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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

A Bibliometric Analysis of the Explainable Artificial Intelligence Research Field

verfasst von : Jose M. Alonso, Ciro Castiello, Corrado Mencar

Erschienen in: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

Verlag: Springer International Publishing

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Abstract

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.

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Nächstes Kapitel Do Hierarchical Fuzzy Systems Really Improve Interpretability?
Fußnoten
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Informatics Research Evaluation (Draft), An Informatics Europe Report. http://​www.​informatics-europe.​org/​working-groups/​research-evaluation.​html.
 
3
The graph was generated by the VOS viewer employing the suggested default parameters for layout visualization and clustering of nodes. Other clustering approaches may be applied, but choosing the best approach is out of the scope of this paper.
 
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Metadaten
Titel
A Bibliometric Analysis of the Explainable Artificial Intelligence Research Field
verfasst von
Jose M. Alonso
Ciro Castiello
Corrado Mencar
Copyright-Jahr
2018
Buch
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

Print ISBN: 978-3-319-91472-5

Electronic ISBN: 978-3-319-91473-2

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-91473-2_1