To work with human unpredictability, different methods are needed to ensure that humans and machines work together.
Complex Inference is one of the important principles that is used in the artificial intelligence concept, as a new form that is used for teaching machines to know how autonomous conclusions are drawn, to know how the action of objects or people could be anticipated. The principle described is still in practice that is completely new and needs to run long.
As per the current method used in artificial intelligence, it is based on deep learning technology to recognize huge data set patterns. But one of the things that are important in machine learning is to ask themselves: “How will my actions affect the actions of people around me?”
To make the situation more complicated in an industrial environment, transparency is one of the most important requirements where the given production targets can be ensured to achieve whereas deep learning technology is exactly the opposite. The patterns are recognized by training the system but the control is lost that how conclusions are reached by its system.
But transparency is something very important requirement in Artificial Intelligence to make it explainable and let people accept it and make it understand how a black box is actually working?
Source:- Elektronik Praxis