Accidents, including deadly ones, caused by software or industrial robots, can be traced to the early days of such technology but they are not a direct consequence of the particulars of the intelligence available in such systems. AI failures, on the other hand, are directly related to the mistakes produced by the intelligence that such systems are designed to exhibit.
We can broadly classify such failures into mistakes during the learning phase and mistakes during performance phase. The system can fail to learn what its human designers want it to learn and instead learn a different, but correlated function. A frequently cited example is a computer vision system which was supposed to classify pictures of tanks but instead learned to distinguish backgrounds of such images [3].
See the full story here: https://mindmatters.ai/2020/07/ai-will-fail-like-everything-else-eventually/