In deep learning, at times the model remains opaque to the user. It is called a black box. It is not easy to decipher how the model functions and how it makes predictions. Its internal working is not known.

This criticism is often levelled against deep neural networks — they are non-transparent and their predictions are not traceable by humans.

Black Box Models

These are used in a number of industries. They are used to predict behaviour of complex systems without fully comprehending how these work. Insurance industry uses Black Box Modelling. It predicts the probability of future claims. Aviation is another industry that uses Black Box. It has to predict manpower requirements during different parts of the day and days of the week. Movies too use Black Box to predict the production cost of a new movie. In financial modelling too, these models are used.

Disadvantages

Tests run by the designer are redundant. Testing is difficult. Results could be over-estimated. These cannot be used for testing code of complex segments.

Advantages

These make predictions about complex systems.