Concerns Using Machine Learning in Software Development - UrIoTNews

There can be a propensity to view ML as a be-all, end-all solution, but it's not. It's imperative developers adhere to traditional SDLC protocols to produce quality products. Developing and optimizing an ML model has too many hyperparameters. It is hard to distinguish a failure of the method versus bad parameter choice. If the model is used for multiple tasks, it is hard to make sure incremental improvements for one tasks are not going to break others.