A bibliometric analysis of the explainable artificial intelligence research field

This paper presents the results of a bibliometric study of the recent research in eXplainable Artificial Intelligence (XAI) systems. We took a global look at the contributions of scholars in XAI as well as the subfields of AI that are mostly involved in the development of XAI systems. It is worthy to remark that we found out that about one third of contributions in XAI came from the fuzzy logic community. Accordingly, we went in depth with the actual connections of fuzzy logic contributions with AI to promote and improve XAI systems in the broad sense. Finally, we outlined new research directions aimed at strengthening the integration of different fields of AI, including fuzzy logic, toward the common objective of making AI accessible to people.

keywords: Interpretability, Understandability, Comprehensibility, Ex- plainable AI, Interpretable Fuzzy Systems