A recent paper by Roman Yampolskiy, director of the Cybersecurity Lab at the University of Louisville, outlines a history of AI failures which are “directly related to the mistakes produced by the intelligence such systems are designed to exhibit.” According to Yampolskiy, these types of failures can be attributed to mistakes during the learning phase or mistakes in the performance phase of the AI system.
Here is TechRepublic’s top 10 AI failures from 2016, drawn from Yampolskiy’s list as well as from the input of several other AI experts.
Bruce Buchanan