Deep learning has deep problems

But according to IEEE Spectrum the inability of a typical deep learning program to perform well on more than one task, for example, severely limits the application of the technology to specific tasks in rigidly controlled environments. More seriously deep learning is untrustworthy because it is not explainable -- and unsuitable for some applications because it can experience catastrophic forgetting. If the algorithm works, it may be impossible to fully understand why. And while the tool is slowly learning a new database, an arbitrary part of its learned memories can suddenly collapse. Therefore, it might be risky to use deep learning on any life-or-death application, such as a medical one.