A Bibliometric Analysis of the Explainable Artificial Intelligence Research Field

• Published in: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations Vol. 853; pp. 3 - 15
• Main Authors: Alonso, Jose M., Castiello, Ciro, Mencar, Corrado
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Comprehensibility; Explainable AI; Interpretability; Interpretable Fuzzy Systems; Understandability
• ISBN: 9783319914725; 3319914723
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-319-91473-2_1

This paper presents the results of a bibliometric study of the recent research on eXplainable Artificial Intelligence (XAI) systems. We took a global look at the contributions of scholars in XAI as well as in 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 come 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.