Explainable Artificial Intelligence (eXAI): Applications

Author: Papuna Qarchava
Co-authors: G.Besiashvili, P.Qarchava
Keywords: artificial intelligence, machine learning, explainable AI; human-AI interaction
Annotation:

The purpose of this explainable artificial intelligence is to answer the question of how an intelligent system makes its “intelligent” decisions. To be able to understand how the so-called “black box “ functions, how well-known methods and algorithms of machine learning work. Utilizing this knowledge is important for engineers and customers. To solve this problem, special explanatory modules are developed for studying, thinking, interpreting and interpreting artificial intelligence algorithms that will explain why the model made such a decision. In addition, this information may be used in the future to increase productivity and adapt machine learning models. Areas of application of the new method, business, industry, medicine ... work is increasing and competition is very high, Google, Microsoft, IBM…