Exploring explainable AI: a bibliometric analysis
Chetan Sharma, Shamneesh Sharma, Komal Sharma, Ganesh Kumar Sethi, Y-H. Chen
Abstract
Over the past few years, explainable artificial intelligence (XAI) has become increasingly popular as a result of the demand for AI systems that are simpler to comprehend and with greater interpretability. This study provides a conceptual framework and a quick assessment of the work done in explainable artificial intelligence. Using the Vosviewer application, the researchers analyzed 4781 research publications from the Scopus database, spanning 2004 to 2023. Observations indicate a rapid and exponential growth in the quantity of publications, commencing in 2018. The importance of the study is shown by the analysis of publishing activities according to the year of publication and the geographical area, together with citation analysis, research methodologies, and data analysis techniques. The researchers have highlighted ten interesting areas that require further study from future researchers. Moreover, the work emphasizes the legal, ethical, and social consequences for the researchers.