Artificial Intelligence and Economic Development: A Review of a recent Publication on AI & ED for Scholars

Abstract

This is a review of a recent article on the intersection area of Artificial Intelligence and Economic Development (Article: ). It is the intention of this review to focus mainly on the needs of researchers with interest in the updated relevant scholarly output.

The content refers to the publication and in this review we identify findings touching on the goal of the review.

In today’s environment of the rapid rise of Artificial Intelligence (AI), debate con- tinues about whether it has beneficial effects on economic development. However, there is only a fragmented perception of what role and place AI technology actually plays in Economic Development (ED). The paper in review, pioneers the research by focusing the detective work and discussion on the intersection of AI and economic development. Specifically, they adopt a two-step methodology. At the first step, they analyze 2211 documents in the AI&ED field using the bibliometric tool Bibliometrix, presenting the internal structure and external characteristics of the field through different metrics and algorithms. In the second step, they perform a qualitative content analysis of clusters calculated from the bibliographic coupling algorithm, detailing the content directions of recently distributed topics in the AI&ED field from different perspectives. The results of the bibliometric analysis suggest that the number of publications in the field has grown exponentially in recent years, and the most relevant source is the “Sustainability” journal. In addition, deep learning and data mining-related research are the key directions for the future. On the whole, scholars have dedicated to the field and developed close cooperation and communication across the board. Also, the content analysis demonstrates that most of the research is centered on the five facets namely, intelligent decision-making, social governance, labour and capital, Industry 4.0, and innovation. The results provide a forward- looking guide for scholars to grasp the current state and potential knowledge gaps in the AI&ED field.