ISBN:
9783031099748
Language:
English
Pages:
1 Online-Ressource(X, 130 p. 31 illus.)
Edition:
1st ed. 2022.
Series Statement:
Studies in Computational Intelligence 1047
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Keywords:
Computational intelligence.
;
Artificial intelligence.
;
Engineering—Data processing.
Abstract:
Why Explainable AI? Why Fuzzy Explainable AI? What Is Fuzzy? -- Defuzzification -- Which Fuzzy Techniques? -- So How Can We Design Explainable Fuzzy AI: Ideas -- How to Make Machine Learning Itself More Explainable -- Final Self-Test.
Abstract:
Modern AI techniques –- especially deep learning –- provide, in many cases, very good recommendations: where a self-driving car should go, whether to give a company a loan, etc. The problem is that not all these recommendations are good -- and since deep learning provides no explanations, we cannot tell which recommendations are good. It is therefore desirable to provide natural-language explanation of the numerical AI recommendations. The need to connect natural language rules and numerical decisions is known since 1960s, when the need emerged to incorporate expert knowledge -- described by imprecise words like "small" -- into control and decision making. For this incorporation, a special "fuzzy" technique was invented, that led to many successful applications. This book described how this technique can help to make AI more explainable.The book can be recommended for students, researchers, and practitioners interested in explainable AI.
DOI:
10.1007/978-3-031-09974-8
