The Open AI researchers were intrigued by a claim that self-driving cars would be intrinsically hard to fool (tricking them into sudden braking maneuvers, say), because “they capture images from multiple scales, angles, perspectives, and the like.”
So they created a set of image-presentation techniques that reliably trick image classifiers, showing that their tricks work from different angles, at different scales, and after transformations.
