To human observers, the following two images are identical. But researchers at Google showed in 2015 that a popular object detection algorithm classified the left image as “panda” and the right one as ...

Machine learning, for all its benevolent potential to detect cancers and create collision-proof self-driving cars, also threatens to upend our notions of what's visible and hidden. It can, for ...

The vulnerabilities of machine learning models open the door for deceit, giving malicious operators the opportunity to interfere with the calculations or decision making of machine learning systems.

The study, titled Conditional Adversarial Fragility in Financial Machine Learning under Macroeconomic Stress, published as a ...

A neural network looks at a picture of a turtle and sees a rifle. A self-driving car blows past a stop sign because a carefully crafted sticker bamboozled its computer vision. An eyeglass frame ...

Much of the anti-adversarial research has been on the potential for minute, largely undetectable alterations to images (researchers generally refer to these as “noise perturbations”) that cause AI’s ...

Artificial intelligence won’t revolutionize anything if hackers can mess with it. That’s the warning from Dawn Song, a professor at UC Berkeley who specializes in studying the security risks involved ...

Machines' ability to learn by processing data gleaned from sensors underlies automated vehicles, medical devices and a host of other emerging technologies. But that learning ability leaves systems ...