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AI failures of 2016

AI has seen a renaissance over the last year, with developments in driverless vehicle technology, voice recognition, and the mastery of the game “Go,” revealing how much machines are capable of.

But with all of the successes of AI, it’s also important to pay attention to when, and how, it can go wrong, in order to prevent future errors. 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.

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