Where Predictive Machine Learning Falls Short and What We Can Do About It - insideBIGDATA

Even at this early stage of the game, machine learning holds much promise, and is being applied to incredibly diverse fields – autonomous driving, medical screening, and supply-chain management. In many of these fields, the application of the technology has been extremely successful, predicting consumer demand and the outbreak of pandemics much more reliably than human intelligence. However, there remain some problems with the basic way in which machine learning works. ML algorithms require huge amounts of data, and data processing capability, to provide reliable predictions. Even if these resources are available, the algorithms can fail.