Autonomous vehicles generally use deep neural network algorithms to “recognize” images. The car’s LIDAR recognizes an obstacle, the camera takes a picture of it, and the computer uses a deep neural network to identify the image as a stop sign. The car’s acceleration system is programmed to slow down and brake when a stop sign is a set distance ahead. Alternatively, the car’s internal map can be programmed to stop at a particular set of GPS coordinates where a human engineer notices that the car fails recognizing a stop sign.
However, deep neural networks are the same type of image-recognition algorithms that misidentified photos of Black people as gorillas. Laboratory tests reveal that deep neural networks are easily confused by minor changes. Something simple, like putting a sparkly unicorn sticker on a stop sign, can cause the image recognition to fail. Disrupting image recognition would result in a self-driving car failing to stop at a stop sign, which is likely to cause an accident or more pedestrian injuries.