Kreinovich V. Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques

Springer Cham, 2022. — 130 p. — (Studies in Computational Intelligence, volume 1047). — ISBN: 978-3-031-09974-8.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 a natural-language explanation of the numerical AI recommendations. The need to connect natural language rules and numerical decisions is known since the 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, which 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.True PDF