AI Researchers Fight Noise by Turning to Biology

Artificial intelligence sees things we don't -- often to its detriment. While machines have gotten incredibly good at recognizing images, it's still easy to fool them. Simply add a tiny amount of noise to the input images, undetectable to the human eye, and the AI suddenly classifies school buses, dogs or buildings as completely different objects, like ostriches. In a paper posted online in June, Nicolas Papernot of the University of Toronto and his colleagues studied different kinds of machine learning models that process language and found a way to fool them by meddling with their input text in a process invisible to humans. The hidden instructions are only seen by the computer when it reads the code behind the text to map the letters to bytes in its memory. Papernot's team showed that even tiny additions, like single characters that encode for white space, can wreak havoc on the model's understanding of the text.