To protect artificial intelligence from attacks, show it fake data

AI systems can sometimes be tricked into seeing something that's not actually there, as when Google's software "saw" a 3-D-printed turtle as a rifle. A way to stop these potential attacks is crucial before the technology can be widely deployed in safety-critical systems like the computer vision software behind self-driving cars. At MIT Technology Review's annual EmTech Digital conference in San Francisco this week, Google Brain researcher Ian Goodfellow explained how researchers can protect their systems. Goodfellow is best known as the creator of generative adversarial networks (GANs), a type of artificial intelligence that makes use of two networks trained on the same data. One of the networks, called the generator, creates synthetic data, usually images, while the other network, called the discriminator, uses the same data set to determine whether the input is real.