also suffered numerous, sometimes deadly, failures. And the increasing ubiquity of AI means that failures can affect not just individuals but millions of people.
Part of the problem is that the neural network technology that drives many AI systems can break down in ways that remain a mystery to researchers. Scientists discuss possible ways to deal with some of these problems; others currently defy explanation or may, philosophically speaking, lack any conclusive solution altogether.
Full article: 7 Revealing Ways AIs Fail – IEEE Spectrum
