A hacked message in a streamed song makes Alexa send money to a foreign entity. A self-driving car crashes after a prankster strategically places stickers on a stop sign so the car misinterprets it as a speed limit sign. Fortunately these haven’t happened yet, but hacks like this, sometimes called adversarial attacks, could become commonplace—unless artificial intelligence (AI) finds a way to outsmart them. Now, researchers have found a new way to give AI a defensive edge, they reported here last week at the International Conference on Learning Representations.
The work could not only protect the public. It also helps reveal why AI, notoriously difficult to understand, falls victim to such attacks in the first place, says Zico Kolter, a computer scientist at Carnegie Mellon University, in Pittsburgh, Pennsylvania, who was not involved in the research. Because some AIs are too smart for their own good, spotting patterns in images that humans can’t, they are vulnerable to those patterns and need to be trained with that in mind, the research suggests.
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