MIT researchers are working to create neural networks that are no longer black boxes

But that is not to say it is perfect by any stretch of the imagination. "Deep learning has led to some big advances in computer vision, natural language processing, and other areas," Tommi Jaakkola, a Massachusetts Institute of Technology professor of electrical engineering and computer science, told Digital Trends. "It's tremendously flexible in terms of learning input/output mappings, but the flexibility and power comes at a cost. That is it that it's very difficult to work out why it is performing a certain prediction in a particular context." This black-boxed lack of transparency would be one thing if deep learning systems were still confined to being lab experiments, but they are not.