A Bibliometric Analysis of the Explainable Artificial Intelligence Research Field

被引：46

作者：

Alonso, Jose M. ^{[1
]}

Castiello, Ciro ^{[2
]}

Mencar, Corrado ^{[2
]}

机构：

[1] Univ Santiago de Compostela, Ctr Singular Invest Tecnol Informac CiTIUS, Santiago De Compostela, Spain

[2] Univ Bari Aldo Moro, Dept Informat, Bari, Italy

来源：

INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS: THEORY AND FOUNDATIONS, IPMU 2018, PT I | 2018年 / 853卷

关键词：

Interpretability; Understandability; Comprehensibility; Explainable AI; Interpretable Fuzzy Systems; SYSTEMS; ACCURACY;

D O I：

10.1007/978-3-319-91473-2_1

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：3 / 15

页数：13

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