ABSTRACT
Most artificial explainability methods relate to the explainability of machine learning, including deep learning. There is a small amount of research on the issue of the explainability of cognitive technologies based on the cognitive cycle, which processes knowledge represented in a symbolic and hybrid, symbolic-numeric way. The aim of the chapter is to assess the explainability issues of cognitive technologies used for sustainable decision support. A systematic literature review methodology is used in the research. The main findings concern systematizing existing knowledge related to the explainability of cognitive technologies used for sustainable decision support. The main scientific contribution of the research is to assess approaches to the explainability of cognitive technologies used for sustainable decision support, and to indicate research gaps in this area. The main contribution to practice is the indication of the possibility of using symbolic and hybrid cognitive technologies for improving sustainable decision support systems.
