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Artificial Intelligence May Not 'Hallucinate' After All

What makes an algorithm mistake a helicopter for a gun? Researchers think the answer has to do more with man than machine.

Thanks to advances in machine learning, computers have gotten really good at identifying what’s in photographs. They started beating humans at the task years ago, and can now even generate fake images that look eerily real. While the technology has come a long way, it’s still not entirely foolproof. In particular, researchers have found that image detection algorithms remain susceptible to a class of problems called adversarial examples.

Adversarial examples are like optical (or audio) illusions for AI. By altering a handful of pixels, a computer scientist can fool a machine learning classifier into thinking, say, a picture of a rifle is actually one of a helicopter. But to you or me, the image still would look like a gun—it almost seems like the algorithm is hallucinating. As image recognition technology is used in more places, adversarial examples may present a troubling security risk. Experts have shown they can be used to do things like cause a self-driving car to ignore a stop sign, or make a facial recognition system falsely identify someone.

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