“Neural networks are commonly used today to analyze complex data – for instance to find clues to illnesses in genetic information. Ultimately, though, no one knows how these networks actually work exactly. That is why Fraunhofer researchers developed software that enables them to look into these black boxes and analyze how they function. The researchers will present their software at CeBIT in Hannover from March 20 to 24, 2017 (Hall 6, Booth B 36). The problem is that it isn’t just researchers who currently don’t know exactly how neural networks function step by step, or why they reach one result or another. Neural networks are, in a sense, black boxes – computer programs that people feed values into and that reliably return results. If you want to teach a neural network, for instance, to recognize cats, then you instruct the system by feeding it thousands of cat pictures. Just like a small child that slowly learns to distinguish cats from dogs, the neural network, too, learns automatically. “In many cases, though, researchers are less interested in the result and far more interested in what the neural network actually does – how it reaches decisions,” says Dr. Wojciech Samek, head of the Machine Learning Group at Fraunhofer Heinrich Hertz Institute HHI in Berlin. So Samek and his team, in collaboration with colleagues from TU Berlin, developed a method that makes it possible to watch a neural network think.”